├── .gitattributes ├── .ipynb_checkpoints └── Youtube Python Geopandas-checkpoint.ipynb ├── README.md ├── Youtube Python Geopandas.ipynb ├── cikti ├── deneme-haritasi.png ├── iller2.cpg ├── iller2.dbf ├── iller2.prj ├── iller2.shp └── iller2.shx └── data ├── gadm36_TUR_1.zip ├── gadm36_TUR_shp.zip ├── ne_10m_airports.zip ├── ne_10m_populated_places.zip ├── ne_10m_railroads.zip ├── ne_10m_rivers_lake_centerlines.zip ├── ne_110m_admin_0_countries.zip ├── tr_iller ├── gadm36_TUR_1.cpg ├── gadm36_TUR_1.dbf ├── gadm36_TUR_1.prj ├── gadm36_TUR_1.shp ├── gadm36_TUR_1.shx └── gadm36_TUR_1.zip └── veriseti.xlsx /.gitattributes: -------------------------------------------------------------------------------- 1 | # Auto detect text files and perform LF normalization 2 | * text=auto 3 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | ## Python ile Mekansal Veri İşlemeye Giriş 2 | 3 | * Anaconda Kurulum: [İndir](https://www.anaconda.com/products/individual) 4 | * Kullandığımız Kütüphaneler: Geopandas, Numpy, Pandas, Shapely, Matplotlib 5 | * Veri Kaynaklarımız: http://www.naturalearthdata.com/ , http://gadm.org 6 | * Bilgisayarınızda github yüklü değil ise sağ üstteki clone or download linki ile dosyaları ve Jupyter Notebook dosyamızı bilgisayarınıza indirebilirsiniz. 7 | 8 | ## Videolar 9 | 10 | * [Mekansal Python 1 - Geopandas, Jupyter Notebook, Veri Okuma, Alan, Tampon Analizi](https://www.youtube.com/watch?v=NOMWTHSrlvI) 11 | * [Mekansal Python 2 - Nokta, Çizgi, Alan Verileri, Koordinat Sistemleri, Görselleştirme](https://www.youtube.com/watch?v=JX9S7tPnrzQ) 12 | * [Mekansal Python 3 - Mekansal Operasyonlar](https://www.youtube.com/watch?v=r2PfCK26ZL8) 13 | * [Mekansal Python 4 - Mekansal Operasyonlar, Veri Birleştirme (Excel ile](https://www.youtube.com/watch?v=O9NrAiDGxhs) 14 | * [Mekansal Python 5 - Görselleştirme, Harita Yapımı](https://www.youtube.com/watch?v=gofAu-jHkEw) 15 | 16 | ## Önemli Mekansal Python Kütüphaneleri 17 | 18 | * [Cartopy](http://scitools.org.uk/cartopy/) - Mekansal veri görselleştirme ve kartografya araçları. 19 | * [Fiona](http://toblerity.org/fiona/) - Mekansal veri formatlarını okuma ve yazma için. 20 | * [folium](https://github.com/python-visualization/folium) - Python için leaflet ile haritalar 21 | * [GDAL](https://anaconda.org/conda-forge/gdal) - The Geospatial Data Abstraction Library, Birçok farklı raster ve vektör veri formatını okumak ve yazmak için birebir. 22 | * [geojsonio](https://github.com/jwass/geojsonio.py) - GeoJSON verilerini Python içerisinde geojson.io'da görüntüleme. 23 | * [GeoPandas](https://github.com/geopandas/geopandas) - Coğrafi veri işleme için Python araçları. 24 | * [GIPPY](https://github.com/gipit/gippy) - Python için mekansal görüntü işleme kütüphanesi. 25 | * [PyProj](https://github.com/jswhit/pyproj) - Projeksiyon dönüşümleri için. 26 | * [PySAL](https://pysal.org/pysal/) - Mekansal veri analizleri için gelişmiş bir araç (patio-temporal data analysis, hot-spots, spatial clusters). 27 | * [PyShp](https://github.com/GeospatialPython/pyshp) - Shapefile okuma ve yazma. 28 | * [rasterio](https://github.com/mapbox/rasterio) - Raster veri okuma ve yazma. 29 | * [rasterstats](https://github.com/perrygeo/python-rasterstats/) - Raster verilerden vektör geometriler aracılığıyla veri özetleme. 