A new shadow detection index for 8-band very high-resolution satellite images

ABSTRACT

The new generation of remote sensing satellite with very high-resolution images has provided a high level of details, which make them a reliable source of information. Presence of shadow can reduce the amount of information that can be extracted from these images. Shadow can be confused with dark objects such as water and dark vegetation. The main aim of this research is to develop a new index to detect shadow in the presence of dark objects using the capabilities of the new remote sensing satellite images. For this study, WorldView-2 (WV-2) remote sensing satellite images with eight spectral bands were used. A spectral reflectance analysis for the main ground features has been studied along the eight spectral bands to determine the most effective bands for shadow detection. These bands are employed with the Hue-Saturation-Intensity colour model for producing the new proposed Saturation Intensity Shadow Detection Index (SISDI). The proposed index is applied to four study areas and compared with two state-of-the-art indices of shadow detection. Results of this comparison demonstrate the more accuracy effectiveness and feasibility of that proposed index. The proposed index achieves the highest overall accuracy (average of 97.8%) and has the ability for detecting small shadow areas.