├── .editorconfig ├── .gitignore ├── LICENSE ├── README.md ├── download.py ├── environment.yml ├── example.geojson ├── geom.py ├── grid.py ├── index.html ├── requirements.txt └── style.json /.editorconfig: -------------------------------------------------------------------------------- 1 | # EditorConfig is awesome: https://EditorConfig.org 2 | 3 | # top-most EditorConfig file 4 | root = true 5 | 6 | # Unix-style newlines with a newline ending every file 7 | [*] 8 | end_of_line = lf 9 | insert_final_newline = true 10 | trim_trailing_whitespace = true 11 | charset = utf-8 12 | indent_style = space 13 | indent_size = 4 14 | 15 | # Tab indentation (no size specified) 16 | [Makefile] 17 | indent_style = tab 18 | 19 | [*.js] 20 | indent_size = 2 21 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | .DS_Store 2 | gdal2tiles/ 3 | gdal2tiles.py 4 | data 5 | data/ 6 | paths.json 7 | paths.txt 8 | *.mbtiles 9 | 10 | # Byte-compiled / optimized / DLL files 11 | __pycache__/ 12 | *.py[cod] 13 | *$py.class 14 | 15 | # C extensions 16 | *.so 17 | 18 | # Distribution / packaging 19 | .Python 20 | build/ 21 | develop-eggs/ 22 | dist/ 23 | downloads/ 24 | eggs/ 25 | .eggs/ 26 | lib/ 27 | lib64/ 28 | parts/ 29 | sdist/ 30 | var/ 31 | wheels/ 32 | *.egg-info/ 33 | .installed.cfg 34 | *.egg 35 | MANIFEST 36 | 37 | # PyInstaller 38 | # Usually these files are written by a python script from a template 39 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 40 | *.manifest 41 | *.spec 42 | 43 | # Installer logs 44 | pip-log.txt 45 | pip-delete-this-directory.txt 46 | 47 | # Unit test / coverage reports 48 | htmlcov/ 49 | .tox/ 50 | .coverage 51 | .coverage.* 52 | .cache 53 | nosetests.xml 54 | coverage.xml 55 | *.cover 56 | .hypothesis/ 57 | .pytest_cache/ 58 | 59 | # Translations 60 | *.mo 61 | *.pot 62 | 63 | # Django stuff: 64 | *.log 65 | local_settings.py 66 | db.sqlite3 67 | 68 | # Flask stuff: 69 | instance/ 70 | .webassets-cache 71 | 72 | # Scrapy stuff: 73 | .scrapy 74 | 75 | # Sphinx documentation 76 | docs/_build/ 77 | 78 | # PyBuilder 79 | target/ 80 | 81 | # Jupyter Notebook 82 | .ipynb_checkpoints 83 | 84 | # pyenv 85 | .python-version 86 | 87 | # celery beat schedule file 88 | celerybeat-schedule 89 | 90 | # SageMath parsed files 91 | *.sage.py 92 | 93 | # Environments 94 | .env 95 | .venv 96 | env/ 97 | venv/ 98 | ENV/ 99 | env.bak/ 100 | venv.bak/ 101 | 102 | # Spyder project settings 103 | .spyderproject 104 | .spyproject 105 | 106 | # Rope project settings 107 | .ropeproject 108 | 109 | # mkdocs documentation 110 | /site 111 | 112 | # mypy 113 | .mypy_cache/ 114 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2019 National Scenic Trails Guide 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # NAIP 2 | 3 | Generate high-resolution tiled imagery from USDA NAIP data 4 | 5 | ## Overview 6 | 7 | I use [OpenMapTiles](https://github.com/openmaptiles/openmaptiles) to create 8 | self-hosted vector map tiles. However, that doesn't provide aerial imagery. 9 | 10 | ### Source data 11 | 12 | The US Department of Agriculture (USDA) captures high-resolution aerial imagery 13 | for the continental US. The USGS's web portal allows for easy downloading of 14 | NAIP imagery. 15 | 16 | According to the [NAIP 17 | website](https://www.fsa.usda.gov/programs-and-services/aerial-photography/imagery-programs/naip-imagery/): 18 | 19 | > NAIP imagery is acquired at a one-meter ground sample distance (GSD) with a 20 | > horizontal accuracy that matches within six meters of photo-identifiable 21 | > ground control points, which are used during image inspection. 