earthchange

Multipurpose satellite change detection in pure Python. Map deforestation, mining, urbanisation, floods, burns, surface-water change and multi-epoch urban growth anywhere on Earth from free Sentinel-1/2 and Landsat data — via Google Earth Engine or Microsoft Planetary Computer (no account needed). Export georeferenced GeoTIFFs, quick-look PNGs, statistics, and print-ready A4 maps.

Install

Heavy dependencies are optional extras, so the install stays lean:

pip install 'earthchange[gee]'       # Google Earth Engine backend (free account)
pip install 'earthchange[mpc,maps]'  # Planetary Computer + maps (no account)
pip install 'earthchange[all]'       # everything

Quick start

# Deforestation around a coordinate, with a finished map
earthchange -s deforestation --lat -3.333 --lon 122.25 --radius 6 --map

# Flood extent from Sentinel-1 SAR — no Earth Engine account needed
earthchange -s flood --lat 27.2 --lon 68.3 \
    --pre 2022-07-01:2022-07-25 --post 2022-08-20:2022-09-10 --backend mpc

# Urban growth timing across 2010/2015/2020 (Landsat 5/8/9)
earthchange -s urban-trend --lat -6.30 --lon 107.15 --map

# List everything
earthchange --list

Each run writes a self-contained output/<run-id>/ folder containing the PNG, GeoTIFF, statistics JSON, metadata, and any maps.

Scenarios

Scenario Method Sensor
deforestation NDVI loss Sentinel-2
urbanization Built-up gain — NDBI (default), UI, BU, IBI, or thermal NDISI/EBBI via --method Sentinel-2 / Landsat
water NDWI change Sentinel-2
burn dNBR severity Sentinel-2
mining SIRAD radar temporal + NDVI loss Sentinel-1 + S2
flood SAR water extent (event vs baseline) Sentinel-1
urban-trend NDBI at 3 epochs → RGB growth-timing map Landsat 5/8/9
coastline Sea boundary + shoreline change (erosion/accretion) + retreat rate m/yr S1 / S2 / Landsat
transit-access % population with access to public transport (SDG 11.2.1) WorldPop + OSM
island-heat SST + LST + wet-bulb (humid heat) trends for small islands OISST / Landsat / ERA5
urban-heat Urban heat island (SUHII) + hot-spot map + decadal trend GHSL + Landsat + MODIS
forest-history Multi-epoch deforestation: year-of-loss map + forest-area trajectory S2 / Landsat NDVI
population-change Two-epoch population change: Miloš-style spike poster + map + optional true GPU 3D via forge3d GHSL GHS_POP
fire-history Multi-year fire record: burned area per year (peat vs mineral), recurrence map, fire season MODIS MCD64A1 + FIRMS

Two backends

--backend Data source Account?
gee (default) Google Earth Engine free account + earthengine authenticate
mpc Microsoft Planetary Computer (STAC) none — streams COGs, processes locally

Optical scenarios build cloud-masked median composites; radar scenarios auto-select the Sentinel-1 orbit with coverage. The AOI is a square centred on your coordinate. Landsat 7 is skipped (SLC-off gaps).

Make maps from a finished run

earthmap output/<run-id>            # render A4 map sheets offline (no GEE)

Map sheets include an OpenStreetMap basemap, the change layer, legend, a statistics panel, a location inset, coordinate grid, scale bar and north arrow.

License

MIT © Firman Hadi. Data: Copernicus Sentinel (ESA) and Landsat (USGS/NASA), via Google Earth Engine or Microsoft Planetary Computer.

Project links

Data verified by PyPI on Jul 29, 2026
Data provided by the project maintainers, verified at the time the release was uploaded to PyPI.

Key dates

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  • Released:
Newer release available (0.1.86)

1 maintainer

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Avatar for firmanhadi from gravatar.com firmanhadi

Credits

Author/Maintainer: Firman Hadi

GitHub Statistics

Data verified by PyPI on Jul 29, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License

MIT License (MIT)

Requires

Python >=3.11

Provides Extra

all forge3d gee maps mpc transit

Tags

change-detection deforestation earth-engine flood geospatial gis landsat ndbi ndvi planetary-computer remote-sensing sentinel

Classifiers

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