Massive Data Mining for Remote Sensing Imagery 

Recent advances in remote sensing technology have led to the increased availability of a multitude of satellite and airborne data, with increasing spatial, spectral and temporal resolutions. Additionally, at lower altitudes, airplanes and unmanned aerial vehicles can deliver very high resolution images from targeted locations. Remote sensing images of very high geometrical resolution can provide a precise and detailed representation of the surveyed scene, which is crucial to any application requiring content analysis. Combining spatial information with other information (like spectral information from hyperspectral imagery or elevation information from LiDAR data), can provide more comprehensive interpretation of objects on the ground. Extracting the relevant information from massive remote sensing data becomes very challenging in practice (the phenomenon that is today also referred to as the big data in various fields of science).