Spatial techniques for image classification

Abstract

The amount of image data that is received from satellites is constantly increasing. For example, nearly 3 terabytes of data are being sent to Earth by NASA’s satellites every day [1]. Advances in satellite technology and computing power have enabled the study of multi-modal, multi-spectral, multi-resolution, and multi-temporal data sets for applications such as urban land-use monitoring and management, GIS and mapping, environmental change, site suitability, and agricultural and ecological studies. Automatic content extraction, classification, and content-based retrieval have become highly desired goals for developing intelligent systems for effective and efficient processing of remotely sensed data sets.