Comparison of the efficiency of local climatic zone algorithm in separating built-up area compared ‎to built-up indices

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.‎