├── .DS_Store ├── .gitignore ├── CONTRIBUTING.md ├── LICENSE ├── README.md ├── _build ├── changelogindex.hbs ├── config.yaml ├── css │ ├── bootstrap.min.css │ └── main.css ├── datasets.hbs ├── detail.hbs ├── examples.hbs ├── font │ ├── roboto-v20-latin-100.eot │ ├── roboto-v20-latin-100.svg │ ├── roboto-v20-latin-100.ttf │ ├── roboto-v20-latin-100.woff │ ├── roboto-v20-latin-100.woff2 │ ├── roboto-v20-latin-300.eot │ ├── roboto-v20-latin-300.svg │ ├── roboto-v20-latin-300.ttf │ ├── roboto-v20-latin-300.woff │ ├── roboto-v20-latin-300.woff2 │ ├── roboto-v20-latin-500.eot │ ├── roboto-v20-latin-500.svg │ ├── roboto-v20-latin-500.ttf │ ├── roboto-v20-latin-500.woff │ ├── roboto-v20-latin-500.woff2 │ ├── roboto-v20-latin-700.eot │ ├── roboto-v20-latin-700.svg │ ├── roboto-v20-latin-700.ttf │ ├── roboto-v20-latin-700.woff │ ├── roboto-v20-latin-700.woff2 │ ├── roboto-v20-latin-900.eot │ ├── roboto-v20-latin-900.svg │ ├── roboto-v20-latin-900.ttf │ ├── roboto-v20-latin-900.woff │ ├── roboto-v20-latin-900.woff2 │ ├── roboto-v20-latin-regular.eot │ ├── roboto-v20-latin-regular.svg │ ├── roboto-v20-latin-regular.ttf │ ├── roboto-v20-latin-regular.woff │ └── roboto-v20-latin-regular.woff2 ├── img │ ├── external │ │ ├── edc_banner.png │ │ └── world.png │ ├── favicon.ico │ ├── logos │ │ ├── planet-logo.svg │ │ └── sinergise-logo.png │ ├── map-pin.svg │ └── sentinel-hub-logo.png ├── index.hbs ├── js │ ├── bootstrap.min.js │ ├── index.js │ ├── jquery.min.js │ └── tags.js ├── partials │ ├── about.hbs │ ├── collectionsList.hbs │ ├── detailList.hbs │ ├── footer.hbs │ ├── header.hbs │ ├── interactive-map.hbs │ ├── sandbox_about.hbs │ ├── sandbox_aboutTag.hbs │ └── sandbox_collectionsList.hbs ├── providers.hbs ├── redirect.hbs ├── rss.xml.hbs ├── sandbox_index.hbs └── sitemap.hbs ├── buildspec.yml ├── collections ├── analysis-ready-planetscope.yaml ├── analysis-ready-planetscope │ ├── ARPS_Bordeaux.png │ ├── ARPS_Des_Moines.png │ ├── ARPS_Perth.png │ ├── analysis-ready-planetscope.png │ ├── open-data.md │ ├── polygons.geojson │ └── sandbox-data.md ├── cnes-land-cover-map.yaml ├── cnes-land-cover-map │ ├── README.md │ ├── cnes-classifier-confidence-france-overview.png │ ├── cnes-classifier-confidence-lyon.png │ ├── cnes-land-cover-map-france-overview.png │ ├── cnes-land-cover-map-lyon.png │ ├── cnes-land-cover-validity-france-overview.png │ └── cnes-land-cover-validity-lyon.png ├── copernicus-dem.yaml ├── copernicus-dem │ └── copernicus-dem.png ├── corine-land-cover-accounting-layers │ ├── README.MD │ ├── istanbul-turkey.png │ ├── po-italy.png │ └── thumbnail.png ├── corine-land-cover │ ├── README.MD │ ├── corine-land-cover.png │ ├── image_alps.png │ └── image_fdoms.png ├── crop-biomass.yaml ├── crop-biomass │ ├── crop-biomass.png │ └── open-data.md ├── forest-carbon-diligence.yaml ├── forest-carbon-diligence │ ├── FCD_BRA.png │ ├── FCD_FRA.png │ ├── FCD_USA.png │ ├── forest-carbon-diligence.png │ ├── polygons.geojson │ └── sandbox-data.md ├── forest-carbon-monitoring.yaml ├── forest-carbon-monitoring │ ├── FCM_LAOS.jpg │ ├── FCM_MADAGASCAR.jpg │ ├── FCM_USA.jpg │ ├── forest-carbon-monitoring.png │ ├── polygons.geojson │ └── sandbox-data.md ├── global-human-settlement-layer-ghs-built-s2 │ ├── README.MD │ ├── ghsl_overview.png │ ├── ghsl_paris.png │ └── global-human-settlement-layer-ghs-built-s2.png ├── global-land-cover │ ├── Dominican_republic_forest_type.png │ ├── README.MD │ ├── global-land-cover.png │ └── north_africa_discrete_classification.png ├── global-surface-water │ ├── README.MD │ ├── global-surface-water.png │ ├── image_change_ganges_river.png │ ├── image_extent_lake_kyoga.png │ ├── image_occurrence_danube_delta.png │ ├── image_recurrence_paddies_eluru.png │ ├── image_seasonality_salar_de_uyuni.png │ └── image_transitions_parana_river.png ├── harmonized-landsat-sentinel.yaml ├── harmonized-landsat-sentinel │ └── harmonized-landsat-sentinel.png ├── hrsi-fsc │ ├── README.MD │ ├── figure.png │ └── hrsi-fsc.png ├── hrsi-gfsc │ ├── README.MD │ ├── figure.png │ └── hrsi-gfsc.png ├── hrsi-psa │ ├── README.MD │ ├── figure.png │ └── hrsi-psa.png ├── hrsi-rlie-s1 │ ├── README.MD │ ├── extent-nordland-norway.png │ ├── qlayer-nordland-norway.png │ └── thumbnail.png ├── hrsi-rlie-s1s2 │ ├── README.MD │ ├── extent-rovaniemi-findland.png │ ├── qlayer-rovaniemi-findland.png │ └── thumbnail.png ├── hrsi-rlie-s2 │ ├── README.MD │ ├── extent-varese-como-lecco-italy.png │ ├── qlayer-varese-como-lecco-italy.png │ └── thumbnail.png ├── hrsi-sws │ ├── README.MD │ ├── figure.png │ └── hrsi-sws.png ├── hrsi-wds │ ├── README.MD │ ├── figure.png │ └── hrsi-wds.png ├── impact-observatory-lulc-map.yaml ├── impact-observatory-lulc-map │ ├── README.md │ ├── io-lulc-ganges-delta.png │ └── io-lulc.png ├── land-surface-temperature.yaml ├── land-surface-temperature │ ├── LST_AUS.png │ ├── LST_FRA.png │ ├── LST_USA.png │ ├── land-surface-temperature.png │ ├── open-data.md │ ├── polygons.geojson │ └── sandbox-data.md ├── landsat-1-5-mss-l1.yaml ├── landsat-1-5-mss-l1 │ └── landsat-1-5-mss-l1.png ├── landsat-4-5-tm-l1.yaml ├── landsat-4-5-tm-l1 │ └── landsat-4-5-tm-l1.png ├── landsat-4-5-tm-l2.yaml ├── landsat-4-5-tm-l2 │ └── landsat-4-5-tm-l2.png ├── landsat-7-etm+-l1.yaml ├── landsat-7-etm+-l1 │ └── landsat-7-etm+-l1.png ├── landsat-7-etm+-l2.yaml ├── landsat-7-etm+-l2 │ └── landsat-7-etm+-l2.png ├── landsat-8-l1.yaml ├── landsat-8-l1 │ └── landsat-8-l1.png ├── landsat-8-l2.yaml ├── landsat-8-l2 │ └── landsat-8-l2.png ├── mapzen-dem.yaml ├── mapzen-dem │ └── mapzen-dem.png ├── modis.yaml ├── modis │ └── modis.png ├── planet-basemaps.yaml ├── planet-basemaps │ ├── PB_AUS.png │ ├── PB_BRA.png │ ├── PB_FRA.png │ ├── planet-basemaps.png │ ├── polygons.geojson │ └── sandbox-data.md ├── planetscope.yaml ├── planetscope │ ├── PS_AUS.png │ ├── PS_BRA.png │ ├── PS_EGY.png │ ├── planetscope.png │ ├── polygons.geojson │ └── sandbox-data.md ├── road-and-building-detection.yaml ├── road-and-building-detection │ ├── RNB_AUS.png │ ├── RNB_BRA.png │ ├── RNB_EGY.png │ ├── polygons.geojson │ ├── road-and-building-detection.png │ └── sandbox-data.md ├── sea-ice-index │ ├── README.md │ ├── sea-ice-concentration.png │ ├── sea-ice-extent.png │ └── sea-ice.png ├── seasonal-trajectories │ ├── README.MD │ ├── erdine-turkey-august.PNG │ ├── erdine-turkey-sept.PNG │ ├── thumbnail-1.png │ └── thumbnail.png ├── sentinel-1-grd.yaml ├── sentinel-1-grd │ └── sentinel-1-grd.png ├── sentinel-2-l1c.yaml ├── sentinel-2-l1c │ └── sentinel-2-l1c.png ├── sentinel-2-l2a.yaml ├── sentinel-2-l2a │ └── sentinel-2-l2a.png ├── sentinel-3-l1b-olci │ └── sentinel-3-l1b-olci.png ├── sentinel-3-l1b-slstr │ └── sentinel-3-l1b-slstr.png ├── sentinel-5p-l2-tropomi │ └── sentinel-5p-l2-tropomi.png ├── sentinel-s2-l2a-mosaic-120.yaml ├── sentinel-s2-l2a-mosaic-120 │ ├── 2019_images │ │ ├── image.png │ │ └── timelapse.gif │ ├── README.MD │ ├── sentinel-2-l2a-120m-mosaic-2019.MD │ ├── sentinel-2-l2a-120m-mosaic.png │ ├── sentinel-s2-l2a-mosaic-120-2020.png │ ├── sentinel-s2-l2a-mosaic-120.png │ ├── world_mosaic_2020.png │ ├── world_mosaic_2020_blue_marble.gif │ ├── world_mosaic_2020_blue_marble.png │ └── world_mosaic_2020_blue_marble_3d.gif ├── skysat.yaml ├── skysat │ ├── SS_AUS.png │ ├── SS_EGY.png │ ├── polygons.geojson │ ├── sandbox-data.md │ └── skysat.png ├── soil-water-content.yaml ├── soil-water-content │ ├── SWC_AUS.png │ ├── SWC_FRA.png │ ├── SWC_USA.png │ ├── open-data.md │ ├── polygons.geojson │ ├── sandbox-data.md │ └── soil-water-content.png ├── vegetation-indices │ ├── README.MD │ ├── south-tyrol-northern-italy-fapar.png │ ├── south-tyrol-northern-italy-ndvi.png │ ├── south-tyrol-northern-italy-ppi.png │ └── thumbnail.png ├── vegetation-phenology-and-productivity-parameters-season-1 │ ├── README.MD │ ├── eosv-candasnos-spain-2019.PNG │ ├── maxv-candasnos-spain-2019.PNG │ ├── sosv-candasnos-spain-2019.PNG │ └── thumbnail.png ├── vegetation-phenology-and-productivity-parameters-season-2 │ ├── README.MD │ ├── maxv-candasnos-spain-2019.PNG │ ├── sosv-candasnos-spain-2019.PNG │ ├── sprod-candasnos-spain-2019.PNG │ ├── thumbnail.png │ └── tprod-candasnos-spain-2019.PNG ├── water-bodies │ ├── Bakhtegan-occurrence.PNG │ ├── README.MD │ ├── baikal-water.PNG │ └── water-bodies.png ├── worldcover.yaml ├── worldcover │ ├── README.MD │ ├── manaus_brazil.png │ ├── south_romania.png │ └── thumbnail.png ├── worldview-geoeye.yaml └── worldview-geoeye │ └── worldview-geoeye.png ├── examples └── how_to_access_public_collections.ipynb ├── gulpfile.js ├── package-lock.json └── package.json /.DS_Store: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/.DS_Store -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | /node_modules 2 | /npm-debug.log 3 | /tmp 4 | /docs 5 | /.settings/ 6 | /.project 7 | /.pydevproject 8 | /.env 9 | /_output 10 | /_tmp 11 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Sentinel Hub Collections 2 | 3 | A repository of publicly available collections that are available for access through [Sentinel Hub](https://www.sentinel-hub.com/). Note that collections in this registry are available via Sentinel Hub, but owned and maintained by different providers. 4 | 5 | ## What is it for? 6 | 7 | When data is shared on Sentinel Hub, anyone can analyze it and build services on top of it using a broad range of compute and data analytics products. Sharing data in the cloud lets data users spend more time on data analysis rather than data acquisition. This repository exists to help people promote and discover datasets that are available via Sentinel Hub resources. 8 | 9 | ## Logos 10 | You can add logos to the `src/img/logos` directory for use in the **detail** pages. Logos should be square PNGs and are currently sized down to 100px x 100px for display. The name of the logo file that the template looks for is tied to the entry in the `ManagedBy` data field. Spaces are replaced with '-' and special characters are removed. If the `ManagedBy` field is using markdown, the link text field is used, otherwise, the entire string is used to generate the logo path for testing. 11 | 12 | ## Endpoints 13 | - `/` - Main datasets listing page, provides search mechanism. 14 | - `ex: /sentinel-2-l1c` - Individual detail pages for each collection, contains details, license, contact, documentation and example usage links and resources available. 15 | - `/usage-examples/` - Lists all usage examples grouped by collection. 16 | - `/index.yaml` - YAML formatted listing of each individual YAML file for provided collections. 17 | - `/index.ndjson` - NDJSON formatted listing of each individual YAML file for provided collections. 18 | - `ex: /tag/satellite-imagery/` - Tag-subsetted view of the main collection listing page. 19 | - `ex: /tag/satellite-imagery/usage-examples/` - Tag-subsetted list usage examples grouped by collection. 20 | - `ex: /tag/satellite-imagery/datasets.yaml` - YAML for all datasets associated with a tag. 21 | - `ex: /collections/sentinel-2-l1c.yaml` - YAML for individual collection, used to create the HTML pages. 22 | - `/sitemap.txt` - Sitemap listing all the HTML pages. 23 | - `/providers.html` - A simple listing of logos of data providers. 24 | 25 | ## Redirects 26 | By using the redirects map in `src/config.yaml` you can set up simple HTML redirects from `source` to `target`. This does not copy any content, simply creates a new HTML page. This function runs after other HTML content is generated so it can be used to create new or overwrite existing HTML pages. 27 | 28 | ## Attribution 29 | This application is based on [Open Data Registry](https://github.com/awslabs/open-data-registry) by AWS Open Data team. 30 | 31 | -------------------------------------------------------------------------------- /_build/changelogindex.hbs: -------------------------------------------------------------------------------- 1 | 2 | 3 | {{> header isHome=isHome}} 4 | 5 | {{> about}} 6 |
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Collections Additions

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{{@key}}

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{{Name}}

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Usage examples for all collections listed in the Sentinel Hub Collections{{#if tag}} tagged with {{tag}}{{/if}}.

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{{Name}}

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| 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | -------------------------------------------------------------------------------- /_build/img/logos/sinergise-logo.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/_build/img/logos/sinergise-logo.png -------------------------------------------------------------------------------- /_build/img/map-pin.svg: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | -------------------------------------------------------------------------------- /_build/img/sentinel-hub-logo.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/_build/img/sentinel-hub-logo.png -------------------------------------------------------------------------------- /_build/index.hbs: -------------------------------------------------------------------------------- 1 | 2 | 3 | {{> header isHome=isHome}} 4 | 5 | {{#isEqual tag "sandbox data"}} 6 | {{> sandbox_aboutTag}} 7 | 8 | {{else}} 9 | {{> about}} 10 | 11 | {{/isEqual}} 12 | 13 | {{> collectionsList}} 14 | 15 | 16 | {{> footer}} 17 | 18 | 19 | 20 | -------------------------------------------------------------------------------- /_build/js/tags.js: -------------------------------------------------------------------------------- 1 | 'use strict'; 2 | 3 | // Listen for clicks on the tags and send to appropriate page if clicked. 4 | $('.tag').click(function () { 5 | let location = rootUrl + 'tag/' + $(this).text().replace(/ /g, '-'); 6 | window.location.href = location; 7 | }); 8 | -------------------------------------------------------------------------------- /_build/partials/about.hbs: -------------------------------------------------------------------------------- 1 |
2 |
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About

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This registry exists to help people discover and share collections that are available via Sentinel Hub.

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Search collections (currently 13 matching collections)

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You are currently viewing a subset of data tagged with {{tag}}.

{{/if}} 24 | 25 |
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Add to this registry

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If you want to add a collection or example of how to use a collection to this registry, please follow the instructions on the Sentinel Hub Collections GitHub repository.

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Unless specifically stated in the applicable collection's documentation, collections available through the Sentinel Hub Collections are not provided and maintained by Sentinel Hub. Collections are provided and maintained by a variety of third parties under a variety of licenses. Please check collection licenses and related documentation to determine if a collection may be used for your application.

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Usage examples

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    If you want to add a collection or usage example to this registry, please follow the instructions on the Sentinel Hub Collections GitHub repository.

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    Home

    9 | {{/if}} 10 | 11 | -------------------------------------------------------------------------------- /_build/partials/header.hbs: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | {{#if isHome}}{{/if}} 6 | 7 | {{#if redirect}}{{/if}} 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | {{#if isDetail}}{{Name}} - {{/if}}Sentinel Hub Collections 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | {{#if isDetail}} 26 | 36 | {{/if}} 37 | 38 | 41 | 42 | 44 | 46 | 47 | 48 | 49 | 50 | 51 | 52 | 53 | 54 | 55 | 56 | 66 |
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    4 | Planet Sandbox Data 5 | 6 |

    7 |

    Test and experience a substantial amount of Planet data samples made available under a CC-BY-NC license to all active Planet users and Sentinel Hub users with a paid subscription or a Trial account. Sandbox Data offers a subset of the WorldStrat locations and dense time-stacks, ranging from 25 to 200 km2 in size. The locations are spread across the world, assuring a stratified representation of various use cases.

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    11 | Worldstrat locations 12 |

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    Available Sandbox Data locations. Basemap from OpenStreetMap.

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    Planet's data, with its dense time series and systematic availability, makes it a perfect input to machine learning models. Sandbox Data serves as a rich and diverse set of data collections, making it possible for data scientists to build, test and validate their machine learning models without huge investment in data subscriptions, even prior to validating the business model.

    17 | 18 |
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    20 | Explore Sandbox Data via EO Browser → 21 |

    22 |
    23 | Discover the easy-to-use theme and selected higlights.* 24 |
    25 |
    26 |     27 | 28 |
    29 |

    30 | Explore Sandbox Data via Sentinel Hub APIs → 31 |

    32 |
    33 | Test in your own environment. See Jupyter Notebooks on Github.* 34 |
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    36 |     37 |

    *Available for all active Planet users and Sentinel Hub users with a paid subscription or a Trial account.

