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Multi-seasonal remote sensing and climate analysis suite with machine learning classification using Google Earth Engine

copied from cf-post-staging / ndvi2gif

Installers

  • noarch v1.0.0
  • osx-64 v0.0.4
  • linux-64 v0.0.4
  • win-64 v0.0.4

conda install

To install this package run one of the following:
conda install conda-forge::ndvi2gif

Description

NDVI2GIF is a comprehensive Python library for multi-seasonal remote sensing and climate analysis using Google Earth Engine. Version 1.0.0 is the first stable release, expanding beyond vegetation monitoring into comprehensive climate analysis.

Key features include: - 88 variables across 7 satellite and climate platforms (Sentinel-1/2/3, Landsat, MODIS, ERA5-Land, CHIRPS) - ERA5-Land climate reanalysis (47 variables, 1950-present): temperature, precipitation, soil moisture, radiation, wind - CHIRPS high-resolution precipitation (1981-present, ~5.5km) - 40+ vegetation and environmental indices with SAR preprocessing - 8 machine learning classification algorithms (supervised and unsupervised) - Time series analysis with trend detection and phenology metrics - Complete Jupyter Book documentation for research workflows


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