22 | 23 | 24 | ### Integration with `style.json` 25 | 26 | The style JSON spec tells Mapbox GL how to style your map. Add the raster imagery 27 | tiles as a source to overlay them with the other sources. 28 | 29 | Within `sources`, each object key defines the name by which the later parts of 30 | `style.json` should refer to the layer. Note the difference between a normal 31 | raster layer and the terrain RGB layer. 32 | 33 | ```json 34 | "sources": { 35 | "openmaptiles": { 36 | "type": "vector", 37 | "url": "https://api.maptiler.com/tiles/v3/tiles.json?key={key}" 38 | }, 39 | "naip": { 40 | "type": "raster", 41 | "url": "https://example.com/url/to/tile.json", 42 | "tileSize": 512 43 | } 44 | } 45 | ``` 46 | 47 | Where the `tile.json` for a raster layer should be something like: 48 | 49 | ```json 50 | { 51 | "attribution": "© USGS", 52 | "description": "NAIP Imagery", 53 | "format": "png", 54 | "id": "naip", 55 | "maxzoom": 15, 56 | "minzoom": 11, 57 | "name": "naip", 58 | "scheme": "tms", 59 | "tiles": ["https://example.com/url/to/tiles/{z}/{x}/{y}.png"], 60 | "version": "2.2.0" 61 | } 62 | ``` 63 | 64 | Later in the style JSON, refer to the raster to style it. This example shows the 65 | raster layer between zooms 11 and 15 (inclusive), and sets the opacity to 0.2 at 66 | zoom 11 and 1 at zoom 15, with a gradual ramp in between. 67 | ```json 68 | { 69 | "id": "naip", 70 | "type": "raster", 71 | "source": "naip", 72 | "minzoom": 11, 73 | "maxzoom": 15, 74 | "paint": { 75 | "raster-opacity": { 76 | "base": 1.5, 77 | "stops": [ 78 | [ 79 | 11, 80 | 0.2 81 | ], 82 | [ 83 | 15, 84 | 1 85 | ] 86 | ] 87 | } 88 | } 89 | } 90 | ``` 91 | 92 | ## Installation 93 | 94 | Clone the repository: 95 | 96 | ``` 97 | git clone https://github.com/nst-guide/naip 98 | cd naip 99 | ``` 100 | 101 | This is written to work with Python >= 3.6. To install dependencies: 102 | 103 | ``` 104 | pip install -r requirements.txt 105 | ``` 106 | 107 | This also has dependencies on some C/C++ libraries. If you have issues 108 | installing with pip, try Conda: 109 | ``` 110 | conda env create -f environment.yml 111 | source activate naip 112 | ``` 113 | 114 | ## Code Overview 115 | 116 | #### `download.py` 117 | 118 | Downloads USGS elevation data for a given bounding box. 119 | 120 | ``` 121 | > python download.py --help 122 | Usage: download.py [OPTIONS] [FILE]... 123 | 124 | Download raw NAIP imagery for given geometry 125 | 126 | Options: 127 | --bbox TEXT Bounding box to download data for. Should be 128 | west, south, east, north. 129 | -b, --buffer-dist FLOAT Buffer to use around provided geometry. Only 130 | used with --file argument. 131 | --buffer-unit [mile|meter|kilometer] 132 | Units for buffer. [default: mile] 133 | --buffer-projection INTEGER EPSG code for projection used when creating 134 | buffer. Coordinates must be in meters. 135 | [default: 3488] 136 | --overwrite Re-download and overwrite existing files. 137 | --help Show this message and exit. 138 | ``` 139 | 140 | This script calls the [National Map 141 | API](https://viewer.nationalmap.gov/tnmaccess/api/index) and finds all the 142 | 3.75'x3.75' NAIP imagery files that intersect the given bounding box or 143 | geometry. By default, it only downloads the most recent image, if more than one 144 | exist. 145 | 146 | The script then downloads each of these files to `data/raw/`. By default, 147 | it doesn't re-download and overwrite a file that already exists. If you wish to 148 | overwrite an existing file, use `--overwrite`. 