Accurate Classification of Remote Sensed Data for Landuse/Land Class of Mangaluru Coastal Region

摘要

Classification of remotely sensed data for land use/land class is one of the key areas for researchers in remote sensing fields. Classification of remote sensed data is necessary for the better categorization of semi urban land features such as wetlands, forests, agriculture and other land and water types. For the accurate classification of remotely sensed data, a high quality data set is needed. In the present research study, to classify the data set, PAN sharpened(fused) images are considered. Image fusion provides better quality and more informative image data set as compared to original data. The performance of different fusion techniques are then evaluated to select the best possible technique which gives better result for image classification.