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    -------------------------------------------------------------------------------- /_build/providers.hbs: -------------------------------------------------------------------------------- 1 | 2 | 3 | {{> header}} 4 | 5 |

    Data Providers

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    14 | 15 | {{> footer}} -------------------------------------------------------------------------------- /_build/redirect.hbs: -------------------------------------------------------------------------------- 1 | 2 | 3 | {{> header redirect=target}} 4 | 5 |
    Please follow this link.
    6 | 7 | {{> footer}} 8 | -------------------------------------------------------------------------------- /_build/rss.xml.hbs: -------------------------------------------------------------------------------- 1 | 2 | 3 | Sentinel Hub Collections 4 | https://collections.sentinel-hub.com/ 5 | Collections available within Sentinel Hub 6 | en-us 7 | info@sentinel-hub.com 8 | {{buildDate}} 9 | {{#each datasets}} 10 | 11 | {{Name}} 12 | {{rootUrl}}{{Slug}} 13 | {{rootUrl}}{{Slug}} 14 | {{md Description}} 15 | 16 | {{/each}} 17 | 18 | 19 | -------------------------------------------------------------------------------- /_build/sandbox_index.hbs: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 9 | 10 | 11 | -------------------------------------------------------------------------------- /_build/sitemap.hbs: -------------------------------------------------------------------------------- 1 | {{baseURL}} 2 | {{#each slugs}} 3 | {{rootUrl}}{{.}}/ 4 | {{/each}} -------------------------------------------------------------------------------- /buildspec.yml: -------------------------------------------------------------------------------- 1 | version: 0.2 2 | 3 | phases: 4 | install: 5 | runtime-versions: 6 | nodejs: 10 7 | commands: 8 | - pip install awscli --upgrade 9 | - npm install 10 | build: 11 | commands: 12 | - npm run build 13 | - aws s3 sync _output/ $COLLECTIONS_BROWSER_S3_BUCKET --delete --acl=bucket-owner-full-control 14 | -------------------------------------------------------------------------------- /collections/analysis-ready-planetscope.yaml: -------------------------------------------------------------------------------- 1 | Name: Analysis-Ready PlanetScope 2 | Description: | 3 | Analysis-Ready PlanetScope combines the monitoring benefits of near-daily 3 m spatial imagery, while enhancing temporal and spatial consistency by informing PlanetScope data with trusted, third-party data sources (Landsat, Sentinel-2, MODIS, VIIRS). 4 | This is accomplished with a proprietary algorithm that creates pre-processed, harmonized, and spatially consistent near-daily stacks of images that enable time-series analysis and machine learning applications. The resulting 4-band data is exceedingly radiometrically and geometrically accurate thanks to vast amounts of reference data in the Planet Archive. 5 | With deeper and more extensive pre-processing, data is more precise and pre-formatted for time-series analysis and machine learning applications. Draw on the powerful, cloud-based visualization and analytical tools in Sentinel Hub to work with data that's tailored to your specific area and time of interest. 6 | Limit storage and compute costs by working with only the data you need before delivering data to your preferred GIS, data science, remote sensing, or software environments via API or OGC streaming services. 7 | Image: analysis-ready-planetscope/analysis-ready-planetscope.png 8 | SandboxData: | 9 | Discover samples of Analysis-Ready PlanetScope, free to all active Planet users and Sentinel Hub users with a paid subscription or a Trial account. [Sandbox Data for Analysis-Ready PlanetScope](https://docs.planet.com/data/imagery/arps/sandbox/) 10 | Resolution: 3 meters (resampled) 11 | GeographicalCoverage: Land surface area (more info) 12 | TemporalAvailability: January 01, 2017 - Present 13 | UpdateFrequency: New versions are released multiple times a year. 14 | TemporalResolution: Near-daily when PlanetScope imagery is available over AOI 15 | BandInformation: 16 | Table: 17 | Columns: 18 | - Name: Name 19 | Title: Name 20 | - Name: Description 21 | Title: Description 22 | Rows: 23 | - Name: blue 24 | Description: "B1" 25 | - Name: green 26 | Description: "B2" 27 | - Name: red 28 | Description: "B3" 29 | - Name: nir 30 | Description: "B4" 31 | - Name: cloud_mask 32 | Description: "Q1" 33 | - Name: scene_mask 34 | Description: "Q2" 35 | Contact: Sentinel Hub Forum on Planet Community 36 | Provider: Planet 37 | ManagedBy: "[Planet](https://www.planet.com/)" 38 | Tags: 39 | - commercial data 40 | - satellite imagery 41 | - analysis ready data 42 | - planetscope 43 | - time series 44 | - sandbox data 45 | 46 | License: License 47 | Resources: 48 | - EndPoint: services.sentinel-hub.com 49 | Type: BYOC collection 50 | Notes: Contains the data purchased by an individual user. [Explore sample CC-BY-NC sandbox data here](https://docs.planet.com/data/imagery/arps/sandbox/) 51 | CustomScripts: 52 | Title: Coming soon here 53 | URL: https://custom-scripts.sentinel-hub.com/ 54 | RegistryEntryAdded: "2024-01-15" 55 | RegistryEntryLastModified: "2024-05-10" 56 | -------------------------------------------------------------------------------- /collections/analysis-ready-planetscope/ARPS_Bordeaux.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/analysis-ready-planetscope/ARPS_Bordeaux.png -------------------------------------------------------------------------------- /collections/analysis-ready-planetscope/ARPS_Des_Moines.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/analysis-ready-planetscope/ARPS_Des_Moines.png -------------------------------------------------------------------------------- /collections/analysis-ready-planetscope/ARPS_Perth.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/analysis-ready-planetscope/ARPS_Perth.png -------------------------------------------------------------------------------- /collections/analysis-ready-planetscope/analysis-ready-planetscope.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/analysis-ready-planetscope/analysis-ready-planetscope.png -------------------------------------------------------------------------------- /collections/analysis-ready-planetscope/open-data.md: -------------------------------------------------------------------------------- 1 | # Analysis Ready PlanetScope Open Data 2 | 3 | ## Short Description 4 | 5 |

    Analysis Ready PlanetScope is Planet's medium resolution time series dataset. It is an enhanced 4-band PlanetScope data product boasting a high degree of data consistency over time. It aims to eliminate the data preparation burden inherent with minimally processed PlanetScope products (L0,L1,L2) while retaining or enhancing all of the benefits of daily imagery at 3m spatial resolution. It has been radiometrically and geometrically calibrated. It includes a temporally-developed cloud mask. This version contains "no data" values where clouds have been masked.

    6 | 7 |

    A collection of Analysis Ready PlanetScope for a limited area and time of interest is available with the CC-BY-SA license.

    8 | 9 | ## Collections 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 |
    Source IDCollection IDTime Range
    PS_ARD_SR_DAILYBYOC-b690a8ba-05c4-49dc-91c7-8484a10071762021-01-01 to 2022-12-31
    27 | 28 | ### Open Data Areas 29 | 30 | To access data over your own areas and times of interest, [contact Planet](https://www.planet.com/contact-sales/#contact-sales). 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 | 41 | 42 | 43 | 44 | 45 |
    NameGeoJSON
    Nebraska, United States{"type":"Polygon","coordinates":[[[-96.678829685,40.72955099 ],[-96.678829685, 40.951639527],[-96.386394376, 40.951639527],[-96.386394376, 40.72955099],[-96.678829685, 40.72955099]]]}
    46 | -------------------------------------------------------------------------------- /collections/analysis-ready-planetscope/polygons.geojson: -------------------------------------------------------------------------------- 1 | {"type": "FeatureCollection", "features": [{"id": "0", "type": "Feature", "properties": {"from": "2022-05-07", "to": "2023-04-29", "center_x": -93.95550602066074, "center_y": 41.2953678964555, "area_sqkm": 576.0, "collection_id": "3f605f75-86c4-411a-b4ae-01c896f0e54e", "geolocation": "Iowa, United States"}, "geometry": {"type": "Polygon", "coordinates": [[[-93.8135391103146, 41.4046686288302], [-93.81085743978488, 41.18850382513997], [-94.09699875695776, 41.18613364259365], [-94.10062635082595, 41.40228046320521], [-93.8135391103146, 41.4046686288302]]]}}, {"id": "1", "type": "Feature", "properties": {"from": "2022-05-03", "to": "2023-04-30", "center_x": -71.74689236955437, "center_y": -14.564970814738205, "area_sqkm": 575.0, "collection_id": "3f605f75-86c4-411a-b4ae-01c896f0e54e", "geolocation": "Cusco, Province of Chumbivilcas, Peru"}, "geometry": {"type": "Polygon", "coordinates": [[[-71.6369139848442, -14.674670102504276], [-71.85956150374594, -14.67203456974097], [-71.8567679621774, -14.455308428872788], [-71.63433731072854, -14.457903379326606], [-71.6369139848442, -14.674670102504276]]]}}, {"id": "2", "type": "Feature", "properties": {"from": "2022-05-01", "to": "2023-04-30", "center_x": -52.37536835924013, "center_y": -6.76511502810888, "area_sqkm": 576.0, "collection_id": "3f605f75-86c4-411a-b4ae-01c896f0e54e", "geolocation": "Par\u00e1, North Region, Brazil"}, "geometry": {"type": "Polygon", "coordinates": [[[-52.26652643579669, -6.656899829295443], [-52.26709208286872, -6.873951685247202], [-52.48426189319361, -6.87332788789026], [-52.483599378926506, -6.656295903069621], [-52.26652643579669, -6.656899829295443]]]}}, {"id": "3", "type": "Feature", "properties": {"from": "2022-05-01", "to": "2023-04-20", "center_x": -0.6761695625664693, "center_y": 44.73360675496526, "area_sqkm": 576.0, "collection_id": "3f605f75-86c4-411a-b4ae-01c896f0e54e", "geolocation": "Nouvelle-Aquitaine, Metropolitan France, France"}, "geometry": {"type": "Polygon", "coordinates": [[[-0.5201358739352488, 44.83848377214294], [-0.5293482528397351, 44.62262921816149], [-0.8316460437322877, 44.62877192563951], [-0.8235585331245763, 44.844672632041046], [-0.5201358739352488, 44.83848377214294]]]}}, {"id": "4", "type": "Feature", "properties": {"from": "2022-05-01", "to": "2023-04-30", "center_x": 13.474661600921767, "center_y": 52.304307492654814, "area_sqkm": 576.0, "collection_id": "3f605f75-86c4-411a-b4ae-01c896f0e54e", "geolocation": "Brandenburg, Germany"}, "geometry": {"type": "Polygon", "coordinates": [[[13.647319424405932, 52.41447863113526], [13.653878879765674, 52.19876680288479], [13.302866493777497, 52.1942395922417], [13.294598412626677, 52.4099162816316], [13.647319424405932, 52.41447863113526]]]}}, {"id": "5", "type": "Feature", "properties": {"from": "2022-05-01", "to": "2023-04-30", "center_x": 31.170712457390746, "center_y": 30.25079042872817, "area_sqkm": 576.0, "collection_id": "3f605f75-86c4-411a-b4ae-01c896f0e54e", "geolocation": "Al Qalyubiya, Egypt"}, "geometry": {"type": "Polygon", "coordinates": [[[31.297252319810408, 30.14430779069598], [31.048183067911715, 30.140839803340192], [31.043898143095458, 30.357295837132238], [31.293513496116468, 30.36079390934212], [31.297252319810408, 30.14430779069598]]]}}, {"id": "6", "type": "Feature", "properties": {"from": "2022-05-01", "to": "2023-04-30", "center_x": 116.15377690444784, "center_y": -31.920991409162493, "area_sqkm": 576.0, "collection_id": "3f605f75-86c4-411a-b4ae-01c896f0e54e", "geolocation": "Western Australia, Australia"}, "geometry": {"type": "Polygon", "coordinates": [[[116.27985599237296, -32.03011160474667], [116.02571488794618, -32.02841366117558], [116.02799461933417, -31.811918741933397], [116.28154120541473, -31.813602525945154], [116.27985599237296, -32.03011160474667]]]}}]} -------------------------------------------------------------------------------- /collections/analysis-ready-planetscope/sandbox-data.md: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /collections/cnes-land-cover-map.yaml: -------------------------------------------------------------------------------- 1 | Name: CNES Land Cover Map 2 | Description: | 3 | The CNES Land Cover Map (Occupation des Sols, OSO) produces land classification for Metropolitan France at 10 m spatial resolution based on Sentinel-2 L2A data within the Theia Land Cover CES framework. 4 | Maps for 2021, 2020, 2019, and 2018 use a 23-categories nomenclature. For earlier maps in 2017 and 2016, a fully compatible 17-classes nomenclature is employed. 5 | 6 | AdditionalInfoExternal: 7 | Title: Additional info 8 | Path: cnes-land-cover-map/README.MD 9 | Image: cnes-land-cover-map/cnes-land-cover-map-france-overview.png 10 | ViewOnEOBrowser: "[EO Browser](https://sentinelshare.page.link/EurE)" 11 | Resolution: 10m 12 | GeographicalCoverage: Metropolitan France with longitude from 6.26°W to 11.85°E and latitude from 51.45°N to 40.46°N 13 | TemporalAvailability: 2016-01-01 - 2021-01-01 14 | UpdateFrequency: Annually 15 | BandInformation: 16 | Table: 17 | Columns: 18 | - Name: Name 19 | Title: Name 20 | - Name: Description 21 | Title: Description 22 | Rows: 23 | - Name: OCS 24 | Description: Main discrete classification according to 23-categories nomenclature. 25 | - Name: OCS_Confidence 26 | Description: The confidence of the classifier. 27 | - Name: OCS_Validity 28 | Description: The number of cloudless images. 29 | Contact: | 30 | - Sentinel Hub Forum on Planet Commmunity 31 | - Theia contacts section 32 | Provider: "[Theia](https://www.theia-land.fr/en/homepage-en/#)" 33 | ManagedBy: "[Sentinel Hub](https://www.sentinel-hub.com/)" 34 | Tags: 35 | - land cover 36 | - machine learning 37 | - derived data 38 | - open data 39 | - raster 40 | - sentinel hub 41 | - systematic 42 | License: | 43 | - Sentinel Hub Terms of Use. 44 | - ETALAB V2.0 open license. Value-added data processed by CNES for the [Theia data center](https://www.theia-land.fr/en/homepage-en/) from Copernicus data. Processing uses algorithms developed by Theia's Centers of Scientific Expertise. 45 | Resources: 46 | - EndPoint: services.sentinel-hub.com 47 | Type: byoc-9baa2732-6597-49d2-ae3b-68ba0a5386b2 48 | CollectionId: 9baa2732-6597-49d2-ae3b-68ba0a5386b2 49 | CustomScripts: 50 | Title: Custom scripts for other collections 51 | URL: https://custom-scripts.sentinel-hub.com/#other_collections 52 | RegistryEntryAdded: "2022-02-08" 53 | RegistryEntryLastModified: "2024-05-10" 54 | -------------------------------------------------------------------------------- /collections/cnes-land-cover-map/cnes-classifier-confidence-france-overview.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/cnes-land-cover-map/cnes-classifier-confidence-france-overview.png -------------------------------------------------------------------------------- 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-------------------------------------------------------------------------------- /collections/copernicus-dem.yaml: -------------------------------------------------------------------------------- 1 | Name: Copernicus DEM 2 | Description: | 3 | [The Copernicus DEM](https://spacedata.copernicus.eu/collections/copernicus-digital-elevation-model) is a Digital Surface Model (DSM) 4 | which represents the bare-Earth surface and all above ground natural and built features. 5 | It is based on [WorldDEM™ ](https://www.intelligence-airbusds.com/imagery/reference-layers/worlddem/) DSM that is derived from [TanDEM-X](https://tandemx-science.dlr.de/) 6 | and is infilled on a local basis with the following DEMs: ASTER, SRTM90, SRTM30, SRTM30plus, GMTED2010, TerraSAR-X Radargrammetric DEM, ALOS World 3D-30m. 7 | Copernicus Programme provides Copernicus DEM in 3 different instances: COP-DEM EEA-10, COP-DEM GLO-30 and COP-DEM GLO-90 where 8 | "COP-DEM GLO-90" tiles and most of the "COP-DEM GLO-30 " tiles are available worldwide with free license. 9 | Sentinel Hub provides two instances named COPERNICUS_90 which uses "COP-DEM GLO-90" and COPERNICUS_30 which uses "COP-DEM GLO-30 Public" 10 | and "COP-DEM GLO-90" in areas where "COP-DEM GLO-30 Public" tiles are not yet released to the public by Copernicus Programme. 11 | Copernicus DEM provides elevation data and can also be used for the orthorectification of satellite imagery (e.g Sentinel 1). 12 | Documentation: "[here](https://docs.sentinel-hub.com/api/latest/data/dem/)" 13 | ViewOnEOBrowser: "[EO Browser](https://sentinelshare.page.link/d3v1)" 14 | Image: copernicus-dem/copernicus-dem.png 15 | Resolution: 30m and 90m 16 | GeographicalCoverage: European and Worldwide coverage ([more info](https://spacedata.copernicus.eu/collections/copernicus-digital-elevation-model)) 17 | TemporalAvailability: static product(two releases 2019 & 2020) for data acquired in (2011-2015) 18 | UpdateFrequency: Updated as soon as new release is available publicly 19 | BandInformation: Information about [bands and data](https://docs.sentinel-hub.com/api/latest/data/dem/#available-bands-and-data) 20 | Contact: Sentinel Hub Forum on Planet Commmunity 21 | Provider: "[Copernicus](https://copernicus.eu/)" 22 | ManagedBy: "[Sentinel Hub](https://www.sentinel-hub.com/)" 23 | Tags: 24 | - core collection 25 | - DEM 26 | - terrain 27 | - 3D 28 | - elevation 29 | - orthorectification 30 | - open data 31 | License: | 32 | - Sentinel Hub Terms of Use. 33 | - Copernicus DEM Attribution and Use. 34 | - Copernicus DEM licensing & citation guidelines section. 35 | Resources: 36 | - EndPoint: services.sentinel-hub.com 37 | Type: dem 38 | DemInstance: COPERNICUS_90, COPERNICUS_30 39 | Notes: Global 40 | CustomScripts: 41 | Title: Collection of DEM custom scripts 42 | URL: https://custom-scripts.sentinel-hub.com/#dem 43 | 44 | 45 | RegistryEntryAdded: "2020-11-30" 46 | RegistryEntryLastModified: "2024-05-10" 47 | 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/collections/corine-land-cover/image_alps.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/corine-land-cover/image_alps.png -------------------------------------------------------------------------------- /collections/corine-land-cover/image_fdoms.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/corine-land-cover/image_fdoms.png -------------------------------------------------------------------------------- /collections/crop-biomass.yaml: -------------------------------------------------------------------------------- 1 | Name: Crop Biomass 2 | Description: | 3 | [Crop Biomass](https://www.planet.com/products/planetary-variables/) provides the ability to track and respond to the highly dynamic nature of biomass in agricultural fields throughout the season. 4 | This enables better-informed decisions, input optimization, interventions, and harvest planning. 5 | This is a relative measure of biomass, so each pixel value has a value of 0 (low biomass) to 1 (high biomass). 6 | The product is provided daily and every day, the user gets a new raster with the data from the most updated direct observation from the day before. 7 | AdditionalInfoExternal: 8 | Title: Open Data for Crop Biomass 9 | Path: crop-biomass/open-data.md 10 | Documentation: "[here](https://docs.sentinel-hub.com/api/latest/data/planetary-variables/crop-biomass/)" 11 | Image: crop-biomass/crop-biomass.png 12 | Resolution: 10m 13 | GeographicalCoverage: Global; Open data in [limited areas](open-data.html); 14 | TemporalAvailability: Global since 2019 (limited after December 2021) 15 | UpdateFrequency: Daily 16 | BandInformation: Information about [bands and data](https://docs.sentinel-hub.com/api/latest/data/planetary-variables/crop-biomass/#available-bands) 17 | Contact: Sentinel Hub Forum on Planet Commmunity 18 | Provider: "[Planet](https://www.planet.com/)" 19 | ManagedBy: "[Planet](https://www.planet.com/)" 20 | Tags: 21 | - open data 22 | - commercial data 23 | - satellite imagery 24 | - planetary variables 25 | - agriculture 26 | - biomass 27 | License: | 28 | [License](https://www.sentinel-hub.com/tou/) 29 | Resources: 30 | - EndPoint: services.sentinel-hub.com 31 | Type: BYOC collection 32 | Notes: Contains the data purchased by individual user. [Explore sample CC-BY-SA open data here](open-data.html). 33 | CustomScripts: 34 | Title: Collection of Crop Biomass custom scripts 35 | URL: https://custom-scripts.sentinel-hub.com/custom-scripts/planetary-variables/crop-biomass/ 36 | 37 | 38 | RegistryEntryAdded: "2024-01-08" 39 | RegistryEntryLastModified: "2024-01-08" 40 | -------------------------------------------------------------------------------- /collections/crop-biomass/crop-biomass.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/crop-biomass/crop-biomass.png -------------------------------------------------------------------------------- /collections/crop-biomass/open-data.md: -------------------------------------------------------------------------------- 1 | # Crop Biomass 2 | 3 | ## Short Description 4 | 5 | [Crop Biomass](https://www.planet.com/products/planetary-variables/) provides the ability to track and respond to the highly dynamic nature of biomass in agricultural fields throughout the season. This enables better-informed decisions, input optimization, interventions, and harvest planning. This is a relative measure of biomass, so each pixel value has a value of 0 (low biomass) to 1 (high biomass). The product is provided daily and every day, the user gets a new raster with the data from the most updated direct observation from the day before.

