Remote sensed high resolution images for cartographic updating

Abstract

Problems related to rapid transformation of land-use have reached a significant impact level. Photo interpretation by human experts has been the major data source for disasters' monitoring and urban planning applications. However, images collected from a sensor which combines reasonably good spectral and spatial resolution images acquired by IKONOS II satellite and a RGB-HIS transformation technique have been considered to merge spectral and spatial information. Then, textural information, which characterizes urban area, has been extracted with the use of an appropriate filter for edge extraction. An MLP classifier has been trained to produce a labeled image with great accuracy in test even if a limited training set has been used. For a photo interpreter, the results reveal a good feasibility of the classified image for monitoring the presence of changes in urban areas, useful for cartographic updating.