30 | * [rio-cogeo](https://github.com/mapbox/rio-cogeo) - CloudOptimized GeoTIFF veri üretmek için. 31 | * [rio-color](https://github.com/mapbox/rio-color) - Raster veriler için temel renk düzenleme işlemleri. 32 | * [rio-hist](https://github.com/mapbox/rio-hist) - Histogram eşitleme. 33 | * [Rtree](http://toblerity.org/rtree/) - Mekansal veri sorgulamaları için. 34 | * [sentinelhub](https://github.com/sentinel-hub/sentinelhub-py) - Sentinel Hub servislerinden uydu görüntüsü indirme ve işleme 35 | * [sentinelsat](https://github.com/sentinelsat/sentinelsat) - Sentinel uydu görüntülerini arama ve indirme için. 36 | * [Shapely](https://pypi.python.org/pypi/Shapely) - Geometrik operasyonlar ve analizler için. 37 | * [srtm.py](https://github.com/tkrajina/srtm.py) - Python ile SRTM sayısal yükseklik verilerine verilerine erişim. 38 | * [PyDelaunay](https://github.com/bennycheung/PyDelaunay) - Delaunay üçgenlemesi 39 | * [zonalstatistics](https://github.com/shakasom/zonalstatistics) - Bölgesel istatistik hesapları (Rasterio&Geopandas) 40 | 41 | -------------------------------------------------------------------------------- /cikti/deneme-haritasi.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kalkan/mekansal-python/b283fd443a8424ca1a4d778f831e016e30b54481/cikti/deneme-haritasi.png -------------------------------------------------------------------------------- /cikti/iller2.cpg: 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UTF-8 -------------------------------------------------------------------------------- /data/tr_iller/gadm36_TUR_1.dbf: -------------------------------------------------------------------------------- 1 | xQaaNAME_1CPalanN Adana 15834933319.992 Adiyaman 7420536516.397 Afyon 14747426454.216 Agri 10300348515.712 Aksaray 7630818167.085 Amasya 6212560394.584 Ankara 25749278960.278 Antalya 21166556552.685 Ardahan 4786743312.765 Artvin 7769141704.397 Aydin 8006358475.827 Balikesir 14713930609.366 Bartin 2584955299.976 Batman 4345458764.158 Bayburt 3391599652.926 Bilecik 4646174088.159 Bingol 8133829140.261 Bitlis 8667363596.321 Bolu 8269607153.122 Burdur 7255279366.153 Bursa 10863190072.422 Canakkale 9777290636.736 Cankiri 7920691050.105 Corum 12312819263.034 Denizli 10894620729.270 Diyarbakir 14811416562.538 Duzce 2388462237.647 Edirne 6126924812.387 Elazig 9285808875.069 Erzincan 11540812976.843 Erzurum 24352206169.709 Eskisehir 14058937015.592 Gaziantep 7151379453.315 Giresun 6808588934.467 Gumushane 6614298034.033 Hakkari 6187119780.178 Hatay 5786086281.414 Igdir 3929370351.720 Isparta 8878881063.775 Istanbul 4756670850.483 Izmir 12368830680.108 Maras 14552764413.990 Karabuk 3316059596.625 Karaman 8340107063.615 Kars 10349896323.591 Kastamonu 13467912089.797 Kayseri 15940256779.472 Kilis 1424244322.788 Kirikkale 4674267195.176 Kirklareli 6358588212.918 Kirsehir 6783710478.637 Kocaeli 4040179661.441 Konya 40920791514.508 Kutahya 12199876919.152 Malatya 11496588980.582 Manisa 13218911735.863 Mardin 10539198862.538 Mersin 15222174648.022 Mugla 12832573871.794 Mus 8130277713.139 Nevsehir 5138204118.649 Nigde 7188785360.238 Ordu 5912196540.250 Osmaniye 3073528450.118 Rize 3640938711.545 Sakarya 4699983283.989 Samsun 9521612173.433 Sanliurfa 19622648064.016 Siirt 4982120901.663 Sinop 6010605930.605 Sirnak 7882602529.728 Sivas 28351454128.645 Tekirdag 6610923732.921 Tokat 9838114670.901 Trabzon 5031905362.122 Tunceli 8048456038.556 Usak 4918731287.706 Van 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