    6 | 7 | A collection of Crop Biomass for a limited area and time of interest is available with the CC-BY-SA license. 8 | 9 | ## Collections 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 |
    Source IDCollection IDTime Range
    BIOMASS-PROXY_V3.0_10BYOC-fc844940-ecc7-49ff-b072-9f81b36ef1912019-01-01 to 2022-12-31
    27 | 28 | ### Open Data Areas 29 | 30 | To purchase data over your own areas and times of interest, [contact Planet](https://www.planet.com/contact-sales/#contact-sales). 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 | 41 | 42 | 43 | 44 | 45 | 46 | 47 | 48 | 49 | 50 | 51 | 52 | 53 | 54 | 55 | 56 | 57 |
    NameGeoJSON
    Nebraska, United States{"type":"Polygon","coordinates":[[[-96.67125913632235,40.95162566686232],[-96.67503530118803,40.84371453657603],[-96.67881146605373,40.73562741668371],[-96.39488641416239,40.729564890366404],[-96.39064956312542,40.83762892304856],[-96.38641271208847,40.94551707893859],[-96.67125913632235,40.95162566686232]]]}
    Madhya Pradesh, India{"type":"Polygon","coordinates":[[[77.32646679000004,22.404910741000037],[77.43339085700006,22.403117055000052],[77.43657419300007,22.592880011000034],[77.32965012600005,22.594673697000076],[77.32646679000004,22.404910741000037]]]}
    Hanover, Germany{"type":"Polygon","coordinates":[[[9.872932,52.252607],[9.872932,52.440107],[10.034981,52.440107],[10.034981,52.252607],[9.872932,52.252607]]]}
    Río Negro Department, Uruguay{"type":"Polygon","coordinates":[[[-57.85901538999997,-32.71934139299998],[-57.741644151999935,-32.720309191999945],[-57.74008043499998,-32.53066719499998],[-57.85745167399995,-32.529699395999955],[-57.85901538999997,-32.71934139299998]]]}
    58 | -------------------------------------------------------------------------------- /collections/forest-carbon-diligence.yaml: -------------------------------------------------------------------------------- 1 | Name: Forest Carbon Diligence 2 | Description: | 3 | The Forest Carbon Diligence product consists of a bundle of data resources: canopy height, canopy cover, and aboveground live carbon with a spatial resolution of 30 m. 4 | These data are collected annually over the entire land mass of the Earth (between 75° N and 60° S). 5 | Documentation: | 6 | Sentinel Hub Documentation for Forest Carbon Diligence
    7 | Product Website for Forest Carbon Diligence 8 | SandboxData: | 9 | Discover samples of Forest Carbon Diligence, free to all active Planet users and Sentinel Hub users with a paid subscription or a Trial account. Sandbox Data for Forest Carbon Diligence 10 | Image: forest-carbon-diligence/forest-carbon-diligence.png 11 | Resolution: 30m 12 | GeographicalCoverage: Global 13 | TemporalAvailability: 2013 - ongoing 14 | UpdateFrequency: Annual 15 | BandInformation: Information about bands and data 16 | Contact: Sentinel Hub Forum on Planet Commmunity 17 | Provider: Planet 18 | ManagedBy: "[Planet](https://www.planet.com/)" 19 | Tags: 20 | - vegetation monitoring 21 | - carbon 22 | - forest 23 | - MRV 24 | - VCM 25 | - change detection 26 | - mapping 27 | - sandbox data 28 | License: License 29 | Resources: 30 | - EndPoint: services.sentinel-hub.com 31 | Type: BYOC collection 32 | Notes: Contains the data purchased by individual user. [Explore sample CC-BY-NC sandbox data here](https://docs.planet.com/data/planetary-variables/forest-carbon-diligence/sandbox/) 33 | CustomScripts: 34 | Title: Collection of Forest Carbon Diligence custom scripts 35 | URL: https://custom-scripts.sentinel-hub.com/custom-scripts/planetary-variables/forest-carbon-diligence/ 36 | 37 | 38 | RegistryEntryAdded: "2024-03-15" 39 | RegistryEntryLastModified: "2025-02-11" 40 | -------------------------------------------------------------------------------- /collections/forest-carbon-diligence/FCD_BRA.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/forest-carbon-diligence/FCD_BRA.png -------------------------------------------------------------------------------- /collections/forest-carbon-diligence/FCD_FRA.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/forest-carbon-diligence/FCD_FRA.png -------------------------------------------------------------------------------- /collections/forest-carbon-diligence/FCD_USA.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/forest-carbon-diligence/FCD_USA.png -------------------------------------------------------------------------------- /collections/forest-carbon-diligence/forest-carbon-diligence.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/forest-carbon-diligence/forest-carbon-diligence.png -------------------------------------------------------------------------------- /collections/forest-carbon-diligence/sandbox-data.md: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /collections/forest-carbon-monitoring.yaml: -------------------------------------------------------------------------------- 1 | Name: Forest Carbon Monitoring 2 | Description: | 3 | The Forest Carbon Monitoring product consists of a bundle of data resources: canopy height, canopy cover, and aboveground live carbon with a spatial resolution of 3 m. These data are collected quarterly over the entire land mass of the Earth (between 75° N and 60° S). 4 | Documentation: | 5 | Product Website for Forest Carbon Monitoring 6 | SandboxData: | 7 | Discover samples of Forest Carbon Monitoring, free to all active Planet users and Sentinel Hub users with a paid subscription or a Trial account. Sandbox Data for Forest Carbon Monitoring 8 | Image: forest-carbon-monitoring/forest-carbon-monitoring.png 9 | Resolution: 3m 10 | GeographicalCoverage: Land surface area (between 75° N and 60° S) 11 | TemporalAvailability: Q1 2021 - Q3 2024 12 | UpdateFrequency: Quarterly 13 | BandInformation: 14 | Contact: Sentinel Hub Forum on Planet Commmunity 15 | Provider: Planet 16 | ManagedBy: "[Planet](https://www.planet.com/)" 17 | Tags: 18 | - Carbon 19 | - Forest 20 | - MRV 21 | - VCM 22 | - Change 23 | - Monitoring 24 | - sandbox data 25 | License: License 26 | Resources: 27 | - EndPoint: services.sentinel-hub.com 28 | Type: BYOC collection 29 | Notes: Contains the data purchased by individual user. [Explore sample CC-BY-NC sandbox data here](https://docs.planet.com/data/planetary-variables/forest-carbon-monitoring/sandbox/) 30 | CustomScripts: 31 | Title: Collection of Forest Carbon Monitoring custom scripts 32 | URL: https://custom-scripts.sentinel-hub.com/custom-scripts/planetary-variables/forest-carbon-monitoring/ 33 | 34 | 35 | RegistryEntryAdded: "2025-01-22" 36 | RegistryEntryLastModified: "2025-02-25" 37 | -------------------------------------------------------------------------------- /collections/forest-carbon-monitoring/FCM_LAOS.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/forest-carbon-monitoring/FCM_LAOS.jpg -------------------------------------------------------------------------------- /collections/forest-carbon-monitoring/FCM_MADAGASCAR.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/forest-carbon-monitoring/FCM_MADAGASCAR.jpg -------------------------------------------------------------------------------- /collections/forest-carbon-monitoring/FCM_USA.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/forest-carbon-monitoring/FCM_USA.jpg -------------------------------------------------------------------------------- /collections/forest-carbon-monitoring/forest-carbon-monitoring.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/forest-carbon-monitoring/forest-carbon-monitoring.png -------------------------------------------------------------------------------- /collections/forest-carbon-monitoring/sandbox-data.md: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /collections/global-human-settlement-layer-ghs-built-s2/README.MD: -------------------------------------------------------------------------------- 1 | # Global Human Settlement Layer - GHS_BUILT_S2 2 | 3 | ## Short description 4 | 5 | The Global Human Settlement (GHS) framework produces global maps of built-up, population density and settlements to monitor human presence on Earth over time. The data are managed by the Joint Research Centre (JRC) and the DG for Regional and Urban Policy (DG REGIO) of the European Commission, together with the international partnership GEO Human Planet Initiative of the GEO Human Planet Initiative. 6 | The Global Human Settlement Layer *GHS-BUILT-S2* is a global map of built-up areas (expressed as probabilities from 0 to 100 %) at 10 m spatial resolution. It was derived from a Sentinel-2 global image composite for the reference year 2018 using Convolutional Neural Networks. 7 |
    8 | Note: the currently available data is in an advanced but preliminary state. Possible gaps and inconsistencies will be fixed in a final quality control process. 9 | 10 | ## Band information 11 | 12 | Built-up probability values rescaled in the range 0-100 (0 for probability = 0 and 100 for probability = 1); 255 = nodata 13 | 14 | ## More information 15 | 16 | - [Official website](https://ghsl.jrc.ec.europa.eu/index.php) 17 | - [Data source](https://ghsl.jrc.ec.europa.eu/download.php?ds=buS2) 18 | - [Scientific publication on the dataset generation](https://link.springer.com/article/10.1007/s00521-020-05449-7) 19 | - [Global Human Settlement Layer - Understanding Human Presence on Planet Earth (booklet)](https://ghsl.jrc.ec.europa.eu/documents/GHSL_Brochure.pdf?t=1639151473) 20 | 21 | Global Human Settlement Layer built-up probabilities over Paris 22 |
    23 | 24 | *Global Human Settlement Layer built-up probabilities over Paris (France) visualised in EO Browser* 25 |
    26 | 27 | Global Human Settlement Layer built-up probabilities over Germany, Netherlands and Belgium 28 |
    29 | 30 | *Global Human Settlement Layer built-up probabilities over parts of Germany, Netherlands and Belgium visualised in EO Browser* 31 | -------------------------------------------------------------------------------- /collections/global-human-settlement-layer-ghs-built-s2/ghsl_overview.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/global-human-settlement-layer-ghs-built-s2/ghsl_overview.png -------------------------------------------------------------------------------- /collections/global-human-settlement-layer-ghs-built-s2/ghsl_paris.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/global-human-settlement-layer-ghs-built-s2/ghsl_paris.png 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Constellation of surface reflectance (SR) data from the Operational Land Imager (OLI) and Multi-Spectral Instrument (MSI) aboard the Landsat 8-9 and Sentinel-2 remote sensing satellites, respectively. The combined measurement enables global observations of the land every 2–3 days. 4 | Input products are Landsat 8-9 Collection 2 Level 1 top-of-atmosphere reflectance and Sentinel-2 L1C top-of-atmosphere reflectance, which NASA radiometrically harmonizes to the maximum extent, resamples to common 30-meter resolution, and grids using the Sentinel-2 Military Grid Reference System (MGRS) UTM grid. Because of this, the products are different from Landsat 8-9 Collection 2 Level 2 surface reflectance and Sentinel-2 L2A surface reflectance. 5 | Documentation: "[here](https://lpdaac.usgs.gov/data/get-started-data/collection-overview/missions/harmonized-landsat-sentinel-2-hls-overview/)" 6 | Image: harmonized-landsat-sentinel/harmonized-landsat-sentinel.png 7 | ViewOnEOBrowser: "[EO Browser](https://sentinelshare.page.link/jsn7)" 8 | Resolution: 30 m 9 | GeographicalCoverage: Global land 10 | TemporalAvailability: April 2013 - ongoing. 11 | UpdateFrequency: 2-3 days 12 | BandInformation: Information about [bands and data](https://docs.sentinel-hub.com/api/latest/data/hls/#available-bands-and-data) 13 | Contact: Sentinel Hub Forum on Planet Commmunity 14 | Provider: "[Land Processes Distributed Active Archive Center (LP DAAC)](https://lpdaac.usgs.gov/)" 15 | ManagedBy: "[Sentinel Hub](https://www.sentinel-hub.com/)" 16 | Tags: 17 | - core collection 18 | - satellite imagery 19 | - natural resource 20 | - vegetation monitoring 21 | - LULC mapping 22 | - LULC change 23 | - brightness temperature 24 | - open data 25 | - landsat 26 | - sentinel 27 | License: | 28 | - Sentinel Hub Terms of Use. 29 | - USGS EROS Data Citation. 30 | Resources: 31 | - EndPoint: services-uswest2.sentinel-hub.com 32 | Type: hls 33 | Notes: Landsat data is available from April 2013 and Sentinel-2 data from November 2015. 34 | CustomScripts: 35 | Title: Collection of custom scripts of Harmonized Landsat Sentinel 36 | URL: https://custom-scripts.sentinel-hub.com/#harmonized-landsat-sentinel 37 | RegistryEntryAdded: "2022-11-17" 38 | RegistryEntryLastModified: "2024-05-10" 39 | -------------------------------------------------------------------------------- /collections/harmonized-landsat-sentinel/harmonized-landsat-sentinel.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/harmonized-landsat-sentinel/harmonized-landsat-sentinel.png -------------------------------------------------------------------------------- /collections/hrsi-fsc/README.MD: -------------------------------------------------------------------------------- 1 | # High-Resolution Snow & Ice Monitoring; Fractional Snow Cover 2 | 3 | ## Short description 4 | 5 | The Fractional Snow Cover (FSC) product provides the snow fraction at the Top Of Canopy (FSCTOC) and On Ground (FSCOG). NDSI is also provided as part of this service. 6 | 7 | ## Band information 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | 29 | 30 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 | 41 | 42 | 43 | 44 | 45 | 46 | 47 | 48 | 49 | 50 |
    Band NameSample TypeExpected ValuesDescription
    FSCTOC UINT 80-100%, 205 - cloud or cloud shadow, 255 - no data Top of canopy fractional snow cover (%)
    FSCOG UINT8 0-100%, 205 - cloud or cloud shadow, 255 - no data On-ground fractional snow cover (%)
    QCTOC UINT8 0 - high quality, 1 - medium quality, 2 - low quality, 3 - minimal quality, 205 - cloud or cloud shadow, 255 - no data FSCTOC quality layer
    QCOG UINT8 0 - high quality, 1 - medium quality, 2 - low quality, 3 - minimal quality, 205 - cloud or cloud shadow, 255 - no data FSCOG quality layer
    NDSI UINT8 0-100%, 205 - cloud or cloud shadow, 255 - no data Normalised difference snow index (%)
    51 | 52 | ## More information 53 | 54 | More information about the HR-S&I snow production workflows that highlights the dependencies between the diferent products and how they are derived can be found [here](https://land.copernicus.eu/pan-european/biophysical-parameters/high-resolution-snow-and-ice-monitoring/snow-products). 55 | 56 | ### Representative Images 57 | 58 | FSC On Ground, 23rd April 2020, Innsbruck, AT 59 | 60 | *On-ground fractional snow cover(%) On Ground, 23rd April 2020, Innsbruck, AT.* -------------------------------------------------------------------------------- /collections/hrsi-fsc/figure.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/hrsi-fsc/figure.png -------------------------------------------------------------------------------- /collections/hrsi-fsc/hrsi-fsc.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/hrsi-fsc/hrsi-fsc.png -------------------------------------------------------------------------------- /collections/hrsi-gfsc/README.MD: -------------------------------------------------------------------------------- 1 | # High-Resolution Snow & Ice Monitoring; Fractional Snow Cover 2 | 3 | ## Short description 4 | 5 | The daily cumulative Gap-filled Fractional Snow Cover (GFSC) product is a more complete version of the FSC product; gap-filled both at a spatial and temporal scale. 6 | 7 | ## Band information 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | 29 | 30 | 31 | 32 |
    Band NameSample TypeExpected ValuesDescription
    GF UINT 80-100%, 205 - cloud or cloud shadow, 255 - no data Fractional snow cover (%)
    QC UINT8 0 - high quality, 1 - medium quality, 2 - low quality, 3 - minimal quality, 205 - cloud or cloud shadow, 255 - no data Fractional snow cover quality layer
    33 | 34 | ## More information 35 | 36 | More information about the HR-S&I snow production workflows that highlights the dependencies between the diferent products and how they are derived can be found [here](https://land.copernicus.eu/pan-european/biophysical-parameters/high-resolution-snow-and-ice-monitoring/snow-products). 37 | 38 | ### Representative Images 39 | 40 | GFSC, 23rd April 2020, Innsbruck, AT 41 | 42 | *Daily cumulative Gap-filled Fractional Snow Cover - Fractional snow cover, 23rd April 2020, Innsbruck, AT.* -------------------------------------------------------------------------------- /collections/hrsi-gfsc/figure.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/hrsi-gfsc/figure.png -------------------------------------------------------------------------------- /collections/hrsi-gfsc/hrsi-gfsc.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/hrsi-gfsc/hrsi-gfsc.png -------------------------------------------------------------------------------- /collections/hrsi-psa/README.MD: -------------------------------------------------------------------------------- 1 | # High-Resolution Snow & Ice Monitoring; Persistent Snow Area 2 | 3 | ## Short description 4 | 5 | The Persistent Snow Area (PSA) product is generated annually from FSC products and provides the extent of persistent snow cover for that year (the area where snow is present throughout the hydrological year). 6 | 7 | The Persistent Snow Area (PSA) product is generated annually from FSC products and provides the extent of persistent snow cover for that year (the area where snow is present throughout the hydrological year). The PSA corresponds to pixels with a snow probability greater than 0.95, i.e. where snow was observed in at least 95% of the observations (under clear-sky conditions). For optimisation reasons, the retrieval methodology assumes that the minimal snow cover is reached across Europe between 1 May and 30 September; thus the algorithm performs the aggregation only over this period. 8 | 9 | ## Band information 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | 29 | 30 | 31 | 32 | 33 | 34 |
    Band NameSample TypeExpected ValuesDescription
    PSA UINT 80 - no persistent snow, 1 - persistent snow, 255 - no data Persistent snow area
    QC UINT8 0 - high quality, 1 - medium quality, 2 - low quality, 3 - minimal quality, 255 - no data Persistent snow area quality layer
    35 | 36 | ## More information 37 | 38 | More information about the HR-S&I snow production workflows that highlights the dependencies between the diferent products and how they are derived can be found [here](https://land.copernicus.eu/pan-european/biophysical-parameters/high-resolution-snow-and-ice-monitoring/snow-products). 39 | 40 | ### Representative Images 41 | 42 | PSA over the Mont Blanc Region, FR 43 | 44 | *PSA over the Mont Blanc Region, FR.* -------------------------------------------------------------------------------- /collections/hrsi-psa/figure.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/hrsi-psa/figure.png -------------------------------------------------------------------------------- /collections/hrsi-psa/hrsi-psa.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/hrsi-psa/hrsi-psa.png -------------------------------------------------------------------------------- /collections/hrsi-rlie-s1/extent-nordland-norway.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/hrsi-rlie-s1/extent-nordland-norway.png -------------------------------------------------------------------------------- /collections/hrsi-rlie-s1/qlayer-nordland-norway.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/hrsi-rlie-s1/qlayer-nordland-norway.png -------------------------------------------------------------------------------- /collections/hrsi-rlie-s1/thumbnail.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/hrsi-rlie-s1/thumbnail.png -------------------------------------------------------------------------------- /collections/hrsi-rlie-s1s2/extent-rovaniemi-findland.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/hrsi-rlie-s1s2/extent-rovaniemi-findland.png -------------------------------------------------------------------------------- /collections/hrsi-rlie-s1s2/qlayer-rovaniemi-findland.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/hrsi-rlie-s1s2/qlayer-rovaniemi-findland.png -------------------------------------------------------------------------------- /collections/hrsi-rlie-s1s2/thumbnail.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/hrsi-rlie-s1s2/thumbnail.png -------------------------------------------------------------------------------- /collections/hrsi-rlie-s2/extent-varese-como-lecco-italy.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/hrsi-rlie-s2/extent-varese-como-lecco-italy.png -------------------------------------------------------------------------------- /collections/hrsi-rlie-s2/qlayer-varese-como-lecco-italy.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/hrsi-rlie-s2/qlayer-varese-como-lecco-italy.png -------------------------------------------------------------------------------- /collections/hrsi-rlie-s2/thumbnail.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/hrsi-rlie-s2/thumbnail.png -------------------------------------------------------------------------------- /collections/hrsi-sws/README.MD: -------------------------------------------------------------------------------- 1 | # High-Resolution Snow & Ice Monitoring; SAR Wet Snow in high mountains - Wet Snow classification in high Mountains areas 2 | 3 | ## Short description 4 | 5 | The SAR Wet Snow (SWS) product provides information on the wet snow extent in high-mountain areas. 6 | 7 | ## Band information 8 | 9 | Table 1: Bands available in HR&SI SWS data collection. 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | 29 | 30 | 31 | 32 | 33 | 34 |