149 | 150 | #### `gdal` 151 | 152 | Use `gdalbuildvrt` to generate a virtual dataset of all image tiles and 153 | `gdal2tiles` to cut the output raster into map tiles. 154 | 155 | `gdal2tiles.py` options: 156 | 157 | - `--processes`: number of individual processes to use for generating the base 158 | tiles. Change this to a suitable number for your computer. 159 | - I also use my forked copy of `gdal2tiles.py` in order to generate high-res retina tiles 160 | 161 | ## Usage 162 | 163 | First, download desired DEM tiles, unzip them, build a VRT (Virtual Dataset), 164 | and optionally download my fork of `gdal2tiles` which allows for creating 165 | 512x512 pngs. 166 | 167 | ```bash 168 | # Download for some geometry 169 | python download.py -b 2 example.geojson 170 | 171 | # Create virtual raster: 172 | # The -b flags take each of the RGB bands at full opacity. 173 | # The -addalpha sets areas with no source raster as transparent. 174 | # See https://github.com/nst-guide/naip/issues/1 175 | gdalbuildvrt -b 1 -b 2 -b 3 -addalpha data/naip.vrt data/raw/*.jp2 176 | 177 | # Download my fork of gdal2tiles.py 178 | # I use my own gdal2tiles.py fork for retina 2x 512x512 tiles 179 | git clone https://github.com/nst-guide/gdal2tiles 180 | cp gdal2tiles/gdal2tiles.py ./ 181 | 182 | # Generate tiled imagery 183 | # --exclude excludes transparent tiles from output tileset 184 | # You may want to set max zoom level 15 185 | ./gdal2tiles.py --processes 10 --exclude data/naip.vrt data/naip_tiles 186 | ``` 187 | 188 | ### Compression 189 | 190 | Running this for a .5 mile buffer for the entire Pacific Crest Trail, with 191 | 512x512 pixel tiles and a max zoom of 16 generated ~60GB of png files. Around 192 | ~45GB of these tiles are in just zoom level 16, and while I'll probably 193 | set a max zoom of 15 in the future, ~15GB is still more than I want to serve. 194 | 195 | Note that these CLI commands worked on macOS, and some might need different syntax on Linux. 196 | 197 | #### WebP 198 | 199 | **Note**: It appears from limited inspection that Mapbox GL JS shows WebP images 200 | slightly pixelated? See [#2](https://github.com/nst-guide/naip/issues/2). 201 | 202 | Google's webp format is a great compressor of png images. Running the `cwebp` 203 | cli (you can download from Google's site or through homebrew ) and setting the 204 | quality to 80/100 reduces file size by about 85% 205 | ``` 206 | > cwebp 10299.png -q 80 -o 10299.webp 207 | ``` 208 | 209 | By default this is _lossy_ compression. You can set `-lossless` if you'd like, 210 | but lossy is fine for my needs. 211 | 212 | The docs for the `-q` option say: 213 | 214 | > Specify the compression factor for RGB channels between 0 and 100. The default is 75. 215 | > 216 | > In case of lossy compression (default), a small factor produces a smaller file 217 | > with lower quality. Best quality is achieved by using a value of 100. 218 | > 219 | > In case of lossless compression (specified by the -lossless option), a small 220 | > factor enables faster compression speed, but produces a larger file. Maximum 221 | > compression is achieved by using a value of 100. 222 | 223 | I think this is really confusing because a higher `-q` value is less compressed 224 | when running lossy and more compressed when running lossless! 225 | 226 | To create a full hierarchy of webp images: 227 | ```bash 228 | cd data/naip_tiles 229 | for f in */*/*.png; do mkdir -p ../naip_tiles_webp/$(dirname $f); cwebp $f -q 80 -o ../naip_tiles_webp/$f ; done 230 | ``` 231 | 232 | Unfortunately, webp isn't supported everywhere, namely on older browsers and on 233 | all iOS browsers. 