Change detection in GIS works by comparing satellite imagery captured at different dates to identify how a landscape has changed over time. Instead of viewing a single image in isolation, the system analyses multiple imagery layers to detect differences in vegetation, land cover, infrastructure, water bodies, and other environmental features.
Using remote sensing and spatial analysis, GIS can highlight areas where significant changes have occurred between monitoring periods. In forest environments, this may include deforestation, fire damage, canopy loss, vegetation decline, infrastructure expansion, land clearing, or shifts in water availability.
The process relies on both visual comparison and automated analytics. Spectral data captured by satellite sensors allows GIS systems to detect subtle environmental changes that may not be immediately visible to the human eye. Automated change detection tools can then flag these areas for further analysis or generate alerts when unexpected activity is identified.
Within SWIFTForest, change detection supports continuous environmental monitoring by creating a time-based record of forest conditions. This allows organisations to track trends, identify risks early, and respond more quickly to environmental threats or operational changes.
Over time, change detection transforms raw satellite imagery into actionable environmental intelligence, helping organisations understand not just what a landscape looks like, but how and why it is changing.