    Band NameSample TypeExpected ValuesDescription
    WSM UINT 8Refer to Table 2 Wet Snow classification in high Mountains areas
    QCWSM UINT8 0 - high quality, 1 - medium quality, 2 - low quality, 3 - minimal quality, 250 - masked, 255 - no data WSM quality layer
    35 | 36 | Table 2: Classification classes and colouring scheme for WSM band. 37 | 38 | 39 | 40 | 41 | 42 | 43 | 44 | 45 | 46 | 47 | 48 | 49 | 50 | 51 | 52 | 53 | 54 | 55 | 56 | 57 | 58 | 59 | 60 | 61 | 62 | 63 | 64 | 65 | 66 | 67 | 68 | 69 | 70 | 71 | 72 | 73 | 74 | 75 | 76 | 77 | 78 | 79 | 80 | 81 | 82 | 83 | 84 | 85 | 86 | 87 | 88 |
    ValueColorLabel
    1110 - Wet snow
    2125 - Dry snow or snow free or patchy snow
    3200 - Radar shadow / layover / foreshortening
    4210 - Water
    5220 - Forest
    6230 - Urban area
    7240 - Non-mountain areas
    8255 - No data
    89 | 90 | ## More information 91 | 92 | More information about the HR-S&I snow production workflows that highlights the dependencies between the diferent products and how they are derived can be found [here](https://land.copernicus.eu/pan-european/biophysical-parameters/high-resolution-snow-and-ice-monitoring/snow-products). 93 | 94 | ### Representative Images 95 | 96 | SWS WSM, 1st April 2021, Bormio, IT 97 | 98 | *SAR Wet Snow in high mountains - Wet Snow classification in high Mountains areas, 1st April 2021, Bormio, IT.* -------------------------------------------------------------------------------- /collections/hrsi-sws/figure.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/hrsi-sws/figure.png -------------------------------------------------------------------------------- /collections/hrsi-sws/hrsi-sws.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/hrsi-sws/hrsi-sws.png -------------------------------------------------------------------------------- /collections/hrsi-wds/README.MD: -------------------------------------------------------------------------------- 1 | # High-Resolution Snow & Ice Monitoring; Wet / Dry Snow - Snow state classification 2 | 3 | ## Short description 4 | 5 | The Wet/Dry Snow (WDS) product differentiates the snow state conditions within the snow mask defined by the FSCTOC information. 6 | 7 | ## Band information 8 | 9 | Table 1: Bands available in HR&SI SWS data collection. 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | 29 | 30 | 31 | 32 | 33 | 34 |
    Band NameSample TypeExpected ValuesDescription
    SSC UINT 8Refer to Table 2 Snow State Classification
    QCSSC UINT8 0 - high quality, 1 - medium quality, 2 - low quality, 3 - minimal quality, 250 - masked, 255 - no data SSC quality layer
    35 | 36 | Table 2: Classification classes and colouring scheme for SSC band. 37 | 38 | 39 | 40 | 41 | 42 | 43 | 44 | 45 | 46 | 47 | 48 | 49 | 50 | 51 | 52 | 53 | 54 | 55 | 56 | 57 | 58 | 59 | 60 | 61 | 62 | 63 | 64 | 65 | 66 | 67 | 68 | 69 | 70 | 71 | 72 | 73 | 74 | 75 | 76 | 77 | 78 | 79 | 80 | 81 | 82 | 83 | 84 | 85 | 86 | 87 | 88 | 89 | 90 | 91 | 92 | 93 |
    ValueColorLabel
    1110 - Wet snow
    2115 - Dry snow
    3120 - Snow free or patchy snow
    4200 - Radar shadow / layover / foreshortening
    5205 - Cloud or cloud shadow
    6210 - Water
    7220 - Forest
    8230 - Urban area
    9255 - No data
    94 | 95 | ## More information 96 | 97 | More information about the HR-S&I snow production workflows that highlights the dependencies between the diferent products and how they are derived can be found [here](https://land.copernicus.eu/pan-european/biophysical-parameters/high-resolution-snow-and-ice-monitoring/snow-products). 98 | 99 | ### Representative Images 100 | 101 | WDS SSC, 1st April 2021, Bormio, IT 102 | 103 | *Wet / Dry Snow - Snow state classification, 1st April 2021, Bormio, IT.* -------------------------------------------------------------------------------- /collections/hrsi-wds/figure.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/hrsi-wds/figure.png -------------------------------------------------------------------------------- /collections/hrsi-wds/hrsi-wds.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/hrsi-wds/hrsi-wds.png -------------------------------------------------------------------------------- /collections/impact-observatory-lulc-map.yaml: -------------------------------------------------------------------------------- 1 | Name: 10m Annual Land Use Land Cover (9-class) 2 | Description: | 3 | The [10m Annual Land Use Land Cover (LULC)](https://www.impactobservatory.com/maps-for-good/) map is produced Impact Observatory, Microsoft, and Esri collaboratively. 4 | The data collection is derived from ESA Sentinel-2 imagery at 10m resolution globaly using Impact Ovservatory's state of the art deep learning AI land classification model which is trained by billions of human-labeled image pixels. 5 | There are 9 LULC classes generated by the algorithm, including Built, Crops, Trees, Water, Rangeland, Flooded Vegetation, Snow/Ice, Bare Ground, and Clouds. 6 | 7 | AdditionalInfoExternal: 8 | Title: Additional info 9 | Path: impact-observatory-lulc-map/README.MD 10 | Image: impact-observatory-lulc-map/io-lulc-ganges-delta.png 11 | ViewOnEOBrowser: "[EO Browser](https://sentinelshare.page.link/Yzf7)" 12 | Resolution: 10m 13 | GeographicalCoverage: Global land area 14 | TemporalAvailability: 2017-2023 15 | UpdateFrequency: Annually, each January 16 | BandInformation: 17 | Table: 18 | Columns: 19 | - Name: Name 20 | Title: Name 21 | - Name: Description 22 | Title: Description 23 | Rows: 24 | - Name: lulc 25 | Description: Main discrete classification defined in the product documentation. 26 | Contact: | 27 | - Sentinel Hub Forum on Planet Commmunity 28 | - Impact Observatory contact: hello@impactobservatory.com 29 | Provider: "[Impact Observatory](https://www.impactobservatory.com/)" 30 | ManagedBy: "[Sentinel Hub](https://www.sentinel-hub.com/)" 31 | Tags: 32 | - land cover 33 | - machine learning 34 | - derived data 35 | - open data 36 | - raster 37 | - sentinel hub 38 | License: | 39 | - [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) 40 | - Sentinel Hub Terms of Use 41 | Resources: 42 | - EndPoint: services.sentinel-hub.com 43 | Type: byoc-0ed26381-7344-4281-b180-66f3da521f75 44 | CollectionId: 0ed26381-7344-4281-b180-66f3da521f75 45 | CustomScripts: 46 | Title: Collection of custom scripts for this dataset 47 | URL: https://custom-scripts.sentinel-hub.com/custom-scripts/other_collections/impact-observatory/ 48 | RegistryEntryAdded: "2023-02-24" 49 | RegistryEntryLastModified: "2024-05-27" 50 | -------------------------------------------------------------------------------- /collections/impact-observatory-lulc-map/README.md: -------------------------------------------------------------------------------- 1 | # 10m Annual Land Use Land Cover (9-class) 2 | 3 | ## Short description 4 | The 10m Annual Land Use Land Cover (LULC) map is produced Impact Observatocy, Microsoft, and Esri collaboratively. 5 | The data collection is derived from ESA Sentinel-2 imagery at 10m resolution globaly using Impact Ovservatory's state of the art deep learning AI land classification model which is trained by billions of human-labeled image pixels. 6 | There are 9 LULC classes generated by the algorithm, including Built, Crops, Trees, Water, Rangeland, Flooded Vegetation, Snow/Ice, Bare Ground, and Clouds. 7 | 8 | ## Band information 9 | The 10m Annual Land Use Land Cover product contains 1 band. The values of this band are described below. 10 | 11 | ### 10m Annual Land Use Land Cover classes description 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | 29 | 30 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 | 41 | 42 | 43 | 44 | 45 | 46 | 47 | 48 | 49 | 50 | 51 | 52 | 53 | 54 | 55 | 56 | 57 | 58 | 59 | 60 | 61 | 62 | 63 | 64 | 65 | 66 | 67 | 68 | 69 | 70 | 71 | 72 | 73 | 74 | 75 | 76 | 77 | 78 |
    ValueColorColor CodeLabel
    1 0x419bdf Water
    20x397d49 Trees
    40x7a87c6 Flooded Vegetation
    50xe49635 Crops
    70xc4281b Built Area
    8 0xa59b8f Bare Ground
    90xa8ebff Snow/Ice
    100x616161 Clouds
    110xe3e2c3 Rangeland
    79 | 80 | ## More information 81 | The [product documentation](https://www.impactobservatory.com/maps-for-good/) can be found on [Impact Observatory](https://www.impactobservatory.com/) and are available on [AWS](https://registry.opendata.aws/io-lulc/). 82 | 83 | ### Representative Images 84 | 85 | 10m Annual Land Use Land Cover Europe 86 | 87 | *10m Annual Land Use Land Cover 2021, Europe visualised in EO Browser.* 88 | 89 | 10m Annual Land Use Land Cover Ganges Delta 90 | 91 | *10m Annual Land Use Land Cover 2022, Ganges Delta visualised in EO Browser.* 92 | -------------------------------------------------------------------------------- /collections/impact-observatory-lulc-map/io-lulc-ganges-delta.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/impact-observatory-lulc-map/io-lulc-ganges-delta.png -------------------------------------------------------------------------------- /collections/impact-observatory-lulc-map/io-lulc.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/impact-observatory-lulc-map/io-lulc.png -------------------------------------------------------------------------------- /collections/land-surface-temperature.yaml: -------------------------------------------------------------------------------- 1 | Name: Land Surface Temperature 2 | Description: | 3 | Planet’s Land Surface Temperature (LST) is a feed of high-resolution, globally available measurement of the skin temperature of the Earth. Combining observations from a range of satellite constellations, Land Surface Temperature is not hindered by clouds, ensuring a continuous, consistent and scientifically reliable data record of more than 20 years. Consequently, there is no requirement to uphold extensive networks of physical sensors. 4 | This Planetary Variable measures the temperature twice a day (daytime and nighttime) with a spatial resolution of 100 m and 1000 m, providing vital intelligence about our nexus food/water system, and urban living conditions. 5 | Documentation: | 6 | Sentinel Hub Documentation for Land Surface Temperature
    7 | Product Website for Land Surface Temperature 8 | SandboxData: | 9 | Discover samples of Land Surface Temperature, free to all active Planet users and Sentinel Hub users with a paid subscription or a Trial account. Sandbox Data for Land Surface Temperature 10 | Image: land-surface-temperature/land-surface-temperature.png 11 | Resolution: 100m and 1000m 12 | GeographicalCoverage: Global 13 | TemporalAvailability: 100 m (July, 1st 2017 - Present)1000 m (June, 15th 2002 - October 4th 2011 (AMSRE) July, 25th 2012 - Present (AMSR2)) 14 | UpdateFrequency: Above 50 degrees latitude:2 obs. daily at 01:30 and 13:30. At the equator:at least ±180 obs. at 01:30 and ±180 obs. at 13:30 observations annually. 15 | BandInformation: Information about bands and data 16 | Contact: Sentinel Hub Forum on Planet Commmunity 17 | Provider: Planet 18 | ManagedBy: "[Planet](https://www.planet.com/)" 19 | Tags: 20 | - commercial data 21 | - satellite imagery 22 | - planetary variables 23 | - agriculture 24 | - thermal 25 | - sandbox data 26 | License: License 27 | Resources: 28 | - EndPoint: services.sentinel-hub.com 29 | Type: BYOC collection 30 | Notes: Contains the data purchased by individual user. [Explore sample CC-BY-NC sandbox data here](https://docs.planet.com/data/planetary-variables/land-surface-temperature/sandbox/) 31 | CustomScripts: 32 | Title: Collection of Land Surface Temperature custom scripts 33 | URL: https://custom-scripts.sentinel-hub.com/custom-scripts/planetary-variables/land-surface-temperature/ 34 | 35 | 36 | RegistryEntryAdded: "2024-01-08" 37 | RegistryEntryLastModified: "2024-05-10" 38 | -------------------------------------------------------------------------------- /collections/land-surface-temperature/LST_AUS.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/land-surface-temperature/LST_AUS.png -------------------------------------------------------------------------------- /collections/land-surface-temperature/LST_FRA.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/land-surface-temperature/LST_FRA.png -------------------------------------------------------------------------------- /collections/land-surface-temperature/LST_USA.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/land-surface-temperature/LST_USA.png -------------------------------------------------------------------------------- /collections/land-surface-temperature/land-surface-temperature.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/land-surface-temperature/land-surface-temperature.png -------------------------------------------------------------------------------- /collections/land-surface-temperature/open-data.md: -------------------------------------------------------------------------------- 1 | # Land Surface Temperature 2 | 3 | ## Short Description 4 | [Land Surface Temperature](https://www.planet.com/products/planetary-variables/) provides twice-daily measurements of land surface temperature with high spatial resolution and consistency. LST data eliminates the need for maintaining large networks of physical sensors, reduces the impact of cloud cover on measurements, and enables a more accurate reflection of ground conditions across large areas. 5 | 6 | A collection of Land Surface Tempearture for a limited area and time of interest is available with the CC-BY-SA license. 7 | 8 | ## Collections 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | 29 |
    Source IDCollection IDTime Range
    LST-AMSR2_V1.0_100BYOC-3af0a65b-4e7d-42d1-9890-1408a23361bb2019-01-01 to 2022-12-31
    LST-AMSR2_V1.0_1000BYOC-462d822c-24be-4f3d-a6a8-ddc6356ff1cc2019-01-01 to 2022-12-31
    30 | 31 | ### Open Data Areas 32 | To access data over your own areas and times of interest, [contact Planet](https://www.planet.com/contact-sales/#contact-sales). 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 | 41 | 42 | 43 | 44 | 45 | 46 | 47 | 48 | 49 | 50 | 51 | 52 | 53 | 54 | 55 | 56 | 57 | 58 | 59 |
    NameGeoJSON
    Nebraska, United States{"type":"Polygon","coordinates":[[[-96.67125913632235,40.95162566686232],[-96.67503530118803,40.84371453657603],[-96.67881146605373,40.73562741668371],[-96.39488641416239,40.729564890366404],[-96.39064956312542,40.83762892304856],[-96.38641271208847,40.94551707893859],[-96.67125913632235,40.95162566686232]]]}
    Madhya Pradesh, India{"type":"Polygon","coordinates":[[[77.32646679000004,22.404910741000037],[77.43339085700006,22.403117055000052],[77.43657419300007,22.592880011000034],[77.32965012600005,22.594673697000076],[77.32646679000004,22.404910741000037]]]}
    Hanover, Germany{"type":"Polygon","coordinates":[[[9.872932,52.252607],[9.872932,52.440107],[10.034981,52.440107],[10.034981,52.252607],[9.872932,52.252607]]]}
    Río Negro Department, Uruguay{"type":"Polygon","coordinates":[[[-57.85901538999997,-32.71934139299998],[-57.741644151999935,-32.720309191999945],[-57.74008043499998,-32.53066719499998],[-57.85745167399995,-32.529699395999955],[-57.85901538999997,-32.71934139299998]]]}
    -------------------------------------------------------------------------------- /collections/land-surface-temperature/sandbox-data.md: -------------------------------------------------------------------------------- 1 | 4 | -------------------------------------------------------------------------------- /collections/landsat-1-5-mss-l1.yaml: -------------------------------------------------------------------------------- 1 | Name: Landsat 1-5 MSS L1 2 | Description: | 3 | The Landsat Multispectral Scanner System (MSS) sensors were carried onboard Landsats 1 to 5. It provides 4 spectral bands. 4 | See [USGS EROS Archive](https://www.usgs.gov/centers/eros/science/usgs-eros-archive-landsat-archives-landsat-1-5-multispectral-scanner-collection?qt-science_center_objects=0#qt-science_center_objects) for more information. MSS Level-1 data provides Top of Atmosphere Reflectance products for the period from July 1972 to October 1992 and from June 2012 to January 2013. 5 | Documentation: "[here](https://docs.sentinel-hub.com/api/latest/data/landsat-mss/)" 6 | Image: landsat-1-5-mss-l1/landsat-1-5-mss-l1.png 7 | Resolution: 68 m x 83 m (commonly resampled to 57 m, or 60 m) 8 | GeographicalCoverage: Global land 9 | TemporalAvailability: | 10 | Landsat 1 from July 1972 to January 1978 11 | Landsat 2 from January 1975 to February 1982 12 | Landsat 3 from March 1978 to March 1983 13 | Landsat 4 from July 1982 to December 1993 14 | Landsat 5 from 1984 to October 1992, and from June 2012 to January 2013 15 | UpdateFrequency: Archived data 16 | BandInformation: Information about [bands and data](https://docs.sentinel-hub.com/api/latest/data/landsat-mss/#available-bands-and-data) 17 | Contact: Sentinel Hub Forum on Planet Commmunity 18 | Provider: "[USGS](https://www.usgs.gov//)" 19 | ManagedBy: "[Sentinel Hub](https://www.sentinel-hub.com/)" 20 | Tags: 21 | - core collection 22 | - satellite imagery 23 | - natural resource 24 | - vegetation monitoring 25 | - LULC mapping 26 | - LULC change 27 | - open data 28 | - landsat 29 | License: | 30 | - Sentinel Hub Terms of Use. 31 | - USGS EROS Data Citation. 32 | Resources: 33 | - EndPoint: services-uswest2.sentinel-hub.com 34 | Type: landsat-mss-l1 35 | Notes: Global coverage from July 1972 to October 1992 and from June 2012 to January 2013 36 | CustomScripts: 37 | Title: Collection of Landsat custom scripts 38 | URL: https://custom-scripts.sentinel-hub.com/custom-scripts/landsat/ 39 | 40 | 41 | RegistryEntryAdded: "2021-07-16" 42 | RegistryEntryLastModified: "2024-05-10" 43 | -------------------------------------------------------------------------------- /collections/landsat-1-5-mss-l1/landsat-1-5-mss-l1.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/landsat-1-5-mss-l1/landsat-1-5-mss-l1.png -------------------------------------------------------------------------------- /collections/landsat-4-5-tm-l1.yaml: -------------------------------------------------------------------------------- 1 | Name: Landsat 4-5 TM L1 2 | Description: | 3 | The Landsat Thematic Mapper (TM) sensor was carried onboard Landsats 4 and 5. 4 | TM collected data in 7 spectral bands; from the blue, green, red, near-infrared, mid-infrared (2) and thermal infrared portions of the electromagnetic spectrum. 5 | Visit [USGS EROS Archive - Landsat Archives - Landsat 4-5 Thematic Mapper Collection 2 Level-1 Data](https://www.usgs.gov/centers/eros/science/usgs-eros-archive-landsat-archives-landsat-4-5-thematic-mapper-collection-2?qt-science_center_objects=0#qt-science_center_objects) webpage 6 | for more information. 7 | Documentation: "[here](https://docs.sentinel-hub.com/api/latest/data/landsat-tm/#available-bands-and-data)" 8 | Image: landsat-4-5-tm-l1/landsat-4-5-tm-l1.png 9 | ViewOnEOBrowser: "[EO Browser](https://sentinelshare.page.link/sPt3)" 10 | Resolution: 30 m (the thermal band is re-sampled from 120 m) 11 | GeographicalCoverage: Global Land 12 | TemporalAvailability: | 13 | Landsat 4 from July 1982 to December 1993 14 | Landsat 5 from March 1984 to May 2012 15 | UpdateFrequency: Archived data 16 | BandInformation: Information about [bands and data](https://docs.sentinel-hub.com/api/latest/data/landsat-8-l2/#available-bands-and-data) 17 | Contact: Sentinel Hub Forum on Planet Commmunity 18 | Provider: "[USGS](https://www.usgs.gov//)" 19 | ManagedBy: "[Sentinel Hub](https://www.sentinel-hub.com/)" 20 | Tags: 21 | - core collection 22 | - satellite imagery 23 | - natural resource 24 | - vegetation monitoring 25 | - LULC mapping 26 | - LULC change 27 | - surface temperature 28 | - open data 29 | - landsat 30 | License: | 31 | - Sentinel Hub Terms of Use. 32 | - USGS EROS Data Citation. 