234 | 235 | #### Lossy PNG 236 | 237 | Because WebP images aren't supported on all devices, I also need to serve a PNG 238 | layer. Unlike the [terrain-rgb elevation 239 | layer](https://github.com/nst-guide/hillshade), for which lossy compression 240 | would erase all meaning of the encoded elevation values, for regular images 241 | lossy compression won't make much of a visual difference. 242 | 243 | From limited searching, the best open source, command line PNG compressor seems 244 | to be [`pngquant`](https://pngquant.org/). This creates PNG images that can be 245 | displayed on any device. You can install with `brew install pngquant`. 246 | 247 | In order to create a directory of compressed images: 248 | ```bash 249 | cd data/naip_tiles 250 | find . -name '*.png' -print0 | xargs -0 -P8 -L1 pngquant --ext -comp.png --quality=70-80 251 | ``` 252 | 253 | Setting quality to `70-80` appears to create files that are about 25% of the 254 | original size. 255 | 256 | I couldn't figure out an easy way to write the output png files to a new 257 | directory. By default they're written in the same directory as the original 258 | file, with an added extension. 259 | 260 | ```bash 261 | # in data/naip_tiles already 262 | mkdir ../naip_tiles_png 263 | # First move all tiles with extension -comp.png to the new directory 264 | # Take out --remove-source-files if you want to copy, not move the files 265 | # I use rsync because I couldn't figure out an easy way with `mv` to move while 266 | # keeping the directory structure. 267 | rsync -a --remove-source-files --include "*/" --include="*-comp.png" --exclude="*" . ../naip_tiles_png/ 268 | # Then rename all of the files, taking off the -comp suffix 269 | cd ../naip_tiles_png 270 | find . -type f -name "*-comp.png" -exec rename -s '-comp.png' '.png' {} + 271 | ``` 272 | 273 | When run on Halfmile's PCT track data with a .5 mile buffer (including 274 | alternates), the resulting data after pngquant compression has file sizes: 275 | ``` 276 | > du -csh * | sort -h 277 | ``` 278 | 279 | | Directory size | Zoom level | 280 | |----------------|------------| 281 | | 8.0K | 4 | 282 | | 20K | 5 | 283 | | 36K | 6 | 284 | | 108K | 7 | 285 | | 348K | 8 | 286 | | 1.2M | 9 | 287 | | 4.1M | 10 | 288 | | 15M | 11 | 289 | | 60M | 12 | 290 | | 240M | 13 | 291 | | 979M | 14 | 292 | | 3.8G | 15 | 293 | | 15G | 16 | 294 | | 20G | total | 295 | 296 | I'll probably serve up to zoom 15 through the web browser, and maybe up to zoom 297 | 14 for offline download. 298 | -------------------------------------------------------------------------------- /download.py: -------------------------------------------------------------------------------- 1 | import re 2 | from pathlib import Path 3 | from urllib.error import HTTPError 4 | from urllib.parse import urlparse 5 | from urllib.request import urlretrieve as _urlretrieve 6 | 7 | import click 8 | import geopandas as gpd 9 | import requests 10 | from dateutil.parser import parse as date_parse 11 | from shapely.geometry import box 12 | from tqdm import tqdm 13 | 14 | from grid import get_cells 15 | 16 | 17 | @click.command() 18 | @click.option( 19 | '--bbox', 20 | required=False, 21 | default=None, 22 | type=str, 23 | help='Bounding box to download data for. Should be west, south, east, north.' 24 | ) 25 | @click.option( 26 | '-b', 27 | '--buffer-dist', 28 | required=False, 29 | type=float, 30 | default=None, 31 | show_default=True, 32 | help='Buffer to use around provided geometry. Only used with --file argument.' 