REMOTE SENSING METHODS TO DETECT AND IDENTIFY CLAY-MADE HOUSES

Abstract. One of the most important issues in urban management is the existence of clay-made houses in or around cities. By the hypothesis that these phenomena are spectrally and spatially behaviour differently from other land uses and land covers. This study attempts to detect and identify clay-made houses through different image processing methods. In this regard, Sentinel 1, 2, and Landsat 8 OLI thermal images of Yazd city have been analysed. After pre-processing, a number of image processing techniques, including optical and radar image composite generation, band ratio, image fusion, image filtering, and image classification (i.e. MLC and ANN), have been used. The result shows that RGB from a combination of Red=radar band C, Green=sentinel band 8, and Blue=sentinel band 4 are the best for visual interpretation of clay-made houses. Also, the most suitable band ratio is the ratio corresponding to radar C and NIR, the Red and Green bands, and the best fusion is derived with Sentinel 1 (band C) and Sentinel 2 (bands 4 and 8) images through the HSV algorithm, kappa coefficients of the agreement for MLC and ANN classifiers are 0.89 and 0.29 respectively. It is concluded that remote sensing image analysis can effectively be used to detect and identify clay-made houses.