Land Classification using a novel Multispectral and SAR data Fusion in Doha area

Abstract:
A new algorithm for land classification is presented in this paper and is based on the fusion of Multispectral, Panchromatic and Synthetic Aperture Radar (SAR) images. The novel approach relies on Generalized Intensity-Hue-Saturation (G-HIS) transform and the Wavelet Transform (WT). The fused image is derived by modulating the SAR texture with the high features details of the Panchromatic WT and by injecting this product at the place of G-HIS high feature details. Finally, a classification is performed on the fused product by using a Maximum Likelihood (ML) classifier. The algorithm has been tested on data acquired by Sentinel-1 (SAR) and Landsat-8 (Multispectral and Panchromatic) over the area of Greater Doha in Qatar in 2017. Results show an increment of 3% in the overall accuracy for the fused product compared to the Multispectral dataset.