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.
FATEMEH KAFI; Elham Yousefi; FATEMEH Jahanishakib
Abstract
The world is warming and the world's population is moving to cities. These two truths do not seem to be related; But a phenomenon called urban heat island connects the two. UHI is one of the most common urban climate phenomena in which some urban areas, especially urban centers, become several degrees ...
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The world is warming and the world's population is moving to cities. These two truths do not seem to be related; But a phenomenon called urban heat island connects the two. UHI is one of the most common urban climate phenomena in which some urban areas, especially urban centers, become several degrees warmer than the surrounding areas. Studying this phenomenon and examining its mechanism is very important for urban planning. In the present study, in order to estimate LST, four single-channel Landsat algorithms, single window, Planck equation and radiation transfer equation in QGIS software environment between 2000 and 2019 in summer and winter seasons in Birjand city have been used. The effect of land use change on the thermal island has also been investigated. In the present study, ground surface temperature in Birjand city was first extracted using Landsat 7 ETM + satellite imagery and Landsat 8 TIRS / OLI sensors in 2000 and 2019 by four methods. In order to investigate the general ability of algorithms to calculate the surface temperature, the statistical indices of mean square error, Nash-Sutcliffe coefficient, mean absolute error and coefficient of determination were used. The results showed that the Landsat single-channel algorithm for calculating the surface temperature in Birjand is more accurate than other algorithms.