33 | Resources: 34 | - EndPoint: services-uswest2.sentinel-hub.com 35 | Type: landsat-tm-l1 36 | Notes: Global coverage from July 1982 to May 2012 37 | CustomScripts: 38 | Title: Collection of Landsat custom scripts 39 | URL: https://custom-scripts.sentinel-hub.com/custom-scripts/landsat/ 40 | 41 | RegistryEntryAdded: "2021-05-12" 42 | RegistryEntryLastModified: "2024-05-10" 43 | -------------------------------------------------------------------------------- /collections/landsat-4-5-tm-l1/landsat-4-5-tm-l1.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/landsat-4-5-tm-l1/landsat-4-5-tm-l1.png -------------------------------------------------------------------------------- /collections/landsat-4-5-tm-l2.yaml: -------------------------------------------------------------------------------- 1 | Name: Landsat 4-5 TM L2 2 | Description: | 3 | The Landsat Thematic Mapper (TM) sensor was carried onboard Landsats 4 and 5. 4 | TM collected data in 7 spectral bands; from the blue, green, red, near-infrared, mid-infrared(2) and thermal infrared portions of the electromagnetic spectrum. 5 | L2 data include Surface Reflectance and Surface Temperature scene-based products. 6 | Visit [USGS EROS Archive - Landsat Archives - Landsat 4-5 TM Collection 2 Level-2 Science Products](https://www.usgs.gov/centers/eros/science/usgs-eros-archive-landsat-archives-landsat-4-5-tm-collection-2-level-2-science?qt-science_center_objects=0#qt-science_center_objects) 7 | for more information. 8 | Documentation: "[here](https://docs.sentinel-hub.com/api/latest/data/landsat-tm-l2/)" 9 | Image: landsat-4-5-tm-l2/landsat-4-5-tm-l2.png 10 | ViewOnEOBrowser: "[EO Browser](https://sentinelshare.page.link/rDSK)" 11 | Resolution: 30 m (the thermal band is re-sampled from 120 m) 12 | GeographicalCoverage: Global Land 13 | TemporalAvailability: | 14 | Landsat 4 from July 1982 to December 1993 15 | Landsat 5 from March 1984 to May 2012 16 | UpdateFrequency: Archived data 17 | BandInformation: Information about [bands and data](https://docs.sentinel-hub.com/api/latest/data/landsat-tm-l2/#available-bands-and-data) 18 | Contact: Sentinel Hub Forum on Planet Commmunity 19 | Provider: "[USGS](https://www.usgs.gov//)" 20 | ManagedBy: "[Sentinel Hub](https://www.sentinel-hub.com/)" 21 | Tags: 22 | - core collection 23 | - satellite imagery 24 | - natural resource 25 | - vegetation monitoring 26 | - LULC mapping 27 | - LULC change 28 | - surface temperature 29 | - open data 30 | - landsat 31 | License: | 32 | - Sentinel Hub Terms of Use. 33 | - USGS EROS Data Citation. 34 | Resources: 35 | - EndPoint: services-uswest2.sentinel-hub.com 36 | Type: landsat-tm-l2 37 | Notes: Global coverage from July 1982 to May 2012 38 | CustomScripts: 39 | Title: Collection of Landsat custom scripts 40 | URL: https://custom-scripts.sentinel-hub.com/custom-scripts/landsat/ 41 | 42 | RegistryEntryAdded: "2021-05-12" 43 | RegistryEntryLastModified: "2024-058-10" 44 | -------------------------------------------------------------------------------- /collections/landsat-4-5-tm-l2/landsat-4-5-tm-l2.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/landsat-4-5-tm-l2/landsat-4-5-tm-l2.png -------------------------------------------------------------------------------- /collections/landsat-7-etm+-l1.yaml: -------------------------------------------------------------------------------- 1 | Name: Landsat 7 ETM+ L1 2 | Description: | 3 | The Landsat 7 Enhanced Thematic Mapper (ETM+) sensor is carried onboard Landsat 7. ETM+ provides 7 spectral bands and 1 thermal band. 4 | See [USGS EROS Archive](https://www.usgs.gov/centers/eros/science/usgs-eros-archive-landsat-archives-landsat-7-enhanced-thematic-mapper-plus?qt-science_center_objects=0#qt-science_center_objects) for more information. Landsat 7 Level-1 data provides Top of Atmosphere Reflectance and Top of the Atmosphere Brightness Temperature products. Level 1 data are available since April 1999. All scenes collected since May 30, 2003 have data gaps due to the Scan Line Corrector (SLC) failure. 5 | Documentation: "[here](https://docs.sentinel-hub.com/api/latest/data/landsat-etm/)" 6 | Image: landsat-7-etm+-l1/landsat-7-etm+-l1.png 7 | Resolution: 30 m (15 m for the panchromatic band, thermal band is re-sampled from 60 m) 8 | GeographicalCoverage: Global land 9 | TemporalAvailability: April 1999 - ongoing 10 | UpdateFrequency: Landsat data are added regularly,as soon as they are available in USGS AWS cloud 11 | BandInformation: Information about [bands and data](https://docs.sentinel-hub.com/api/latest/data/landsat-etm/#available-bands-and-data) 12 | Contact: Sentinel Hub Forum on Planet Commmunity 13 | Provider: "[USGS](https://www.usgs.gov//)" 14 | ManagedBy: "[Sentinel Hub](https://www.sentinel-hub.com/)" 15 | Tags: 16 | - core collection 17 | - satellite imagery 18 | - natural resource 19 | - vegetation monitoring 20 | - LULC mapping 21 | - LULC change 22 | - brightness temperature 23 | - open data 24 | - landsat 25 | License: | 26 | - Sentinel Hub Terms of Use. 27 | - USGS EROS Data Citation. 28 | Resources: 29 | - EndPoint: services-uswest2.sentinel-hub.com 30 | Type: landsat-etm-l1 31 | Notes: Global coverage since April 1999. All scenes collected since May 30, 2003 have data gaps due to the Scan Line Corrector (SLC) failure. 32 | CustomScripts: 33 | Title: Collection of Landsat custom scripts 34 | URL: https://custom-scripts.sentinel-hub.com/custom-scripts/landsat/ 35 | RegistryEntryAdded: "2021-07-16" 36 | RegistryEntryLastModified: "2024-05-10" 37 | -------------------------------------------------------------------------------- /collections/landsat-7-etm+-l1/landsat-7-etm+-l1.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/landsat-7-etm+-l1/landsat-7-etm+-l1.png -------------------------------------------------------------------------------- /collections/landsat-7-etm+-l2.yaml: -------------------------------------------------------------------------------- 1 | Name: Landsat 7 ETM+ L2 2 | Description: | 3 | The Landsat 7 Enhanced Thematic Mapper (ETM+) sensor is carried onboard Landsat 7. ETM+ provides 7 spectral bands and 1 thermal band. 4 | See [USGS EROS Archive](https://www.usgs.gov/centers/eros/science/usgs-eros-archive-landsat-archives-landsat-7-etm-plus-collection-2-level-2?qt-science_center_objects=0#qt-science_center_objects) for more information. Landsat 7 level-2 data provides atmospherically corrected Surface Reflectance and Surface Brightness Temperature products. Level-2 data are available since April 1999. 5 | Documentation: "[here](https://docs.sentinel-hub.com/api/latest/data/landsat-etm-l2/)" 6 | Image: landsat-7-etm+-l2/landsat-7-etm+-l2.png 7 | Resolution: 30 m (thermal band is re-sampled from 60 m) 8 | GeographicalCoverage: Global land 9 | TemporalAvailability: April 1999 - ongoing 10 | UpdateFrequency: Landsat data are added regularly,as soon as they are available in USGS AWS cloud 11 | BandInformation: Information about [bands and data](https://docs.sentinel-hub.com/api/latest/data/landsat-etm-l2/#available-bands-and-data) 12 | Contact: Sentinel Hub Forum on Planet Commmunity 13 | Provider: "[USGS](https://www.usgs.gov//)" 14 | ManagedBy: "[Sentinel Hub](https://www.sentinel-hub.com/)" 15 | Tags: 16 | - core collection 17 | - satellite imagery 18 | - natural resource 19 | - vegetation monitoring 20 | - LULC mapping 21 | - LULC change 22 | - surface temperature 23 | - open data 24 | - landsat 25 | License: | 26 | - Sentinel Hub Terms of Use. 27 | - USGS EROS Data Citation. 28 | Resources: 29 | - EndPoint: services-uswest2.sentinel-hub.com 30 | Type: landsat-etm-l2 31 | Notes: Global coverage since April 1999. 32 | CustomScripts: 33 | Title: Collection of Landsat custom scripts 34 | URL: https://custom-scripts.sentinel-hub.com/custom-scripts/landsat/ 35 | RegistryEntryAdded: "2021-07-16" 36 | RegistryEntryLastModified: "2024-05-10" 37 | -------------------------------------------------------------------------------- /collections/landsat-7-etm+-l2/landsat-7-etm+-l2.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/landsat-7-etm+-l2/landsat-7-etm+-l2.png -------------------------------------------------------------------------------- /collections/landsat-8-l1.yaml: -------------------------------------------------------------------------------- 1 | Name: Landsat 8-9 L1 2 | Description: | 3 | [Landsat 8-9 Level 1](https://www.usgs.gov/centers/eros/science/usgs-eros-archive-landsat-archives-landsat-8-9-operational-land-imager-and) collection includes both 4 | [Landsat 8](https://www.usgs.gov/landsat-missions/landsat-8?qt-science_support_page_related_con=0#qt-science_support_page_related_con) and the most recently launched 5 | [Landsat 9](https://www.usgs.gov/landsat-missions/landsat-9) satellites (provided by NASA/USGS), both carrying the Operational Land Imager (OLI) and 6 | the Thermal Infrared Sensor (TIRS) instruments, with 9 optical and 2 thermal bands. These two sensors provide seasonal coverage of the global landmass. 7 | [Landsat 8-9 Level 1 data](https://www.usgs.gov/core-science-systems/nli/landsat/landsat-collection-2-level-1-data?qt-science_support_page_related_con=1#qt-science_support_page_related_con) 8 | from the most recently released [collection 2](https://www.usgs.gov/faqs/what-updates-are-being-made-landsat-collection-2?qt-news_science_products=0#qt-news_science_products), 9 | provides Top of Atmosphere Reflectance and Top of the Atmosphere Brightness Temperature products. Level 1 data are available since February 2013 for Landsat 8 and since January 2022 for Landsat 9. 10 | Documentation: "[here](https://docs.sentinel-hub.com/api/latest/data/landsat-8/)" 11 | Image: landsat-8-l1/landsat-8-l1.png 12 | ViewOnEOBrowser: "[EO Browser](https://sentinelshare.page.link/abtC)" 13 | Resolution: 30m 14 | GeographicalCoverage: Land ([more info](https://landsat.gsfc.nasa.gov/landsat-8/mission-details)) 15 | TemporalAvailability: February 2013 - ongoing 16 | UpdateFrequency: Landsat data are added regularly,as soon as they are available in USGS AWS cloud 17 | BandInformation: Information about [bands and data](https://docs.sentinel-hub.com/api/latest/data/landsat-8/#available-bands-and-data) 18 | Contact: Sentinel Hub Forum on Planet Commmunity 19 | Provider: "[USGS](https://www.usgs.gov//)" 20 | ManagedBy: "[Sentinel Hub](https://www.sentinel-hub.com/)" 21 | Tags: 22 | - core collection 23 | - satellite imagery 24 | - natural resource 25 | - vegetation monitoring 26 | - LULC mapping 27 | - LULC change 28 | - surface temperature 29 | - open data 30 | - landsat 31 | License: | 32 | - Sentinel Hub Terms of Use. 33 | - USGS EROS Data Citation. 34 | Resources: 35 | - EndPoint: services-uswest2.sentinel-hub.com 36 | Type: landsat-ot-l1 37 | Notes: Global since Feb 2013 38 | CustomScripts: 39 | Title: Collection of Landsat custom scripts 40 | URL: https://custom-scripts.sentinel-hub.com/custom-scripts/landsat/ 41 | 42 | 43 | RegistryEntryAdded: "2018-04-17" 44 | RegistryEntryLastModified: "2024-05-10" 45 | -------------------------------------------------------------------------------- /collections/landsat-8-l1/landsat-8-l1.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/landsat-8-l1/landsat-8-l1.png -------------------------------------------------------------------------------- /collections/landsat-8-l2.yaml: -------------------------------------------------------------------------------- 1 | Name: Landsat 8-9 L2 2 | Description: | 3 | [Landsat 8-9 Level 2](https://www.usgs.gov/centers/eros/science/usgs-eros-archive-landsat-archives-landsat-8-9-operational-land-imager-and) collection includes both 4 | [Landsat 8](https://www.usgs.gov/landsat-missions/landsat-8?qt-science_support_page_related_con=0#qt-science_support_page_related_con) and the most recently launched 5 | [Landsat 9](https://www.usgs.gov/landsat-missions/landsat-9) satellites (provided by NASA/USGS), both carrying the Operational Land Imager (OLI) and 6 | the Thermal Infrared Sensor (TIRS) instruments, with 9 optical and 2 thermal bands. These two sensors provide seasonal coverage of the global landmass. 7 | [Landsat 8-9 Level 2 data](https://www.usgs.gov/core-science-systems/nli/landsat/landsat-collection-2-level-2-science-products) 8 | from the most recently released [collection 2](https://www.usgs.gov/faqs/what-updates-are-being-made-landsat-collection-2?qt-news_science_products=0#qt-news_science_products), 9 | provides atmospherically corrected Surface Reflectance and Surface Brightness Temperature products generated from Collection 2 Level-1 scenes that have been processed to Tier 1 or Tier 2. 10 | Collection 2 level 2 data are available since February 2013 for Landsat 8 and since January 2022 for Landsat 9 and new data are continously added usually within 24 hours after Level 1 scenes are available. 11 | Documentation: "[here](https://docs.sentinel-hub.com/api/latest/data/landsat-8-l2/)" 12 | Image: landsat-8-l2/landsat-8-l2.png 13 | ViewOnEOBrowser: "[EO Browser](https://sentinelshare.page.link/tWrZ)" 14 | Resolution: 30m 15 | GeographicalCoverage: Land ([more info](https://landsat.gsfc.nasa.gov/landsat-8/mission-details)) 16 | TemporalAvailability: February 2013 - ongoing 17 | UpdateFrequency: Landsat data are added regularly,as soon as they are available in USGS AWS cloud 18 | BandInformation: Information about [bands and data](https://docs.sentinel-hub.com/api/latest/data/landsat-8-l2/#available-bands-and-data) 19 | Contact: Sentinel Hub Forum on Planet Commmunity 20 | Provider: "[USGS](https://www.usgs.gov//)" 21 | ManagedBy: "[Sentinel Hub](https://www.sentinel-hub.com/)" 22 | Tags: 23 | - core collection 24 | - satellite imagery 25 | - natural resource 26 | - vegetation monitoring 27 | - LULC mapping 28 | - LULC change 29 | - surface temperature 30 | - open data 31 | - landsat 32 | License: | 33 | - Sentinel Hub Terms of Use. 34 | - USGS EROS Data Citation. 35 | Resources: 36 | - EndPoint: services-uswest2.sentinel-hub.com 37 | Type: landsat-ot-l2 38 | Notes: Global since Feb 2013 39 | CustomScripts: 40 | Title: Collection of Landsat custom scripts 41 | URL: https://custom-scripts.sentinel-hub.com/custom-scripts/landsat/ 42 | 43 | RegistryEntryAdded: "2018-04-17" 44 | RegistryEntryLastModified: "2024-05-10" 45 | -------------------------------------------------------------------------------- /collections/landsat-8-l2/landsat-8-l2.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/landsat-8-l2/landsat-8-l2.png -------------------------------------------------------------------------------- /collections/mapzen-dem.yaml: -------------------------------------------------------------------------------- 1 | Name: Mapzen DEM 2 | Description: | 3 | Mapzen DEM is based on [Mapzen's terrain tiles](https://github.com/tilezen/joerd/tree/master/docs) that provide global DEM and bathymetry data. 4 | Mapzen terrain tiles is a composite of elevation data of varying resolutions from [multiple open data sources](https://github.com/tilezen/joerd/blob/master/docs/data-sources.md) 5 | including [SRTM](https://www.usgs.gov/centers/eros/science/usgs-eros-archive-digital-elevation-shuttle-radar-topography-mission-srtm-1-arc?qt-science_center_objects=0#qt-science_center_objects), 6 | [ETOPO1](https://www.ngdc.noaa.gov/mgg/global/global.html), 7 | and other higher resolution sources for some parts of the world. 8 | Mapzen DEM provides bare-earth terrain heights and can also be used for the orthorectification of satellite imagery (e.g Sentinel 1). 9 | Documentation: "[here](https://docs.sentinel-hub.com/api/latest/data/dem/)" 10 | Image: mapzen-dem/mapzen-dem.png 11 | ViewOnEOBrowser: "[EO Browser](https://sentinelshare.page.link/wDL1)" 12 | Resolution: "varies per zoom level, location and data source [more info](https://github.com/tilezen/joerd/blob/master/docs/data-sources.md#what-is-the-ground-resolution)" 13 | GeographicalCoverage: Ocean and Land ([more info](https://github.com/tilezen/joerd/blob/master/docs/data-sources.md#what-is-sourced-at-what-zooms)) 14 | TemporalAvailability: static [current version was built in 2017](https://github.com/tilezen/joerd/blob/master/docs/data-sources.md#data-updates) 15 | UpdateFrequency: "[depends on updates by Mapzen](https://github.com/tilezen/joerd/blob/master/docs/data-sources.md#data-updates)" 16 | BandInformation: Information about [bands and data](https://docs.sentinel-hub.com/api/latest/data/dem/#available-bands-and-data) 17 | Contact: Sentinel Hub Forum on Planet Commmunity 18 | Provider: "[Mapzen](https://www.mapzen.com/)" 19 | ManagedBy: "[Sentinel Hub](https://www.sentinel-hub.com/)" 20 | Tags: 21 | - core collection 22 | - DEM 23 | - terrain 24 | - 3D 25 | - elevation 26 | - orthorectification 27 | - open data 28 | License: | 29 | - Sentinel Hub Terms of Use. 30 | - Mapzen Terms of Service. 31 | Resources: 32 | - EndPoint: services-uswest2.sentinel-hub.com 33 | Type: dem 34 | DemInstance: MAPZEN 35 | Notes: Global 36 | - EndPoint: services.sentinel-hub.com 37 | Type: dem 38 | DemInstance: MAPZEN 39 | Notes: Global coverage up to resolution level 13 (level 14 is missing). 40 | CustomScripts: 41 | Title: Collection of DEM custom scripts 42 | URL: https://custom-scripts.sentinel-hub.com/#dem 43 | 44 | RegistryEntryAdded: "2018-04-17" 45 | RegistryEntryLastModified: "2024-05-10" 46 | -------------------------------------------------------------------------------- /collections/mapzen-dem/mapzen-dem.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/mapzen-dem/mapzen-dem.png -------------------------------------------------------------------------------- /collections/modis.yaml: -------------------------------------------------------------------------------- 1 | Name: MODIS MCD43A4.006 2 | Description: | 3 | [MODIS](https://modis.gsfc.nasa.gov/about/) (Moderate Resolution Imaging Spectroradiometer) is the main 4 | instrument operating on both NASA's [Terra](https://terra.nasa.gov/) and [Aqua](https://aqua.nasa.gov/) satellites. 5 | It acquires images of the earth in 36 bands within the visible and the infrared regions of the spectrum at low to medium spatial resolutions. 6 | MODIS is designed to provide atleast daily observations of land, oceans and lower atmosphere that contribute to 7 | local or global scale land or water applications. There are several products derived from MODIS which include land, atmosphere, cryospehere and ocean products. 8 | MCD43A4 Nadir BRDF-Adjusted Reflectance (NBAR) product Version 6 is a MODIS land product available in Sentinel Hub. 9 | It is computed daily for each of MODIS bands 1 - 7 and it contains the most representative pixels from 16 day period temporarily weighted to the ninth day. 10 | MCD43A4.006 is available since February 2000 on a daily basis but with a 8 days delay. Sentinel Hub no longer has the latest MODIS data because the underlying data provider has ceased operations. Data from February 24, 2000 to February 10, 2023 remains accessible. 11 | Documentation: "[here](https://docs.sentinel-hub.com/api/latest/data/modis/mcd/)" 12 | Image: modis/modis.png 13 | ViewOnEOBrowser: "[EO Browser](https://sentinelshare.page.link/6TQV)" 14 | Resolution: 500m 15 | GeographicalCoverage: MCD43A4.006 product covers Land ([more info](https://modis.gsfc.nasa.gov/about/specifications.php)) 16 | TemporalAvailability: February 24, 2000 - February 10, 2023 17 | UpdateFrequency: Archived data. Sentinel Hub no longer has the latest MODIS data. 18 | BandInformation: Information about [bands and data](https://docs.sentinel-hub.com/api/latest/data/modis/mcd/#available-bands-and-data) 19 | Contact: Sentinel Hub Forum on Planet Commmunity 20 | Provider: "[USGS](https://www.usgs.gov//)" 21 | ManagedBy: "[Sentinel Hub](https://www.sentinel-hub.com/)" 22 | Tags: 23 | - core collection 24 | - satellite imagery 25 | - agriculture 26 | - natural resource 27 | - disaster response 28 | - open data 29 | License: | 30 | - Sentinel Hub Terms of Use. 31 | - USGS EROS Data Citation. 32 | Resources: 33 | - EndPoint: services-uswest2.sentinel-hub.com 34 | Type: modis 35 | Notes: Gloabl from February 24, 2000 to February 10, 2023 36 | CustomScripts: 37 | Title: Collection of MODIS custom scripts 38 | URL: https://custom-scripts.sentinel-hub.com/#modis 39 | 40 | RegistryEntryAdded: "2018-04-17" 41 | RegistryEntryLastModified: "2024-05-10" 42 | -------------------------------------------------------------------------------- /collections/modis/modis.