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Mehdi Feyzolahpour ,
Volume 10, Issue 2 (9-2023)
Abstract

Earth's surface temperature is considered an important parameter in biosphere, ice globe and climate change studies. In this research, LST, NDVI, NDMI and NDWI values were calculated for the Anzali wetland area using the OLI and TIRS measurements of the Landsat 8 satellite. Investigations showed that the minimum LST temperature for the years 2013, 2018 and 2023 was equal to 13.94, 22.36 and 14.6, respectively, and its maximum values for these years were equal to 35.7, 40.58 and 31.6. 31.6 degrees Celsius is estimated respectively. Vegetation status, access to water resources and water stress for the study area were estimated with NDVI, NDWI and NDMI indices. Bands 3, 4, 5, 6 and 10 of Landsat 8 satellite were used to estimate these indicators. The obtained values were compared with LST values. The distribution charts show that the highest negative correlation between LST and NDMI is established at the rate of -0.65 and the highest positive correlation between the NDWI and LST indices is established at the rate of 0.23. In general, the investigations have shown that there is a negative correlation between the NDMI and NDVI indices with the LST index. The Support Vector Machine (SVM) method was also used to investigate land use changes (LULC). The results showed that in the studied area, which has an area of 686.81 square kilometers, agricultural lands have faced significant expansion and reached 487.7 square kilometers from 329 square kilometers in 2013. In the meantime, forest areas have faced a sharp decrease and have decreased from 34.8 square kilometers to 1.73 square kilometers.

Arastoo Yari, Mehdi Feyzolahpour, Neda Kanani,
Volume 10, Issue 4 (12-2023)
Abstract

Earth surface temperature provides important information on the role of land use and land cover on energy balance processes. Therefore, the purpose of this research is to evaluate the LST patterns due to changes in land use (LULC). The studied area is located in Talesh region with an area of 300.6 square kilometers. For this purpose, Landsat images were downloaded in dry and wet seasons from 1365 to 1401. Four user classes were identified by maximum likelihood classification (MLC) and support vector machine (SVM) in 36-year intervals. The Kappa coefficient values for the SVM model were equal to 0.7802 and for the MLC model it was equal to 0.5328. NDVI, NDSI, and NDWI spectral indices were calculated for vegetation, barren soil, and water and were compared with LST in the above years. Changes in land use during the years 1365 to 1401 were an important factor in changes in the temperature of the earth's surface, which averaged from 13.7 degrees Celsius to 39.5 degrees Celsius in the wet season and -0.37 to 41.07 degrees Celsius in the dry season has been variable. Water areas and vegetation have the lowest and barren soil have the highest LST values. The highest negative correlation of -0.74 belongs to the NDVI index in 1365 and the highest positive correlation of 0.79 belongs to the NDSI index in 1365. The area of the forest area has decreased by 20.3% and agricultural land has increased by 217% in 36 years. Barren lands have changed the most and decreased from 2.68 square kilometers to 12 square kilometers. In general, LST has increased due to the increase of human activities such as the expansion of agricultural land and deforestation in the studied period.
 


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