November 2024
Intermediate to advanced
282 pages
7h 44m
French
Content preview from Python pour l'analyse des données géospatiales
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Chapitre 9. Exploration de la bibliothèque d'abstraction de données géospatiales (GDAL)
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Aucune discussion sur les plates-formes et les bibliothèques open source ne serait complète sans une présentation de la Geospatial Data Abstraction Library (GDAL), une ressource permettant de traiter efficacement les données géospatiales matricielles et vectorielles. Travailler avec des données matricielles et vectorielles nécessite un ensemble d'outils, et la GDAL fonctionne sous le capot de nombreux programmes que tu as utilisés dans ce livre, notamment ArcGIS, QGIS et Google Earth. Lorsque l'on se fie à la facilité de programmation d'une interface graphique, il est souvent facile d'oublier la complexité de la combinaison de divers types et formats de données afin de travailler efficacement avec un modèle de données unifié. C'est pourquoi GDAL est un outil important. Il simplifie le travail avec les données géospatiales dans un large éventail de formats et de systèmes de référence spatiale.
Dans ce chapitre, nous travaillerons avec des rasters et nous verrons comment utiliser l'IDE Spyder pour travailler avec GDAL, y compris comment changer la projection de la carte avec la fonction warp, travailler avec des bandes raster, transformer des fichiers et créer des masques binaires. Nous ferons également un rapide tour d'horizon de trois autres ressources utiles pour ...
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