Difference between revisions of "Digitizing in Python"
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Google Earth Engine |
Google Earth Engine |
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Google Colab or any other Python language system or notebooks. |
Google Colab or any other Python language system or notebooks. |
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Python libraries: <syntaxhighlight lang=" |
Python libraries: <syntaxhighlight lang="python"> |
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<syntaxhighlight lang="earthengine-api, geemap, rasterio, geopandas, shapely, matplotlib"> |
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==Setting up Colab and Google Earth Engine== |
==Setting up Colab and Google Earth Engine== |
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Revision as of 07:38, 17 December 2025
Contents
Purpose
The purpose of this tutorial is to automate the digitization of land cover features such as vegetation, waterbodies, and roads, using Sentinel-2 satellite imagery and Python-based geospatial tools.
Objective
Use Google Earth Engine (GEE) to acquire the satellite images for processing in python. Compute NDVI (vegetation), NDWI (water), NDBI (roads) indices. Export rasters to your Google Drive. Convert rasters to vectors. Visualize and colourize digitized features.
Software
Google Earth Engine Google Colab or any other Python language system or notebooks. Python libraries: <syntaxhighlight lang="python"> <syntaxhighlight lang="earthengine-api, geemap, rasterio, geopandas, shapely, matplotlib">
