Clustering of detected changes in satellite imagery using fuzzy c-means algorithm

GeoCDX (Geospatial Change Detection and eXploitation) is an integrated system for detecting change between multi-temporal, high-resolution satellite or airborne images. Overlapping images are organized into 256×256 meter tiles in a global grid system. A tile change score measures the amount of change in the tile which is the aggregation of pixel-level change score. The tiles are initially ranked by these change scores. However, this ranking does not account for the wide variety of change types. To learn the change patterns in the data, we apply the fuzzy c-means clustering algorithm to the tiles. Each resulting cluster contains tiles with similar type of change. Users looking for certain types of change can review the tile clusters rather than the more time consuming process of searching through the tile list based on the initial ranking. The clusters also provide users an overview of various types of change found in the scene.