33 | ) 34 | @click.option( 35 | '--buffer-unit', 36 | required=False, 37 | show_default=True, 38 | type=click.Choice(['mile', 'meter', 'kilometer'], case_sensitive=False), 39 | default='mile', 40 | help='Units for buffer.') 41 | @click.option( 42 | '--buffer-projection', 43 | required=False, 44 | show_default=True, 45 | type=int, 46 | default=3488, 47 | help= 48 | 'EPSG code for projection used when creating buffer. Coordinates must be in meters.' 49 | ) 50 | @click.option( 51 | '--overwrite', 52 | is_flag=True, 53 | default=False, 54 | help="Re-download and overwrite existing files.") 55 | @click.argument( 56 | 'file', 57 | type=click.Path( 58 | exists=True, file_okay=True, dir_okay=False, resolve_path=True), 59 | nargs=-1) 60 | def main(bbox, file, buffer_dist, buffer_unit, buffer_projection, overwrite): 61 | """Download raw NAIP imagery for given geometry 62 | """ 63 | if (bbox is None) and (not file): 64 | raise ValueError('Either bbox or file must be provided') 65 | 66 | if (bbox is not None) and (file): 67 | raise ValueError("Both bbox and file can't be provided") 68 | 69 | geometries = None 70 | if bbox: 71 | bbox = tuple(map(float, re.split(r'[, ]+', bbox))) 72 | geometries = [box(*bbox)] 73 | 74 | if file: 75 | geometries = [] 76 | for f in file: 77 | gdf = gpd.read_file(f).to_crs(epsg=4326) 78 | 79 | # Create buffer if arg is provided 80 | if buffer_dist is not None: 81 | from geom import buffer 82 | gdf = buffer( 83 | gdf, 84 | distance=buffer_dist, 85 | unit=buffer_unit, 86 | epsg=buffer_projection) 87 | 88 | geometries.extend( 89 | list(get_cells(gdf.unary_union, cell_size=0.0625))) 90 | 91 | if geometries is None: 92 | raise ValueError('Error while computing geometries') 93 | 94 | print('Downloading NAIP imagery for geometries:') 95 | for geometry in geometries: 96 | print(geometry.bounds) 97 | 98 | download_dir = Path('data/raw') 99 | download_dir.mkdir(parents=True, exist_ok=True) 100 | local_paths = download_naip( 101 | geometries, directory=download_dir, overwrite=overwrite) 102 | with open('paths.txt', 'w') as f: 103 | f.writelines(_paths_to_str(local_paths)) 104 | 105 | 106 | def download_naip(geometries, directory, overwrite): 107 | """ 108 | Args: 109 | - geometries (list): list of bounding boxes (as shapely objects) 110 | - directory (pathlib.Path): directory to download files to 111 | - overwrite (bool): whether to re-download and overwrite existing files 112 | """ 113 | urls = [] 114 | for geometry in geometries: 115 | new_urls = get_urls(geometry.bounds) 116 | if new_urls is not None: 117 | urls.extend(new_urls) 118 | 119 | local_paths = [] 120 | counter = 1 121 | for url in urls: 122 | print(f'Downloading file {counter} of {len(urls)}') 123 | print(url) 124 | local_path = download_url(url, directory, overwrite=overwrite) 125 | if local_path is not None: 126 | local_paths.append(local_path) 127 | 128 | counter += 1 129 | 130 | return local_paths 131 | 132 | 133 | def get_urls(bbox): 134 | """ 135 | Args: 136 | - bbox (tuple): bounding box (west, south, east, north) 137 | - high_res (bool): If True, downloads high-res 1/3 arc-second DEM 138 | """ 139 | url = 'https://viewer.nationalmap.gov/tnmaccess/api/products' 140 | product = 'USDA National Agriculture Imagery Program (NAIP)' 141 | extent = '3.75 x 3.75 minute' 142 | fmt = 'JPEG2000' 143 | 144 | params = { 145 | 'datasets': product, 146 | 'bbox': ','.join(map(str, bbox)), 147 | 'outputFormat': 'JSON', 148 | 'version': 1, 149 | 'prodExtents': extent, 150 | 'prodFormats': fmt} 151 | 152 | res = requests.get(url, params=params) 153 | try: 154 | res = res.json() 155 | except: 156 | return None 157 | 158 | # If I don't need to page for more results, return 159 | if len(res['items']) == res['total']: 160 | return select_results(res) 161 | 162 | # Otherwise, need to page 163 | all_results = [*res['items']] 164 | n_retrieved = len(res['items']) 165 | n_total = res['total'] 166 | 167 | for offset in range(n_retrieved, n_total, n_retrieved): 168 | params['offset'] = offset 169 | res = requests.get(url, params=params).json() 170 | all_results.extend(res['items']) 171 | 172 | # Keep all results with best fit index >0 173 | return select_results(all_results) 174 | 175 | 176 | def select_results(results): 177 | """Select relevant images from results 178 | 179 | Selects most recent image for location, and results with positive fit index. 180 | """ 181 | # Select results with positive bestFitIndex 182 | results = [x for x in results['items'] if x['bestFitIndex'] > 0] 183 | 184 | # counter_dict schema: 185 | # counter_dict = { 186 | # bounds: { 187 | # 'dateCreated': date, 188 | # 'downloadURL' 189 | # } 190 | # } 191 | counter_dict = {} 192 | for result in results: 193 | bounds = result_to_bounds(result) 194 | 195 | # does something already exist with these bounds? 196 | existing = counter_dict.get(bounds) 197 | 198 | # If exists, check if newer 199 | if existing is not None: 200 | existing_date = existing['dateCreated'] 201 | this_date = date_parse(result['dateCreated']) 202 | if this_date < existing_date: 203 | continue 204 | 205 | # Doesn't exist yet or is newer, so add to dict 206 | counter_dict[bounds] = { 207 | 'dateCreated': date_parse(result['dateCreated']), 208 | 'downloadURL': result['downloadURL']} 209 | 210 | return [x['downloadURL'] for x in counter_dict.values()] 211 | 212 | 213 | def result_to_bounds(res_item): 214 | minx = str(res_item['boundingBox']['minX']) 215 | maxx = str(res_item['boundingBox']['maxX']) 216 | miny = str(res_item['boundingBox']['minY']) 217 | maxy = str(res_item['boundingBox']['maxY']) 218 | return ','.join((minx, miny, maxx, maxy)) 219 | 220 | 221 | def download_url(url, directory, overwrite=False): 222 | # Cache original download in self.raw_dir 223 | parsed_url = urlparse(url) 224 | filename = Path(parsed_url.path).name 225 | local_path = Path(directory) / filename 226 | if overwrite or (not local_path.exists()): 227 | try: 228 | urlretrieve(url, local_path) 229 | except HTTPError: 230 | print(f'File could not be downloaded:\n{url}') 231 | return None 232 | 233 | return local_path.resolve() 234 | 235 | 236 | def _paths_to_str(paths): 237 | return [str(path) for path in paths] 238 | 239 | 240 | class DownloadProgressBar(tqdm): 241 | def update_to(self, b=1, bsize=1, tsize=None): 242 | if tsize is not None: 243 | self.total = tsize 244 | self.update(b * bsize - self.n) 245 | 246 | 247 | def urlretrieve(url, output_path): 248 | with DownloadProgressBar(unit='B', unit_scale=True, miniters=1, 249 | desc=url.split('/')[-1]) as t: 250 | _urlretrieve(url, filename=output_path, reporthook=t.update_to) 251 | 252 | 253 | if __name__ == '__main__': 254 | main() 255 | -------------------------------------------------------------------------------- /environment.yml: -------------------------------------------------------------------------------- 1 | name: naip 2 | channels: 3 | - conda-forge 4 | dependencies: 5 | - click 6 | - dateutil 7 | - geopandas 8 | - numpy 9 | - pint 10 | - requests 11 | - shapely 12 | - tqdm 13 | -------------------------------------------------------------------------------- /example.geojson: -------------------------------------------------------------------------------- 