earthstat

Inspired through participating in the AgML community's "Forecast Subnational Yield" activity, this Python library emerges as a vital tool for professionals and researchers engaged with remote sensing raster data. Designed with a focus on processing huge amount of TIFF files, our package excels at extracting statistical information for specific spatial units. By converting raster datasets into easily accessible CSV files. This library Ideal to prepare csv datasets for training Machine Learning (ML) models for different purposes. Also, significantly enhances the ability to leverage remote sensing data for impactful analyses (monitoring climate change, etc.). AgML community and the challenge of forecasting subnational agricultural yields has directly influenced the development of this library, ensuring it meets the high standards required for advanced environmental and agricultural data processing.

• Free software: MIT License
• Documentation: https://AbdelrahmanAmr3.github.io/earthstat

Features

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