  An entropy-based image segmentation approach is introduced and applied to
color images obtained from Google Earth. Segmentation refers to the process of
partitioning a digital image in order to locate different objects and regions
of interest. The application to satellite images paves the way to automated
monitoring of ecological catastrophes, urban growth, agricultural activity,
maritime pollution, climate changing and general surveillance. Regions
representing aquatic, rural and urban areas are identified and the accuracy of
the proposed segmentation methodology is evaluated. The comparison with gray
level images revealed that the color information is fundamental to obtain an
accurate segmentation.
