An Examination of the Effect of Land Use Changes on the Temporal-Spatial Models of Land Surface Temperature Using Remote Sensing and GIS Data (Case Study: Ilam City)
2023
Sheikhi, Hojat | Malekmohamadi, Reza
Due to the vast changes it brings about in the land use and land cover, the rapid expansion of cities has had many negative effects on the environmental quality at global level. Examples include air quality, increased temperature, changes in perspective, and the alteration of agricultural lands into barren lands that leads to the loss of biodiversity. Since land use changes happen at extensively, remote sensing technology is a necessary, efficient, and valuable means to monitor changes. In this study, the effect of land use changes on the temporal-spatial patterns of land surface temperature in the urban lands of Ilam city in a 30-year period (1990-2020) was examined using Landsat satellite images and simulation of changes using fuzzy ARTMAP neural network model. Landsat satellite sensors (TM, OLI, ETM) were used to investigate the longitudinal and spatial changes (LST) in Ilam city. To provide the land use map, the pixel-based classification for all periods (1990-1995-2000-2005-2010-2015-2020) was applied using ENVI and Ecognitio software packs and then estimations were made using NDVI and LST models. The results showed that Ilam city ecosystem has moderate levels of NDVI. The average temperature of residential land use level in June is 35.8 degrees centigrade, and the temperatures of three land uses of horticulture, agriculture, and other uses (uncovered lands) were 32.22, 37.25, and 38.46, respectively, with the main lands with the minimum temperature being green highlands. In city, existence of high rise buildings and building shading, use of materials with less heat absorption such as Isogam, urban green space and furniture, and air pollution lead to lesser absorption of energy. On the other hand, the spatial distribution of NDVI was aligned with LSP values. The results regarding land use areas using fuzzy-neural network show that residential land uses has risen from 19.18 percent in 1990 to 39.35 percent in 2020, which shows the city expansion and development. On the other hand, the horticultural land use has declined from 8.64 in 1990 to 3.49 in 2020, which can be attributed to the development of urban space.
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