satchange 0.1.19

Multipurpose satellite change detection (deforestation, mining, urbanisation, floods, burns, water, urban growth) via Google Earth Engine or Microsoft Planetary Computer.

satchange

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.

• 📖 Full hands-on tutorial (English & Bahasa Indonesia): https://firmanhadi21.github.io/rs-change-detection/
• 💻 Source, examples & case study: https://github.com/firmanhadi21/rs-change-detection

Install

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

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

Quick start

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

# Flood extent from Sentinel-1 SAR — no Earth Engine account needed
satchange -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)
satchange -s urban-trend --lat -6.30 --lon 107.15 --map

# List everything
satchange --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

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

satmap 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.