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.
CITATION STYLE
Aksoy, S. (2006). Spatial techniques for image classification. In Signal and Image Processing for Remote Sensing (pp. 491–513). CRC Press. https://doi.org/10.1201/9781420003130-29
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