Raster4ML：用于机器学习的地理空间栅格处理库链接：https://github.com/remotesensinglab/raster4mlWhen geospatial raster data is concerned in a machine learning pipeline, it is often required to extract meaningful features, such as vegetation indices (e.g., NDVI, EVI, NDRE, etc.) or textures. This package provides easy-to-use functions that can automatically calculates the features with one or several lines of codes in Python. It also has the functionality of extracting statistics based on shapefile (i.e., point or polygon) from a raster data. Any type of raster data is supported regardless of satellite or UAVs.Key FeaturesStack raster bandsAutomatically calculate vegetation indices (supports 350+ indices)Extract raster values based on shapefileClip raster based on polygonDocumentationDetailed documentation with tutorials can be found here: https://raster4ml.readthedocs.io/How to Use?Stacking bandsstack_bands(image_paths=['Band_1.tif', 'Band_2.tif', 'Band_3.tif',
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