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/modis/modis.png -------------------------------------------------------------------------------- /collections/planet-basemaps.yaml: -------------------------------------------------------------------------------- 1 | Name: Planet Basemaps 2 | Description: | 3 | Globally available mosaics at a cell size of 4.77 m (at equator) using Mercator projection. 4 | Planet Basemaps are offered at a weekly, biweekly, monthly, or quarterly cadence and provide a clear, comprehensive view of an area of interest by automating the selection of the best individual images to create a complete, seamless, and recent “mosaic” that allows you to understand change over broad areas. 5 | Planet Basemaps are also well suited for machine learning-analytics by applying cloud masking and radiometric normalization to allow for consistent data across large geographic areas of interest. 6 | Documentation: | 7 | Planet Basemaps Product Documentation 8 | SandboxData: | 9 | Discover samples of Basemaps, free to all active Planet users and Sentinel Hub users with a paid subscription or a Trial account. Sandbox Data for Planet Basemaps 10 | Image: planet-basemaps/planet-basemaps.png 11 | Resolution: 4.77m at equator based on PlanetScope GSD 12 | GeographicalCoverage: Global between 74° N and 60° S (seasonally dependent) 13 | TemporalAvailability: 01 July 2016 - present 14 | UpdateFrequency: Weekly, Biweekly, Monthly, Quarterly 15 | Temporal Resolution: Weekly, biweekly, monthly or quarterly using PlanetScope daily imagery 16 | BandInformation: 17 | Table: 18 | Columns: 19 | - Name: Name 20 | Title: Name 21 | - Name: Description 22 | Title: Description 23 | Rows: 24 | - Name: blue 25 | Description: "Blue" 26 | - Name: green 27 | Description: "Green" 28 | - Name: red 29 | Description: "Red" 30 | - Name: nir 31 | Description: "NIR" 32 | - Name: alpha 33 | Description: "Alpha" 34 | - Name: provenance 35 | Description: "Provenance" 36 | - Name: clear 37 | Description: "Usable Data mask - Clear mask" 38 | - Name: snow 39 | Description: "Usable Data mask - Snow mask" 40 | - Name: shadow 41 | Description: "Usable Data mask - Shadow mask" 42 | - Name: haze_light 43 | Description: "Usable Data mask - Light haze mask" 44 | - Name: haze_heavy 45 | Description: "Usable Data mask - Heavy haze mask" 46 | - Name: cloud 47 | Description: "sable Data mask - Cloud mask" 48 | - Name: confidence 49 | Description: "Usable Data mask - Confidence map" 50 | - Name: udm1 51 | Description: "Unusable Data Mask" 52 | Contact: Sentinel Hub Forum on Planet Commmunity 53 | Provider: Planet 54 | ManagedBy: "[Planet](https://www.planet.com/)" 55 | Tags: 56 | - high resolution imagery 57 | - commercial data 58 | - satellite imagery 59 | - mosaic 60 | - vegetation monitoring 61 | - planetscope 62 | - mapping 63 | - analysis ready data 64 | - sandbox data 65 | License: License 66 | Resources: 67 | - EndPoint: services.sentinel-hub.com 68 | Type: BYOC collection 69 | Notes: Contains the data purchased by individual user. [Explore sample CC-BY-NC sandbox data here](https://docs.planet.com/data/imagery/basemaps/sandbox/) 70 | CustomScripts: 71 | Title: Coming soon here 72 | URL: https://custom-scripts.sentinel-hub.com/ 73 | 74 | RegistryEntryAdded: "2024-03-15" 75 | RegistryEntryLastModified: "2024-04-03" 76 | -------------------------------------------------------------------------------- /collections/planet-basemaps/PB_AUS.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/planet-basemaps/PB_AUS.png -------------------------------------------------------------------------------- /collections/planet-basemaps/PB_BRA.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/planet-basemaps/PB_BRA.png -------------------------------------------------------------------------------- /collections/planet-basemaps/PB_FRA.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/planet-basemaps/PB_FRA.png -------------------------------------------------------------------------------- /collections/planet-basemaps/planet-basemaps.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/planet-basemaps/planet-basemaps.png -------------------------------------------------------------------------------- /collections/planet-basemaps/sandbox-data.md: -------------------------------------------------------------------------------- 1 | 4 | -------------------------------------------------------------------------------- /collections/planetscope.yaml: -------------------------------------------------------------------------------- 1 | Name: PlanetScope 2 | Description: | 3 | With hundreds of Dove satellites in orbit, PlanetScope Monitoring provides a medium-resolution, continuous, and complete view of the world from above, every day. PlanetScope images are approximately 3 m per pixel resolution. 4 | 5 | Sentinel Hub offers the ability to purchase, order and access both the archive data and newly acquired data available globally since 2016. Sentinel Hub provides access to PlanetScope data in Top of the atmosphere (TOA) reflectance. 6 | Documentation: | 7 | Sentinel Hub Documentation for PlanetScope
    8 | Product Website for PlanetScope 9 | SandboxData: | 10 | Discover samples of PlanetScope, free to all active Planet users and Sentinel Hub users with a paid subscription or a Trial account. Sandbox Data for PlanetScope 11 | Image: planetscope/planetscope.png 12 | Resolution: 3m 13 | GeographicalCoverage: Land surface area (more info) 14 | TemporalAvailability: 2016 - ongoing 15 | UpdateFrequency: new imagery added on a daily basis 16 | BandInformation: Information about bands and data 17 | Contact: Sentinel Hub Forum on Planet Commmunity 18 | Provider: Planet 19 | ManagedBy: "[Planet](https://www.planet.com/)" 20 | Tags: 21 | - high resolution imagery 22 | - commercial data 23 | - satellite imagery 24 | - multi spectral imagery 25 | - vegetation monitoring 26 | - mapping 27 | - agriculture 28 | - sandbox data 29 | License: License 30 | Resources: 31 | - EndPoint: services.sentinel-hub.com 32 | Type: BYOC collection 33 | Notes: Contains the data purchased by individual user. [Explore sample CC-BY-NC sandbox data here](https://docs.planet.com/data/imagery/planetscope/sandbox/) 34 | CustomScripts: 35 | Title: Collection of PlanetScope custom scripts 36 | URL: https://custom-scripts.sentinel-hub.com/#planet_scope 37 | 38 | 39 | RegistryEntryAdded: "2018-04-17" 40 | RegistryEntryLastModified: "2024-05-10" 41 | -------------------------------------------------------------------------------- /collections/planetscope/PS_AUS.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/planetscope/PS_AUS.png -------------------------------------------------------------------------------- /collections/planetscope/PS_BRA.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/planetscope/PS_BRA.png -------------------------------------------------------------------------------- /collections/planetscope/PS_EGY.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/planetscope/PS_EGY.png -------------------------------------------------------------------------------- /collections/planetscope/planetscope.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/planetscope/planetscope.png -------------------------------------------------------------------------------- /collections/planetscope/sandbox-data.md: -------------------------------------------------------------------------------- 1 | 4 | -------------------------------------------------------------------------------- /collections/road-and-building-detection.yaml: -------------------------------------------------------------------------------- 1 | Name: Road and Building Detection 2 | Description: | 3 | Globally available land cover maps derived from Planetscope imagery classifying pixels as road, building or neither. Generated on a weekly or monthly basis, Planet's Road & Building Detection can be used to stay up to date with the latest development around the globe. 4 | By leveraging a semantic segmentation model on all the PlanetScope imagery published in a given area for a given week or month, we assign a probability value (0-255) that the pixel represents a road, building or neither object. 5 | These results are aggregated together into a weekly or monthly layer and this process is repeated through time, generating a time-series of pixel values ready for analysis. 6 | Documentation: | 7 | Planet Road and Building Detection Product Documentation 8 | SandboxData: | 9 | Discover samples of Road and Buiding Detection, free to all active Planet users and Sentinel Hub users with a paid subscription or a Trial account. Sandbox Data for Road and Building Detection 10 | Image: road-and-building-detection/road-and-building-detection.png 11 | Resolution: 4.77m at equator based on PlanetScope GSD 12 | GeographicalCoverage: Global between 74° N and 60° S (seasonally dependent) 13 | TemporalAvailability: 01 January 2018 - present 14 | UpdateFrequency: Weekly or Monthly 15 | Temporal Resolution: Weekly or monthly using PlanetScope daily imagery 16 | BandInformation: 17 | Table: 18 | Columns: 19 | - Name: Name 20 | Title: Name 21 | - Name: Description 22 | Title: Description 23 | - Name: Values 24 | Title: Values 25 | Rows: 26 | - Name: roads 27 | Description: "Road Detection" 28 | Values: "[0-255], (the greater the pixel value, the greater the likelihood that the pixel is classified correctly)" 29 | - Name: buildings 30 | Description: "Building Detection" 31 | Values: "[0-255], (the greater the pixel value, the greater the likelihood that the pixel is classified correctly)" 32 | - Name: other 33 | Description: "Neither Roads nor Buildings" 34 | Values: "[0-255], (the greater the pixel value, the greater the likelihood that the pixel is classified correctly)" 35 | - Name: alpha 36 | Description: "Alpha mask" 37 | Values: "[0/255], 255 indicating valid pixels, 0 indicating invalid pixels" 38 | Contact: Sentinel Hub Forum on Planet Commmunity 39 | Provider: Planet 40 | ManagedBy: "[Planet](https://www.planet.com/)" 41 | Tags: 42 | - high resolution imagery 43 | - commercial data 44 | - planetscope 45 | - analytics 46 | - building detection 47 | - road detection 48 | - land cover 49 | - mapping 50 | - sandbox data 51 | License: License 52 | Resources: 53 | - EndPoint: services.sentinel-hub.com 54 | Type: BYOC collection 55 | Notes: Contains the data purchased by individual user. [Explore sample CC-BY-NC sandbox data here](sandbox-data.html) 56 | CustomScripts: 57 | Title: Coming soon here 58 | URL: https://custom-scripts.sentinel-hub.com/ 59 | 60 | RegistryEntryAdded: "2024-05-10" 61 | RegistryEntryLastModified: "2024-05-10" 62 | -------------------------------------------------------------------------------- /collections/road-and-building-detection/RNB_AUS.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/road-and-building-detection/RNB_AUS.png -------------------------------------------------------------------------------- /collections/road-and-building-detection/RNB_BRA.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/road-and-building-detection/RNB_BRA.png -------------------------------------------------------------------------------- /collections/road-and-building-detection/RNB_EGY.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/road-and-building-detection/RNB_EGY.png -------------------------------------------------------------------------------- /collections/road-and-building-detection/road-and-building-detection.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/road-and-building-detection/road-and-building-detection.png -------------------------------------------------------------------------------- /collections/sea-ice-index/README.md: -------------------------------------------------------------------------------- 1 | # Water Bodies 2 | 3 | ## Short description 4 | 5 | [Sea Ice Index](https://nsidc.org/data/G02135/versions/3) products offer information about ice cover and its trends in the Arctic and Antarctica. 6 | In this collection, sea ice extent and concentration maps are provided at a resolution of 25 km on a daily basis. 7 | The products are computed using images from the Special Sensor Microwave Imager (SSM/I) and 8 | Special Sensor Microwave Imager/Sounder (SSMIS) instruments on Defense Meteorological Satellite Program (DMSP) 9 | satellites. Sea ice concentrations are generated from 10 | [brightness temperature data](https://nsidc.org/data/nsidc-0051). Sea ice extent is computed as areas covered by ice 11 | with a concentration greater than 15 percent. This dataset is for demonstration purposes only and is not maintained. 12 | 13 | ## Band information 14 | 15 | The sea ice index product contains 4 bands that are described in Table 1 below. 16 | 17 |
    18 | 19 | **Table 1: Bands** 20 | 21 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 | 41 | 42 | 43 | 44 | 45 | 46 | 47 | 48 | 49 | 50 | 51 | 52 | 53 | 54 | 55 | 56 | 57 | 58 | 59 | 60 | 61 |
    NameValuesDescription
    Concentration0-1000; 2540; 2530Sea ice concentration, includes land masses and coastlines. Sea ice concentration are expressed in percentage * 10. Land masses are assigned the value 2540. Coastlines are assigned the value 2530.
    Concentration ice0-1000Sea ice concentration. Values are expressed in percentage * 10.
    Extent0; 1; 253; 254Sea ice extent (binary), includes land masses and coastlines. Areas covered by ice are assigned the value 1. Land masses are assigned the value 254. Coastlines are assigned the value 253.
    Extent ice0;1Sea ice extent (binary).
    62 | 63 | ## More information 64 | - [Data Source](https://nsidc.org/data/G02135/versions/3) 65 | - [Product User Manual](https://nsidc.org/sites/nsidc.org/files/G02135-V003-UserGuide_1.pdf) 66 | 67 | 68 | ![Sea ice concentration](sea-ice-concentration.png) 69 | 70 | *Sea ice concentration in the northern hemisphere on 29th January 2021.* 71 | 72 | ![Sea ice extent](sea-ice-extent.png) 73 | 74 | *Sea ice extent in the southern hemisphere on 29th July 2020.* 75 | 76 | -------------------------------------------------------------------------------- /collections/sea-ice-index/sea-ice-concentration.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/sea-ice-index/sea-ice-concentration.png -------------------------------------------------------------------------------- /collections/sea-ice-index/sea-ice-extent.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/sea-ice-index/sea-ice-extent.png -------------------------------------------------------------------------------- /collections/sea-ice-index/sea-ice.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/sea-ice-index/sea-ice.png -------------------------------------------------------------------------------- /collections/seasonal-trajectories/README.MD: -------------------------------------------------------------------------------- 1 | # Seasonal Trajectories, 10-daily 2 | 3 | ## Short description 4 | Seasonal Trajectories (ST) product is a filtered time series of [Plant Phenology Index(PPI)](https://www.nateko.lu.se/research/remote-sensing-and-earth-observation/lund-earth-observation-research-group/vegetation-phenology) provided yearly on a 10-daily basis at 10m resolution . 5 | It is part of the Copernicus Land Monitoring Service (CLMS), pan-European High Resolution Vegetation Phenology and Productivity [(HR-VPP)](https://land.copernicus.eu/pan-european/biophysical-parameters/high-resolution-vegetation-phenology-and-productivity) product suite. 6 | The Seasonal Trajectories PPI is derived through fitting a smoothing and gap filling function to the yearly time-series raw PPI values generated from Sentinel-2 satellite observations. 7 | In addition to the PPI band, a QFLAG band indicating the quality of the smoothing process is included. 8 | The Seasonal Trajectories provide the vegetation status for each pixel on a regular 10-day time step from January 1 2017 onwards over the EEA39 region. 9 | More information about ST product is outlined in the [product user manual](https://land.copernicus.eu/user-corner/technical-library/product-user-manual-of-seasonal-trajectories/) 10 | 11 | ## Band information 12 | The available bands include: PPI and QFLAG 13 | 14 | ### QFLAG 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | 29 | 30 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 | 41 | 42 | 43 | 44 | 45 | 46 | 47 | 48 | 49 | 50 | 51 | 52 | 53 | 54 | 55 | 56 |
    ValueQualityDefinition
    5High More than 8 Clear-sky land observations found in a 91-day-window
    4medium 3 to 8 Clear-sky land observations found in a 91-day-window
    3low 1 to 2 Clear-sky land observations found in a 91-day-window
    2Filled (interpolation) Clear-sky land observation(s) found on both left and right sides but outside a 91-day-window
    1Filled (extrapolation) Clear-sky land observation found on one side (left or right) but outside a 91-day-window
    0 Filled (extrapolation) The time series was not processed
    57 | 58 | ## More information 59 | 60 | ### Representative Images 61 | 62 | Erdine Turkey Seasonal Trajectories PPI 63 | 64 | *Seasonal Trajectories PPI August 2019, Gala Lake and surroundings along Greece-Turkey border.* 65 | 66 |
    67 |
    68 | Erdine Turkey Seasonal Trajectories PPI 69 | 70 | *Seasonal Trajectories PPI September 2019, Gala Lake and surroundings along Greece-Turkey border.* 71 | -------------------------------------------------------------------------------- /collections/seasonal-trajectories/erdine-turkey-august.PNG: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/seasonal-trajectories/erdine-turkey-august.PNG -------------------------------------------------------------------------------- /collections/seasonal-trajectories/erdine-turkey-sept.PNG: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/seasonal-trajectories/erdine-turkey-sept.PNG -------------------------------------------------------------------------------- /collections/seasonal-trajectories/thumbnail-1.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/seasonal-trajectories/thumbnail-1.png -------------------------------------------------------------------------------- /collections/seasonal-trajectories/thumbnail.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/seasonal-trajectories/thumbnail.png -------------------------------------------------------------------------------- /collections/sentinel-1-grd.yaml: -------------------------------------------------------------------------------- 1 | Name: Sentinel-1 GRD 2 | Description: 3 | The [Sentinel - 1 radar imaging mission](https://sentinel.esa.int/web/sentinel/missions/sentinel-1) 4 | is composed of a constellation of two polar-orbiting satellites providing continous all-weather, day and night imagery for 5 | Land and Maritime Monitoring. C-band synthentic aperture radar imaging has the advantage of operating at wavelenghts that are 6 | not obstructed by clouds or lack of illumination and therefore can acquire data during day or night under all weather conditions. 7 | With 6 days repeat cycle on the entire world and daily acquistions of sea ice zones and Europe's major shipping routes, 8 | Sentinel-1 ensures reliable data availability to support emergency services and applications requiring time series observations. 9 | Sentinel-1 continues the retired ERS and ENVISAT missions. Level 1 GRD products are available since October 2014. 10 | Documentation: "[here](https://docs.sentinel-hub.com/api/latest/data/sentinel-1-grd/)" 11 | Image: sentinel-1-grd/sentinel-1-grd.png 12 | Resolution: High - 10m, Medium - 40m 13 | ViewOnEOBrowser: "[EO Browser](https://apps.sentinel-hub.com/eo-browser/?zoom=10&lat=41.9&lng=12.5&themeId=DEFAULT-THEME&datasetId=S1_AWS_IW_VVVH&fromTime=2021-03-28T00%3A00%3A00.000Z&toTime=2021-03-28T23%3A59%3A59.999Z&layerId=ENHANCED-VISUALIZATION-ORTHORECTIFIED&visualizationUrl=https%3A%2F%2Fservices.sentinel-hub.com%2Fogc%2Fwms%2Ff2068f4f-3c75-42cf-84a1-42948340a846)" 14 | GeographicalCoverage: Land, coastal zones, shipping routes ([more info](https://sentinel.esa.int/web/sentinel/user-guides/sentinel-1-sar/revisit-and-coverage)) 15 | TemporalAvailability: October 2014- ongoing 16 | UpdateFrequency: New Sentinel data are added regularly, usually within few hours after they are available on Copernicus Hub. 17 | BandInformation: Information about [bands and data](https://docs.sentinel-hub.com/api/latest/data/sentinel-1-grd/#available-bands-and-data) 18 | Contact: Sentinel Hub Forum on Planet Commmunity 19 | Provider: "[Copernicus](https://copernicus.eu/)" 20 | ManagedBy: "[Sentinel Hub](https://www.sentinel-hub.com/)" 21 | Tags: 22 | - core collection 23 | - satellite imagery 24 | - SAR 25 | - maritime monitoring 26 | - land monitoring 27 | - disaster response 28 | - open data 29 | - sentinel 30 | License: | 31 | - Sentinel Hub Terms of Use. 32 | - Sentinel-1 GRD Attribution and Use . 