A novel method for urban land cover mapping based on new vegetation indices and texture-spectral information from fused visible and hyperspectral thermal infrared airborne data

Update information on urban regions has been substantial for management communities. In this research, a novel method was developed for Urban Land Cover Mapping (ULCM). Textural-spectral features obtained from Hyperspectral Thermal Infrared (HTIR) data were fused with spatial-spectral features of the visible image for ULCM. The proposed method consists of three hierarchical steps. First, trees and vegetation classes were classified based on spatial- spectral features extracted from the visible image. Also, two new vegetation indices were introduced. By studying spectral signatures of trees and vegetation classes on the HTIR data, it was shown that trees and vegetation classes could be discriminated by visible data. Second, textural-spectral features of the HTIR data were fused with visible image features to extract bare soil, (gray; concrete; red) roof buildings and roads classes. Using HTIR textural features increased the overall accuracy and Kappa coefficient values about 6% and 8% correspondingly. Third, the results of the first and second steps were overlaid and post processing has been done. The obtained results for overall accuracy and Kappa coefficient values were 94.96% and 0.928 respectively. The comparison of the achieved results with the results of the contest announced by IEEE has shown the efficiency of the proposed method.