Najme Satari; Malihe Erfani; FATEMEH Jahanishakib
Abstract
Trend analysis of growth of cities and predicting their changes in the future are essential for spatial planning. For this purpose, it is necessary to map build-up areas. In many areas, especially in arid climate, it is not possible to separate the build-up areas from the surrounding land cover simply. ...
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Trend analysis of growth of cities and predicting their changes in the future are essential for spatial planning. For this purpose, it is necessary to map build-up areas. In many areas, especially in arid climate, it is not possible to separate the build-up areas from the surrounding land cover simply. That's mean the usual methods of classifying satellite images or conventional indices can’t separate mentioned classes with acceptable accuracy. Hence, many researchers have developed different spectral indices to extract the build-up areas. The use of surface temperature changes to represent build-up areas using the Local Climate Zones (LCZ) algorithm is less considered and is a relatively new method. Therefore, in this paper, the separation of build-up areas from the other surrounding land cover was considered using LCZ algorithm. There is no limit to the number of bands in this method, thus four series of Landsat satellite images in the year 2020 were used and the LCZ algorithm’s accuracy was compared with the latest automatic classified build-up indices including DBI, BLFEI, BAEI and BAEM. The results of this study showed that the classification accuracy of the LCZ algorithm was 96%, while the BLFEI and BAEM indices were not able to completely separate the build-up areas from other types of land cover. The total accuracy of the BAEI index was 0.37. Therefore, the use of LCZ method has a high efficiency compared to build-up indices, and it is recommended in arid and semi-arid zones.