33 | Resources: 34 | - EndPoint: services.sentinel-hub.com 35 | Type: sentinel-1-grd 36 | Notes: Global since January 2017 37 | CustomScripts: 38 | Title: Collection of Sentinel-1 custom scripts 39 | URL: https://custom-scripts.sentinel-hub.com/#sentinel-1 40 | 41 | 42 | RegistryEntryAdded: "2018-04-17" 43 | RegistryEntryLastModified: "2025-02-25" 44 | -------------------------------------------------------------------------------- /collections/sentinel-1-grd/sentinel-1-grd.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/sentinel-1-grd/sentinel-1-grd.png -------------------------------------------------------------------------------- /collections/sentinel-2-l1c.yaml: -------------------------------------------------------------------------------- 1 | Name: Sentinel-2 L1C 2 | Description: | 3 | The [Sentinel-2 mission](https://sentinel.esa.int/web/sentinel/missions/sentinel-2) is 4 | a land monitoring constellation of two satellites that provide high resolution 5 | optical imagery and provide continuity for the current SPOT and Landsat missions. 6 | The mission provides a global coverage of the Earth's land surface every 5 days, 7 | making the data of great use in on-going studies. L1C data are available from 8 | June 2015 globally. L1C data provide Top of the atmosphere (TOA) reflectance. 9 | Image: sentinel-2-l1c/sentinel-2-l1c.png 10 | Documentation: "[here](https://docs.sentinel-hub.com/api/latest/data/sentinel-2-l1c/)" 11 | ViewOnEOBrowser: "[EO Browser](https://apps.sentinel-hub.com/eo-browser/?zoom=10&lat=41.9&lng=12.5&themeId=DEFAULT-THEME&datasetId=S2L1C&fromTime=2021-03-31T00%3A00%3A00.000Z&toTime=2021-03-31T23%3A59%3A59.999Z&layerId=1_TRUE_COLOR&visualizationUrl=https%3A%2F%2Fservices.sentinel-hub.com%2Fogc%2Fwms%2F42924c6c-257a-4d04-9b8e-36387513a99c)" 12 | Resolution: 10m 13 | GeographicalCoverage: Land surface area ([more info](https://sentinel.esa.int/web/sentinel/user-guides/sentinel-2-msi/revisit-coverage)) 14 | TemporalAvailability: 2015 - ongoing 15 | UpdateFrequency: New Sentinel data are added regularly, usually within few hours after they are available on Copernicus Hub. 16 | BandInformation: Information about [bands and data](https://docs.sentinel-hub.com/api/latest/data/sentinel-2-l1c/#available-bands-and-data) 17 | Contact: Sentinel Hub Forum on Planet Commmunity 18 | Provider: "[Copernicus](https://copernicus.eu/)" 19 | ManagedBy: "[Sentinel Hub](https://www.sentinel-hub.com/)" 20 | Tags: 21 | - core collection 22 | - satellite imagery 23 | - multi spectral imagery 24 | - agriculture 25 | - natural resource 26 | - disaster response 27 | - open data 28 | - sentinel 29 | License: | 30 | - Sentinel Hub Terms of Use. 31 | - Sentinel-2 L1C Attribution and Use . 32 | Resources: 33 | - EndPoint: services.sentinel-hub.com 34 | Type: sentinel-2-l1c 35 | Notes: Global since November 2015 36 | CustomScripts: 37 | Title: Collection of Sentinel-2 custom scripts 38 | URL: https://custom-scripts.sentinel-hub.com/#sentinel-2 39 | 40 | 41 | RegistryEntryAdded: "2018-04-17" 42 | RegistryEntryLastModified: "2025-02-25" 43 | -------------------------------------------------------------------------------- /collections/sentinel-2-l1c/sentinel-2-l1c.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/sentinel-2-l1c/sentinel-2-l1c.png -------------------------------------------------------------------------------- /collections/sentinel-2-l2a.yaml: -------------------------------------------------------------------------------- 1 | Name: Sentinel-2 L2A 2 | Description: | 3 | The [Sentinel-2 mission](https://sentinel.esa.int/web/sentinel/missions/sentinel-2) is 4 | a land monitoring constellation of two satellites that provide high resolution 5 | optical imagery and provide continuity for the current SPOT and Landsat missions. 6 | The mission provides a global coverage of the Earth's land surface every 5 days, 7 | making the data of great use in on-going studies. L2A data are available from November 2016 over Europe 8 | region and globally since January 2017. L2A data provide Bottom of the atmosphere (BOA) reflectance. 9 | Documentation: "[here](https://docs.sentinel-hub.com/api/latest/data/sentinel-2-l2a/)" 10 | Image: sentinel-2-l2a/sentinel-2-l2a.png 11 | ViewOnEOBrowser: "[EO Browser](https://apps.sentinel-hub.com/eo-browser/?zoom=10&lat=41.9&lng=12.5&themeId=DEFAULT-THEME&datasetId=S2L2A&fromTime=2021-03-31T00%3A00%3A00.000Z&toTime=2021-03-31T23%3A59%3A59.999Z&layerId=1_TRUE_COLOR&visualizationUrl=https%3A%2F%2Fservices.sentinel-hub.com%2Fogc%2Fwms%2Fbd86bcc0-f318-402b-a145-015f85b9427e)" 12 | Resolution: 10m 13 | GeographicalCoverage: Land surface area ([more info](https://sentinel.esa.int/web/sentinel/user-guides/sentinel-2-msi/revisit-coverage)) 14 | TemporalAvailability: Europe November 2016 - ongoing, Global January 2017 - ongoing 15 | UpdateFrequency: New Sentinel data are added regularly, usually within few hours after they are available on Copernicus Hub. 16 | BandInformation: "Information about [bands and data](https://docs.sentinel-hub.com/api/latest/data/sentinel-2-l2a/#available-bands-and-data)" 17 | Contact: Sentinel Hub Forum on Planet Commmunity 18 | Provider: "[Copernicus](https://copernicus.eu/)" 19 | ManagedBy: "[Sentinel Hub](https://www.sentinel-hub.com/)" 20 | Tags: 21 | - core collection 22 | - satellite imagery 23 | - multi spectral imagery 24 | - agriculture 25 | - natural resource 26 | - disaster response 27 | - open data 28 | - sentinel 29 | License: | 30 | - Sentinel Hub Terms of Use. 31 | - Sentinel-2 L2A Attribution and Use . 32 | Resources: 33 | - EndPoint: services.sentinel-hub.com 34 | Type: sentinel-2-l2a 35 | Notes: Europe since November 2016, Global since January 2017 36 | CustomScripts: 37 | Title: Collection of Sentinel-2 custom scripts 38 | URL: https://custom-scripts.sentinel-hub.com/#sentinel-2 39 | 40 | RegistryEntryAdded: "2018-04-17" 41 | RegistryEntryLastModified: "2025-02-25" 42 | -------------------------------------------------------------------------------- /collections/sentinel-2-l2a/sentinel-2-l2a.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/sentinel-2-l2a/sentinel-2-l2a.png -------------------------------------------------------------------------------- /collections/sentinel-3-l1b-olci/sentinel-3-l1b-olci.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/sentinel-3-l1b-olci/sentinel-3-l1b-olci.png -------------------------------------------------------------------------------- /collections/sentinel-3-l1b-slstr/sentinel-3-l1b-slstr.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/sentinel-3-l1b-slstr/sentinel-3-l1b-slstr.png -------------------------------------------------------------------------------- /collections/sentinel-5p-l2-tropomi/sentinel-5p-l2-tropomi.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/sentinel-5p-l2-tropomi/sentinel-5p-l2-tropomi.png -------------------------------------------------------------------------------- /collections/sentinel-s2-l2a-mosaic-120.yaml: -------------------------------------------------------------------------------- 1 | Name: Sentinel-2 L2A 120m Mosaic 2 | Description: Sentinel-2 L2A 120m mosaic is a derived product, which contains best pixel values for 10-daily periods, modelled by removing the cloudy pixels and then performing interpolation among remaining values. As clouds can be missed and as there are some parts of the world which have lengthy cloudy periods, clouds might be remaining in some parts. The actual modelling script is available [here](https://sentinel-hub.github.io/custom-scripts/sentinel-2/interpolated_time_series/). 3 | AdditionalInfoExternal: 4 | Title: Additional info 5 | Path: sentinel-s2-l2a-mosaic-120/README.MD 6 | Image: sentinel-s2-l2a-mosaic-120/sentinel-s2-l2a-mosaic-120.png 7 | Resolution: 120m 8 | GeographicalCoverage: Land surface area between 58 degrees South and 72 degrees North. 9 | TemporalAvailability: 2020 (past years will be added later); old 2019 data results can be found [here](https://collections.sentinel-hub.com/sentinel-s2-l2a-mosaic-120/sentinel-2-l2a-120m-mosaic-2019.html). 10 | UpdateFrequency: New data will be added annually. 11 | BandInformation: 12 | Table: 13 | Columns: 14 | - Name: Name 15 | Title: Name 16 | - Name: Description 17 | Title: Description 18 | - Name: Notes 19 | Title: Notes 20 | Rows: 21 | - Name: B01 22 | Description: Coastal aerosol 23 | Notes: DN, typically from 0-10000 24 | - Name: B02 25 | Description: Blue 26 | Notes: DN, typically from 0-10000 27 | - Name: B03 28 | Description: Green 29 | Notes: DN, typically from 0-10000 30 | - Name: B04 31 | Description: Red 32 | Notes: DN, typically from 0-10000 33 | - Name: B05 34 | Description: Vegetation red edge 35 | Notes: DN, typically from 0-10000 36 | - Name: B06 37 | Description: Vegetation red edge 38 | Notes: DN, typically from 0-10000 39 | - Name: B07 40 | Description: Vegetation red edge 41 | Notes: DN, typically from 0-10000 42 | - Name: B08 43 | Description: NIR 44 | Notes: DN, typically from 0-10000 45 | - Name: B8A 46 | Description: Narrow NIR 47 | Notes: DN, typically from 0-10000 48 | - Name: B09 49 | Description: Water Vapour 50 | Notes: DN, typically from 0-10000 51 | - Name: B11 52 | Description: SWIR 53 | Notes: DN, typically from 0-10000 54 | - Name: B12 55 | Description: SWIR 56 | Notes: DN, typically from 0-10000 57 | - Name: QM 58 | Description: QualityMask 59 | Notes: DN, from 0-3; OK if larger than 0. Additional info here. 60 | Contact: Sentinel Hub Forum on Planet Commmunity 61 | Provider: "[Sentinel Hub](https://www.sentinel-hub.com/)" 62 | ManagedBy: "[Sentinel Hub](https://www.sentinel-hub.com/)" 63 | Tags: 64 | - satellite imagery 65 | - multi spectral imagery 66 | - machine learning 67 | - agriculture 68 | - open data 69 | - sentinel 70 | License: | 71 | - "CC-BY 4.0, Credit: Contains modified Copernicus data 2020 processed by Sentinel Hub" 72 | - Sentinel Hub Terms of Use. 73 | Resources: 74 | - EndPoint: services.sentinel-hub.com 75 | Type: byoc-484d8dbb-9e3e-41f2-b96b-35189d3ae37f 76 | CollectionId: 484d8dbb-9e3e-41f2-b96b-35189d3ae37f 77 | Notes: Global data for 2020 78 | 79 | DataAtWork: 80 | Tutorials: 81 | - Title: How to Make the Perfect Time-Lapse of the Earth 82 | URL: https://medium.com/sentinel-hub/how-to-make-the-perfect-time-lapse-of-the-earth-351f214527f6 83 | AuthorName: Lubej M. 84 | AuthorURL: https://medium.com/@lubej.matic 85 | Tools & Applications: 86 | - Title: Digital Twin Sandbox 87 | URL: https://apps.sentinel-hub.com/digital_twin_sandbox 88 | AuthorName: Sentinel Hub 89 | AuthorURL: http://www.sentinel-hub.com/ 90 | Publications: 91 | - Title: Digital Twin Sandbox Sentinel-2 collection available to everyone 92 | URL: https://medium.com/sentinel-hub/digital-twin-sandbox-sentinel-2-collection-available-to-everyone-20f3b5de846e 93 | AuthorName: Milcinski G., Lubej M. 94 | 95 | RegistryEntryAdded: "2021-03-21" 96 | RegistryEntryLastModified: "2024-05-10" 97 | -------------------------------------------------------------------------------- /collections/sentinel-s2-l2a-mosaic-120/2019_images/image.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/sentinel-s2-l2a-mosaic-120/2019_images/image.png -------------------------------------------------------------------------------- /collections/sentinel-s2-l2a-mosaic-120/2019_images/timelapse.gif: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/sentinel-s2-l2a-mosaic-120/2019_images/timelapse.gif -------------------------------------------------------------------------------- /collections/sentinel-s2-l2a-mosaic-120/README.MD: -------------------------------------------------------------------------------- 1 | # Sentinel-2 L2A 120m Mosaic 2 | 3 | ## Short description 4 | 5 | Sentinel-2 L2A 120m mosaic is a derived product, which contains best pixel values for 10-daily periods, modelled by removing the cloudy pixels and then performing interpolation among remaining values. As clouds can be missed and as there are some parts of the world which have lengthy cloudy periods, clouds might be remaining in some parts. The actual modelling script is available [here](https://sentinel-hub.github.io/custom-scripts/sentinel-2/interpolated_time_series/). 6 | 7 | ## Band information 8 | Sentinel-2 L2A 120m mosaic contains 12 Sentinel 2 L2A bands and 1 quality mask. Find more information about sentinel 2 L2A bands [here](https://docs.sentinel-hub.com/api/latest/data/sentinel-2-l2a/#available-bands-and-data). 9 | 10 | ### Quality Mask 11 | 12 | #### Value details 13 | - 0: no data; areas where no valid observations have been found 14 | - 1: interpolation passed; areas where the interpolation process successfully finished 15 | - 2: artificially raised value; some/all bands' DN values here were raised from 0 to 1 so that these areas are not confused with `NO_DATA` areas 16 | - 3: interpolation failed; usually this happens if it's detected that clouds are always present - the values is set to max of bands' values, which is 10000 17 | 18 | #### Usage 19 | 20 | All values larger than 0 are deemed as OK, so it is suggested to use the `QM` band in the following way for selecting valid areas: 21 | `QM != 0` 22 | 23 | ## More information 24 | 25 | ### Representative Images and Animations 26 | 27 | World mosaic 2020 28 |
    29 | 30 | *World mosaic, using 2020 Sentinel-2 L2A data.* 31 | 32 |
    33 |
    34 | World mosaic 2020, blue marble background 35 |
    36 | 37 | *World mosaic 2020 animation on blue marble background with sea ice index information* 38 | 39 |
    40 |
    41 | World mosaic 2020, blue marble background 42 |
    43 | 44 | *World mosaic 2020 3D animation on blue marble background with sea ice index information* 45 | 46 | 47 | -------------------------------------------------------------------------------- /collections/sentinel-s2-l2a-mosaic-120/sentinel-2-l2a-120m-mosaic-2019.MD: -------------------------------------------------------------------------------- 1 | # Sentinel-2 L2A 120m Mosaic-2019 2 | 3 | Sentinel-2 L2A 120m mosaic is a derived product, which contains best pixel values for 10-daily periods, modelled by removing the cloudy pixels and then performing interpolation among remaining values. As there are some parts of the world, which have lengthy cloudy periods, clouds might be remaining in some parts. The actual modelling script is available [here](https://sentinel-hub.github.io/custom-scripts/sentinel-2/interpolated_time_series/). Sentinel-2 L2A 120m Mosaic 2019 product contains 6 of Sentinel 2 L2A bands. 4 | 5 | ## Resources and access details 6 | 7 | |Name | Description| 8 | | ------ | ------ | 9 | | End Point | `services.sentinel-hub.com` | 10 | | Type | `byoc-0074520d-bcf5-4811-8f6f-afd946e77695`| 11 | | Collection_id |`0074520d-bcf5-4811-8f6f-afd946e77695` | 12 | 13 | 14 | ## Band information 15 | Sentinel-2 L2A 120m Mosaic 2019 product contains 6 bands as described in table 1 below. Find more information about sentinel 2 L2A bands [here](https://docs.sentinel-hub.com/api/latest/data/sentinel-2-l2a/#available-bands-and-data) 16 | **Table 1: Bands** 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | 29 | 30 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 | 41 | 42 | 43 | 44 | 45 | 46 | 47 | 48 | 49 | 50 | 51 | 52 | 53 | 54 | 55 | 56 | 57 | 58 |
    NameDescription Notes
    B02 Blue DN, typically from 0-10000
    B03 Green DN, typically from 0-10000
    B04 Red DN, typically from 0-10000
    B08 NIR DN, typically from 0-10000
    B11 SWIR DN, typically from 0-10000
    B12 SWIR DN, typically from 0-10000
    59 | 60 | ## More information 61 | 62 | ### Representative images 63 | 64 | ![Yearly time-lapse of the world](2019_images/timelapse.gif) 65 | 66 | *Yearly time-lapse of the world, using 2019 Sentinel-2 L2A data.* 67 | 68 | ![Screenshot of the same data in the EO Browser](2019_images/image.png) 69 | 70 | *Screenshot of the same data in EO Browser* 71 | 72 | -------------------------------------------------------------------------------- /collections/sentinel-s2-l2a-mosaic-120/sentinel-2-l2a-120m-mosaic.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/sentinel-s2-l2a-mosaic-120/sentinel-2-l2a-120m-mosaic.png -------------------------------------------------------------------------------- /collections/sentinel-s2-l2a-mosaic-120/sentinel-s2-l2a-mosaic-120-2020.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/sentinel-s2-l2a-mosaic-120/sentinel-s2-l2a-mosaic-120-2020.png -------------------------------------------------------------------------------- /collections/sentinel-s2-l2a-mosaic-120/sentinel-s2-l2a-mosaic-120.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/sentinel-s2-l2a-mosaic-120/sentinel-s2-l2a-mosaic-120.png -------------------------------------------------------------------------------- /collections/sentinel-s2-l2a-mosaic-120/world_mosaic_2020.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/sentinel-s2-l2a-mosaic-120/world_mosaic_2020.png -------------------------------------------------------------------------------- /collections/sentinel-s2-l2a-mosaic-120/world_mosaic_2020_blue_marble.gif: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/sentinel-s2-l2a-mosaic-120/world_mosaic_2020_blue_marble.gif -------------------------------------------------------------------------------- /collections/sentinel-s2-l2a-mosaic-120/world_mosaic_2020_blue_marble.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/sentinel-s2-l2a-mosaic-120/world_mosaic_2020_blue_marble.png -------------------------------------------------------------------------------- /collections/sentinel-s2-l2a-mosaic-120/world_mosaic_2020_blue_marble_3d.gif: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/sentinel-s2-l2a-mosaic-120/world_mosaic_2020_blue_marble_3d.gif -------------------------------------------------------------------------------- /collections/skysat.yaml: -------------------------------------------------------------------------------- 1 | Name: SkySat 2 | Description: | 3 | Planet's extensive Skysat archive is available at 50 cm spatial resolution for images collected on or after June 30, 2020, and at 72 cm spatial resolution for images collected before June 30, 2020. 4 | The SkySat image archive dates back to 2014. 5 | 6 | The Skysat satellite constellation consists of ~20 satellites that were launched between 2013 and 2020. 7 | Because of its rapid revisit time, these data are suitable for monitoring rapid changes on the Earth's surface. 8 | Documentation: | 9 | Sentinel Hub Documentation for SkySat
    10 | Product Website for Skysat 11 | SandboxData: | 12 | Discover samples of SkySat, free to all active Planet users and Sentinel Hub users with a paid subscription or a Trial account. Sandbox Data for SkySat 13 | Image: skysat/skysat.png 14 | Resolution: 0.5m (resampled) 15 | GeographicalCoverage: Worldwide (more info) 16 | TemporalAvailability: 2014 - ongoing 17 | UpdateFrequency: Capacity to image up to 10x a day but acquisitions must be tasked (ordered). 18 | BandInformation: Information about bands and data 19 | Contact: Sentinel Hub Forum on Planet Commmunity 20 | Provider: Planet 21 | ManagedBy: "[Planet](https://www.planet.com/)" 22 | Tags: 23 | - high resolution imagery 24 | - commercial data 25 | - satellite imagery 26 | - multi spectral imagery 27 | - vegetation monitoring 28 | - mapping 29 | - agriculture 30 | - sandbox data 31 | License: License 32 | Resources: 33 | - EndPoint: services.sentinel-hub.com 34 | Type: BYOC collection 35 | Notes: Contains the data purchased by individual user. [Explore sample CC-BY-NC sandbox data here](https://docs.planet.com/data/imagery/skysat/sandbox/) 36 | CustomScripts: 37 | Title: Collection of SkySat custom scripts 38 | URL: https://custom-scripts.sentinel-hub.com/#sky_sat 39 | 40 | 41 | RegistryEntryAdded: "2022-11-24" 42 | RegistryEntryLastModified: "2024-05-10" 43 | -------------------------------------------------------------------------------- /collections/skysat/SS_AUS.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/skysat/SS_AUS.png -------------------------------------------------------------------------------- /collections/skysat/SS_EGY.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/skysat/SS_EGY.png -------------------------------------------------------------------------------- /collections/skysat/sandbox-data.md: -------------------------------------------------------------------------------- 1 | 4 | -------------------------------------------------------------------------------- /collections/skysat/skysat.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/skysat/skysat.png -------------------------------------------------------------------------------- /collections/soil-water-content.yaml: -------------------------------------------------------------------------------- 1 | Name: Soil Water Content 2 | Description: | 3 | The Soil Water Content is the measure of the amount of water present in a unit volume of soil. 4 | It is typically expressed as a percentage and represents the ratio between the volume of water and the total volume of the soil. 5 | This measurement is crucial for understanding the water status of the soil and provides information on factors such as drought monitoring, soil health and hydrological processes. 6 | The Soil Water Content Planetary Variable measures the water content of the soil almost daily with a spatial resolution of 100 m and 1000 m. 7 | It is not affected by clouds and has a long and consistent data record of more than 20 years, so there is no need to maintain large networks of physical sensors. 8 | Documentation: | 9 | Sentinel Hub Documentation for Soil Water Content