1 | {"type": "FeatureCollection", "features": [{"type": "Feature", "geometry": {"type": "LineString", "coordinates": [[-116.466981, 32.589741, 889.15], [-116.467028, 32.589935, 886.93], [-116.467185, 32.590052, 883.79], [-116.46783, 32.590296, 876.62], [-116.467875, 32.590604, 874.0], [-116.467677, 32.591089, 870.3], [-116.467661, 32.591417, 870.32], [-116.467123, 32.591869, 864.45], [-116.467078, 32.593434, 856.32], [-116.466723, 32.594004, 854.01], [-116.466729, 32.595078, 845.65], [-116.46663, 32.595242, 844.88], [-116.466714, 32.595544, 841.19], [-116.466713, 32.597496, 822.88], [-116.466833, 32.597577, 822.54], [-116.467476, 32.597648, 822.21], [-116.467967, 32.597806, 823.44], [-116.468266, 32.597768, 823.81], [-116.468682, 32.597554, 824.87], [-116.468848, 32.597545, 825.76], [-116.46946, 32.59878, 819.85], [-116.46975, 32.599137, 818.54], [-116.469697, 32.599446, 816.49], [-116.469777, 32.599846, 815.06], [-116.469983, 32.600064, 814.1], [-116.470134, 32.600774, 811.36], [-116.470418, 32.600959, 814.93], [-116.470253, 32.601266, 814.3], [-116.470347, 32.601714, 810.71], [-116.470216, 32.601887, 809.07], [-116.47042, 32.602157, 810.52], [-116.470279, 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[-116.530218, 33.056922, 1017.35], [-116.530527, 33.056842, 1017.23], [-116.530841, 33.05652, 1016.84], [-116.530865, 33.056122, 1015.83], [-116.531176, 33.055919, 1010.29], [-116.531428, 33.055957, 1010.6], [-116.53192, 33.056483, 1007.89]]}, "properties": {"name": "Rodriguez Spring Road", "alternate": true}}, {"type": "Feature", "geometry": {"type": "LineString", "coordinates": [[-116.522256, 32.980348, 1522.92], [-116.5224, 32.980381, 1522.79], [-116.522505, 32.980308, 1524.81], [-116.522553, 32.980013, 1527.84], [-116.522673, 32.979915, 1527.21], [-116.522699, 32.979483, 1529.89], [-116.522884, 32.979224, 1528.88], [-116.523022, 32.979129, 1527.23], [-116.523244, 32.979104, 1524.31], [-116.523694, 32.979162, 1520.65], [-116.523801, 32.979053, 1521.23], [-116.523843, 32.978752, 1523.46], [-116.523977, 32.978699, 1523.29], [-116.524328, 32.978745, 1521.59], [-116.524539, 32.978639, 1522.56], [-116.524621, 32.978374, 1525.1], [-116.525033, 32.978001, 1528.31], [-116.525376, 32.977949, 1527.8], [-116.526081, 32.978008, 1525.39], [-116.526613, 32.977806, 1523.06], [-116.526923, 32.977881, 1522.65]]}, "properties": {"name": "Sunrise Trailhead Trail", "alternate": true}}]} -------------------------------------------------------------------------------- /geom.py: -------------------------------------------------------------------------------- 1 | import geopandas as gpd 2 | import pint 3 | 4 | ureg = pint.UnitRegistry() 5 | 6 | 7 | def buffer( 8 | gdf: gpd.GeoDataFrame, distance: float, unit: str, 9 | epsg=3488) -> gpd.GeoSeries: 10 | """Create buffer around GeoDataFrame 11 | 12 | Args: 13 | gdf: dataframe with geometry to take buffer around 14 | distance: distance for buffer 15 | unit: units for buffer distance, either ['mile', 'meter', 'kilometer'] 16 | epsg: local projection for creating buffer, should have meter projection 17 | 18 | Returns: 19 | GeoDataFrame with buffer polygon 20 | """ 21 | 22 | # Reproject to EPSG 3488 (meter accuracy) 23 | # https://epsg.io/3488 24 | gdf = gdf.to_crs(epsg=epsg) 25 | 26 | # Find buffer distance in meters 27 | unit_dict = { 28 | 'mile': ureg.mile, 29 | 'meter': ureg.meter, 30 | 'kilometer': ureg.kilometer, } 31 | pint_unit = unit_dict.get(unit) 32 | if pint_unit is None: 33 | raise ValueError(f'unit must be one of {list(unit_dict.keys())}') 34 | 35 | distance_m = (distance * pint_unit).to(ureg.meters).magnitude 36 | buffer = gdf.buffer(distance_m) 37 | 38 | # Reproject back to EPSG 4326 for saving 39 | buffer = buffer.to_crs(epsg=4326) 40 | 41 | return buffer 42 | -------------------------------------------------------------------------------- /grid.py: -------------------------------------------------------------------------------- 1 | """ 2 | Helpers for dealing with regularly spaced grids 3 | 4 | NOTE: this is taken and simplified from nst-guide/create-database/grid.py: 5 | https://github.com/nst-guide/create-database/blob/master/code/grid.py 6 | """ 7 | from math import ceil, floor 8 | 9 | import numpy as np 10 | from shapely.geometry import box 11 | 12 | 13 | def get_cells(geom, cell_size, offset=0): 14 | """ 15 | Args: 16 | - geom: geometry to check intersections with. Can either be a LineString or a Polygon 17 | - cell_size: size of cell, usually either 1, .125, or .1 (degrees) 18 | - offset: Non-zero when looking for centerpoints, i.e. for lightning 19 | strikes data where the labels are by the centerpoints of the 20 | cells, not the bordering lat/lons 21 | 22 | Returns: 23 | Iterable[polygon]: generator yielding polygons representing matching 24 | cells 25 | """ 26 | bounds = geom.bounds 27 | 28 | # Get whole-degree bounding box of `bounds` 29 | minx, miny, maxx, maxy = bounds 30 | minx, miny = floor(minx), floor(miny) 31 | maxx, maxy = ceil(maxx), ceil(maxy) 32 | 33 | # Get the lower left corner of each box 34 | ll_points = get_ll_points(minx, maxx, miny, maxy, offset, cell_size) 35 | 36 | # Get grid intersections 37 | return get_grid_intersections(geom, ll_points, cell_size) 38 | 39 | 40 | def get_ll_points(minx, maxx, miny, maxy, offset, cell_size): 41 | for x in np.arange(minx - offset, maxx + offset, cell_size): 42 | for y in np.arange(miny - offset, maxy + offset, cell_size): 43 | yield (x, y) 44 | 45 | 46 | def get_grid_intersections(geom, ll_points, cell_size): 47 | for ll_point in ll_points: 48 | ur_point = (ll_point[0] + cell_size, ll_point[1] + cell_size) 49 | bbox = box(*ll_point, *ur_point) 50 | if bbox.intersects(geom): 51 | yield bbox 52 | -------------------------------------------------------------------------------- /index.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | Contours 6 | 7 | 11 | 12 | 13 | 14 | 15 |
16 | 28 | 29 | 30 | -------------------------------------------------------------------------------- /requirements.txt: -------------------------------------------------------------------------------- 1 | click 2 | dateutil 3 | geopandas 4 | numpy 5 | pint 6 | requests 7 | shapely 8 | tqdm 9 | -------------------------------------------------------------------------------- /style.json: -------------------------------------------------------------------------------- 1 | { 2 | "version": 8, 3 | "name": "NAIP", 4 | "metadata": { 5 | "maputnik:renderer": "mbgljs" 6 | }, 7 | "sources": { 8 | "naip": { 9 | "minzoom": 4, 10 | "maxzoom": 16, 11 | "tileSize": 512, 12 | "tiles": [ 13 | "https://tiles.nst.guide/naip-png/{z}/{x}/{y}.png" 14 | ], 15 | "type": "raster", 16 | "scheme": "tms" 17 | } 18 | }, 19 | "sprite": "", 20 | "glyphs": "https://orangemug.github.io/font-glyphs/glyphs/{fontstack}/{range}.pbf", 21 | "layers": [ 22 | { 23 | "id": "naip", 24 | "type": "raster", 25 | "source": "naip", 26 | "minzoom": 4, 27 | "paint": { 28 | "raster-opacity": 1 29 | }, 30 | "layout": { 31 | "visibility": "visible" 32 | } 33 | } 34 | ], 35 | "id": "contours" 36 | } 37 | --------------------------------------------------------------------------------