    10 | Product Website for Soil Water Content 11 | SandboxData: | 12 | Discover samples of Soil Water Content, free to all active Planet users and Sentinel Hub users with a paid subscription or a Trial account. Sandbox Data for Soil Water Content 13 | Image: soil-water-content/soil-water-content.png 14 | Resolution: 100m and 1000km 15 | GeographicalCoverage: Global 16 | TemporalAvailability: 1000 m (2002 - present), 100 m (2017 - present) 17 | UpdateFrequency: 137-365 observations per year 18 | BandInformation: Information about bands and data 19 | Contact: Sentinel Hub Forum on Planet Commmunity 20 | Provider: Planet 21 | ManagedBy: "[Planet](https://www.planet.com/)" 22 | Tags: 23 | - commercial data 24 | - satellite imagery 25 | - planetary variables 26 | - agriculture 27 | - drought 28 | - sandbox data 29 | License: License 30 | Resources: 31 | - EndPoint: services.sentinel-hub.com 32 | Type: BYOC collection 33 | Notes: Contains the data purchased by individual user. [Explore sample CC-BY-NC sandbox data here](https://docs.planet.com/data/planetary-variables/soil-water-content/sandbox/) 34 | CustomScripts: 35 | Title: Collection of Soil Water Content custom scripts 36 | URL: https://custom-scripts.sentinel-hub.com/custom-scripts/planetary-variables/soil-water-content/ 37 | 38 | 39 | RegistryEntryAdded: "2024-01-08" 40 | RegistryEntryLastModified: "2024-05-10" 41 | -------------------------------------------------------------------------------- /collections/soil-water-content/SWC_AUS.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/soil-water-content/SWC_AUS.png -------------------------------------------------------------------------------- /collections/soil-water-content/SWC_FRA.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/soil-water-content/SWC_FRA.png -------------------------------------------------------------------------------- /collections/soil-water-content/SWC_USA.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/soil-water-content/SWC_USA.png -------------------------------------------------------------------------------- /collections/soil-water-content/open-data.md: -------------------------------------------------------------------------------- 1 | # Soil Water Content 2 | 3 | ## Short Description 4 | [Soil Water Content](https://www.planet.com/products/planetary-variables/) is the measure of the amount of water present in a unit volume of soil. It is typically expressed as a percentage and represents the ratio of the volume of water to the total volume of the soil. This measurement is crucial for understanding the water status of the soil, providing insights into factors like drought monitoring, soil health, and hydrological processes. The Soil Water Content Planetary Variable provides near-daily measurements of soil water content data with spatial resolution of 100 m and 1000 m. It is unhindered by clouds and has a long and consistent data record of more than 20 years, eliminating the need for maintaining large networks of physical sensors. 5 | 6 | A collection of Soil Water Content for a limited area and time of interest is available with the CC-BY-SA license. 7 | 8 | ## Collections 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | 29 |
    Source IDCollection IDTime Range
    SWC-SMAP-L_V2.0_100BYOC-d1581c49-c956-4edf-ab09-34f48a677aea2019-01-01 to 2022-12-31
    SWC-SMAP-L_V5.0_1000BYOC-c03b6ed1-9255-47ac-9510-4f140d3260f32019-01-01 to 2022-12-31
    30 | 31 | ### Open Data Areas 32 | To access data over your own areas and times of interest, [contact Planet](https://www.planet.com/contact-sales/#contact-sales). 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 | 41 | 42 | 43 | 44 | 45 | 46 | 47 | 48 | 49 | 50 | 51 | 52 | 53 | 54 | 55 | 56 | 57 | 58 | 59 |
    NameGeoJSON
    Nebraska, United States{"type":"Polygon","coordinates":[[[-96.67125913632235,40.95162566686232],[-96.67503530118803,40.84371453657603],[-96.67881146605373,40.73562741668371],[-96.39488641416239,40.729564890366404],[-96.39064956312542,40.83762892304856],[-96.38641271208847,40.94551707893859],[-96.67125913632235,40.95162566686232]]]}
    Madhya Pradesh, India{"type":"Polygon","coordinates":[[[77.32646679000004,22.404910741000037],[77.43339085700006,22.403117055000052],[77.43657419300007,22.592880011000034],[77.32965012600005,22.594673697000076],[77.32646679000004,22.404910741000037]]]}
    Hanover, Germany{"type":"Polygon","coordinates":[[[9.872932,52.252607],[9.872932,52.440107],[10.034981,52.440107],[10.034981,52.252607],[9.872932,52.252607]]]}
    Río Negro Department, Uruguay{"type":"Polygon","coordinates":[[[-57.85901538999997,-32.71934139299998],[-57.741644151999935,-32.720309191999945],[-57.74008043499998,-32.53066719499998],[-57.85745167399995,-32.529699395999955],[-57.85901538999997,-32.71934139299998]]]}
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The product available here is the [Water Bodies 100m Version 1](https://land.copernicus.eu/global/products/wb) collection which is derived from Sentinel-2 level 1C data, starting from October 2020 after the end of the PROBA-V mission and is delivered as a monthly composite product at 100m resolution. 5 | 6 | The Water Bodies product contain one main Water Bodies detection layer (WB) and one Quality layer (QUAL) that provides information on the seasonal dynamics of the detected water bodies. Water Bodies detection layer (WB) shows water bodies detected using the Modified Normalized Difference Water Index [(MNDWI)](https://en.wikipedia.org/wiki/Normalized_difference_water_index) derived from Sentinel-2 Level 1C data. The Quality layer (QUAL) is generated from water body occurrence statistics computed from previous monthly Water Bodies products.The occurrence statistics is ranked from low occurrence to permanent occurrence. 7 | 8 | More information about the data can be obtained from the [Water Bodies product](https://land.copernicus.eu/global/products/wb) page. 9 | 10 | ## Band information 11 | Water Bodies product contain 2 bands (WB and QUAL) and are described in Table 1 below. 12 | 13 | **Table 1: Bands** 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | 36 | 37 | 38 | 39 | 40 | 41 | 55 | 56 | 57 |
    NameUnitsValuesDescription
    WB DN 70 Main Water Bodies detection layer showing water pixels and non-water pixels 29 |
      30 |
    • 0 = Sea
      • 31 |
    • 70 = Water
      • 32 |
    • 251 = No data
      • 33 |
    • 255 = No water
      • 34 |
    35 |
    QUAL DN 71 - 76 Quality layer which gives information on water bodies occurrence 42 |
      43 |
    • 0 = Sea
      • 44 |
    • 71 = Very low occurence
      • 45 |
    • 72 = Low occurence
      • 46 |
    • 73 = Medium occurence
      • 47 |
    • 74 = High occurence
      • 48 |
    • 75 = Very high occurence
      • 49 |
    • 76 = Permanent occurence
      • 50 |
    • 251 = No data
      • 51 |
    • 252 = Cloud
      • 52 |
    • 255 = Not water
      • 53 |
    54 |
    58 | 59 | ## More information 60 | - [Data Source](https://land.copernicus.vgt.vito.be/PDF/portal/Application.html#Browse;Root=514888;Collection=1000152;Time=NORMAL,NORMAL,-1,,,-1,,) 61 | - [Product User Manual](https://land.copernicus.eu/global/sites/cgls.vito.be/files/products/CGLOPS2_PUM_WB100m_V1_I1.10.pdf) 62 | 63 | Water bodies map Baikal lake 64 |
    65 | 66 | *October 2020 monthly composite map showing surface water body extent around Russia's largest freshwater lake Baikal visualised in EO browser* 67 | 68 | Water occurrence map lake Bakhtegan and Tashk, Iran 69 |
    70 | 71 | *December 2020 water body occurrence on Iran's second largest salt lake Bakhtegan and lake Tashk visualised in EO browser* 72 | -------------------------------------------------------------------------------- /collections/water-bodies/baikal-water.PNG: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/water-bodies/baikal-water.PNG -------------------------------------------------------------------------------- /collections/water-bodies/water-bodies.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/water-bodies/water-bodies.png -------------------------------------------------------------------------------- /collections/worldcover.yaml: -------------------------------------------------------------------------------- 1 | Name: ESA WorldCover 2 | Description: | 3 | The European Space Agency (ESA) WorldCover is a global land cover map with 11 different land cover classes produced at 10m resolution based on combination of both Sentinel-1 and Sentinel-2 data. 4 | In areas where Sentinel-2 images are covered by clouds for an extended period of time, Sentinel-1 data then provides complimentary information on the structural 5 | characteristics of the observed land cover. Therefore, the combination of Sentinel-1 and Sentinel-2 data makes it possible to update the land cover map almost in real time. 6 | WorldCover Map was first produced for 2020 using v100 of the algorithm and later for 2021 with v200 algorithm. Due to the different algorithm versions, it should be noted that changes between WorldCover map 2020 and WorldCover map 2021 are a result of both actual changes in land cover and in the used algorithm. WorldCover map is provided as part of the 5th Earth Observation Envelope Programme (EOEP-5). It provides global coverage of valuable information for applications such as biodiversity, food security, carbon assessment and climate modelling. 7 | More information can be found on the [WorldCover website](https://esa-worldcover.org/en) and the [2020 v100 Product user Manual](https://esa-worldcover.s3.eu-central-1.amazonaws.com/v100/2020/docs/WorldCover_PUM_V1.0.pdf) and [2021 v200 Product user Manual](https://esa-worldcover.s3.eu-central-1.amazonaws.com/v200/2021/docs/WorldCover_PUM_V2.0.pdf) 8 | AdditionalInfoExternal: 9 | Title: Additional info 10 | Path: worldcover/README.MD 11 | Image: worldcover/thumbnail.png 12 | ViewOnEOBrowser: "[EO Browser](https://sentinelshare.page.link/hjyS)" 13 | Resolution: 10m 14 | GeographicalCoverage: Global land area 15 | TemporalAvailability: "2020, 2021" 16 | UpdateFrequency: Annually 17 | BandInformation: 18 | Table: 19 | Columns: 20 | - Name: Name 21 | Title: Name 22 | - Name: Description 23 | Title: Description 24 | Rows: 25 | - Name: Map 26 | Description: Main discrete classification according to FAO LCCS scheme, 11 land cover classes. 27 | Contact: | 28 | - VITO Remote Sensing 29 | - Sentinel Hub Forum on Planet Commmunity 30 | Provider: "[European Space Agency](https://esa-worldcover.org/en)" 31 | ManagedBy: "[Sentinel Hub](https://www.sentinel-hub.com/)" 32 | Tags: 33 | - land cover 34 | - agriculture 35 | - biodiversity 36 | - worldcover 37 | - derived data 38 | - open data 39 | License: "[Creative Commons Attribution 4.0 International License](https://creativecommons.org/licenses/by/4.0/), read more details on attribution and citation [here](https://esa-worldcover.org/en/data-access)" 40 | Resources: 41 | - EndPoint: services.sentinel-hub.com 42 | Type: byoc-0b940c63-45dd-4e6b-8019-c3660b81b884 43 | CollectionId: 0b940c63-45dd-4e6b-8019-c3660b81b884 44 | CustomScripts: 45 | Title: Custom scripts for other collections 46 | URL: https://custom-scripts.sentinel-hub.com/#other_collections 47 | RegistryEntryAdded: "2021-10-20" 48 | RegistryEntryLastModified: "2024-05-10" 49 | -------------------------------------------------------------------------------- /collections/worldcover/README.MD: -------------------------------------------------------------------------------- 1 | # WorldCover 2 | 3 | ## Short description 4 | The European Space Agency (ESA) WorldCover is a global land cover map with 11 different land cover classes produced at 10m resolution based on combination of both Sentinel-1 and Sentinel-2 data. In areas where Sentinel-2 images are covered by clouds for an extended period of time, Sentinel-1 data then provides complimentary information on the structural characteristics of the observed land cover. Therefore, the combination of Sentinel-1 and Sentinel-2 data makes it possible to update the land cover map almost in real time. 5 | 6 | WorldCover Map was first produced for 2020 using v100 of the algorithm and later for 2021 with v200 algorithm. Due to the different algorithm versions, it should be noted that changes between WorldCover map 2020 and WorldCover map 2021 are a result of both actual changes in land cover and in the used algorithm. WorldCover map is provided as part of the 5th Earth Observation Envelope Programme (EOEP-5). It provides global coverage of valuable information for applications such as biodiversity, food security, carbon assessment and climate modelling. 7 | 8 | More information can be found on the [WorldCover website](https://esa-worldcover.org/en) and the [2020 v100 Product user Manual](https://esa-worldcover.s3.eu-central-1.amazonaws.com/v100/2020/docs/WorldCover_PUM_V1.0.pdf) and [2021 v200 Product user Manual](https://esa-worldcover.s3.eu-central-1.amazonaws.com/v200/2021/docs/WorldCover_PUM_V2.0.pdf) 9 | 10 | ## Band information 11 | WorldCover product has 1 band named `Map`. The values of this band are described below. 12 | 13 | ### WorldCover Map classes description 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | 29 | 30 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 | 41 | 42 | 43 | 44 | 45 | 46 | 47 | 48 | 49 | 50 | 51 | 52 | 53 | 54 | 55 | 56 | 57 | 58 | 59 | 60 | 61 | 62 | 63 | 64 | 65 | 66 | 67 | 68 | 69 | 70 | 71 | 72 | 73 | 74 | 75 | 76 | 77 | 78 | 79 | 80 | 81 | 82 | 83 | 84 | 85 | 86 | 87 | 88 | 89 | 90 | 91 | 92 | 93 | 94 | 95 | 96 | 97 | 98 |
    ValueColorColor CodeClass Name
    10 0x006400 Tree cover
    200xffbb22 Shrubland
    300xffff4c Grassland
    400xf096ff Cropland
    500xfa0000 Built up
    60 0xb4b4b4 Bare /sparse vegetation
    700xf0f0f0 Snow and Ice
    800x0064c8 Permanent water bodies
    900x0096a0 Herbaceous wetland
    950x00cf75 Mangroves
    1000xfae6a0 Moss and lichen
    0 No data
    99 | 100 | ## More information 101 | 102 | ### Representative Images 103 | 104 | WorldCover South Romania 105 | 106 | *WorldCover 2020, river Olt, South of Romania visualised in EO Browser.* 107 | 108 |
    109 | WorldCover Amazonas Brazil 110 | 111 | *WorldCover 2020, Manaus Amazonas Brazil visualised in EO Browser* 112 | -------------------------------------------------------------------------------- /collections/worldcover/manaus_brazil.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/worldcover/manaus_brazil.png -------------------------------------------------------------------------------- /collections/worldcover/south_romania.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/worldcover/south_romania.png -------------------------------------------------------------------------------- /collections/worldcover/thumbnail.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/worldcover/thumbnail.png -------------------------------------------------------------------------------- /collections/worldview-geoeye.yaml: -------------------------------------------------------------------------------- 1 | Name: WorldView (+ GeoEye ) 2 | Description: | 3 | [Maxar Technologies](https://www.maxar.com/) offers multi-spectral, high resolution, commercial satellite imagery acquired 4 | by currently four on-orbit and three retired [constellation of satellites](https://www.maxar.com/constellation) 5 | namely WorldView, GeoEye, QuickBird and IKONOS. 6 | Sentinel Hub offers a possibility to purchase, order and access Worldview and Geoeye satellite imagery ordered through [European Space Imaging](https://docs.sentinel-hub.com/api/latest/static/files/data/maxar/world-view/resources/brochures/EUSI_Company_Brochure.pdf). 7 | The data available for purchase through Sentinel Hub are GeoEye-1 (GE01), WorldView-2 (WV02), WorldView-3 (WV03) and WorldView-4 (WV04). 8 | WorldView-4 data available for purchase is the imagery archive acquired from November 2016 to January 2019 while the satellite was operational. 9 | The rest of the constellation offers both, imagery archive available since 2009 and a tasking capability to acquire images systematically over an area of interest. 10 | The archived images are available sporadically over an area of interest since images are in general not acquired systematically. 11 | Sentinel Hub provides images in Top of the atmosphere (TOA) reflectance. 12 | Documentation: "[here](https://docs.sentinel-hub.com/api/latest/data/maxar/world-view/)" 13 | Image: worldview-geoeye/worldview-geoeye.png 14 | Resolution: 0.5 m for panchromatic band and 2 m for multispectral bands. 15 | GeographicalCoverage: Land surface area ([more info](https://www.maxar.com/constellation)) 16 | TemporalAvailability: 2009 - ongoing 17 | UpdateFrequency: data is not acquired systematically, data acquisition is tasked 18 | BandInformation: Information about [bands and data](https://docs.sentinel-hub.com/api/latest/data/maxar/world-view/#available-bands-and-data) 19 | Contact: Sentinel Hub Forum on Planet Commmunity 20 | Provider: "[Maxar](https://www.maxar.com/)" 21 | ManagedBy: "[European Space Imaging](https://www.euspaceimaging.com/)" 22 | Tags: 23 | - commercial data 24 | - multi spectral imagery 25 | - high resolution imagery 26 | - maritime monitoring 27 | - defense 28 | - disaster response 29 | - mapping 30 | License: | 31 | - Sentinel Hub Terms of Use. 32 | - Maxar Internal use License. 33 | Resources: 34 | - EndPoint: services.sentinel-hub.com 35 | Type: BYOC collection 36 | Notes: Contains the data purchased by individual user 37 | 38 | RegistryEntryAdded: "2021-04-17" 39 | RegistryEntryLastModified: "2024-05-10" 40 | -------------------------------------------------------------------------------- /collections/worldview-geoeye/worldview-geoeye.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/sentinel-hub/collections/ccf2956377d866966cd683879441e2dea8aa7317/collections/worldview-geoeye/worldview-geoeye.png -------------------------------------------------------------------------------- /package.json: -------------------------------------------------------------------------------- 1 | { 2 | "name": "open-data-registry-browser", 3 | "version": "0.0.1", 4 | "description": "Browser for https://github.com/sentinel-hub/collections", 5 | "main": "gulpfile.js", 6 | "scripts": { 7 | "build": "./node_modules/gulp-cli/bin/gulp.js", 8 | "serve": "./node_modules/gulp-cli/bin/gulp.js serve" 9 | }, 10 | "author": "Joe Flasher", 11 | "license": "Apache-2.0", 12 | "private": false, 13 | "repository": "https://github.com/sentinel-hub/collections", 14 | "devDependencies": { 15 | "browser-sync": "^2.26.14", 16 | "del": "^3.0.0", 17 | "gulp": "^4.0.0", 18 | "gulp-cli": "^2.2.0", 19 | "gulp-flatmap": "^1.0.2", 20 | "gulp-hb": "^8.0.0", 21 | "gulp-rename": "^1.4.0", 22 | "gulp-yaml": "^2.0.4", 23 | "handlebars": "^4.3.0", 24 | "jest": "^26.6.3", 25 | "lodash": "^4.17.19", 26 | "marked": "^0.8.0", 27 | "natives": "^1.1.6", 28 | "object-path": ">=0.11.5", 29 | "require-dir": "^0.3.2", 30 | "yaml": "^1.4.0" 31 | }, 32 | "dependencies": { 33 | "bootstrap": "3.4.1", 34 | "ndjson": "^1.5.0" 35 | } 36 | } 37 | --------------------------------------------------------------------------------