RS
Abstract
Changes in land cover and land use due to human activities have left adverse effects on the environment. The eastern regions of Ardabil province are a clear example of this phenomenon. The purpose of this research is to analyze spatial and temporal changes in land cover and land use and its effects on ...
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Changes in land cover and land use due to human activities have left adverse effects on the environment. The eastern regions of Ardabil province are a clear example of this phenomenon. The purpose of this research is to analyze spatial and temporal changes in land cover and land use and its effects on the temperature of the surface of the earth in Lake Neor. To estimate land use and land cover, random forest models (RTC), maximum likelihood model (MLC) and support vector machine (SVM) were used and the efficiency of each was estimated by the Kappa coefficient and it was observed that the SVM model has the highest Kappa coefficient (0.87) Bands 6, 5 and 10 of Landsat 8 were also used to extract the LST index, and it was observed that the western part of the lake faced an increase in the temperature of the earth's surface. During the time period of 2002, 2013 and 2022, significant changes were observed in the water area of Neor Lake and its nearby vegetation. Barren lands had the largest extent in all studied periods. Vegetation has increased by 1.04 square kilometers based on SVM model. The surface area of the lake was estimated as 3.19 square kilometers based on the MLC model in 2002. The area of the water zone in the MLC model has decreased by 1.56 square kilometers between 2002 and 2022, and this decrease is 0.67 and 0.69 square kilometers for the RTC and SVM models, respectively.
RS
Abstract
Extraction of the water zone in the western parts of Afghanistan through remote sensing images is an efficient way to investigate and monitor water resources and its impact on the water resources of eastern Iran, especially the wells of Sistan and Baluchestan. In this research, from OLI sensor of Landsat ...
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Extraction of the water zone in the western parts of Afghanistan through remote sensing images is an efficient way to investigate and monitor water resources and its impact on the water resources of eastern Iran, especially the wells of Sistan and Baluchestan. In this research, from OLI sensor of Landsat 8 satellite and TM sensor of Landsat 5 satellite, Normalized Difference Water Index (NDWI), modified Normalized Difference Water Index (MNDWI), normalized difference moisture index (NDMI), automated water extracted index (AWEI), new water index (NWI), and water ratio index (WRI) have been used to extract water areas. In the worst case, the area of the Arghandab dam has decreased by only 2.44 km upstream and the NDMI index has shown an increase of 0.65 square km in the moisture resources of this dam. However, the surface of the well in the southern half of Zabul has decreased from 55.94 square kilometers to 17.82 square kilometers, which shows a decrease of 38.12 square kilometers. This shows a sharp decrease in the level of the semi-well. This has caused more heat to be emitted in the dry areas. But the minimum temperature has decreased from 17.47 degrees to 11.87 degrees Celsius, which has experienced a decrease of 1.95 degrees Celsius. The LST index has a negative correlation with all the indices and the highest correlation with the NWI index was -0.941 in 1994. The lowest correlation was also obtained at the rate of -0.65 related to the NDMI index.
RS
Mehdi feyzolahpour
Abstract
The purpose of this research is to investigate the relationship between LST and LULC in Heyran region. LULC indices consist of normalized difference of vegetation index (NDVI), normalized difference of built-up index (NDBI) and modified normalized difference of water index (MNDWI). The area of the studied ...
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The purpose of this research is to investigate the relationship between LST and LULC in Heyran region. LULC indices consist of normalized difference of vegetation index (NDVI), normalized difference of built-up index (NDBI) and modified normalized difference of water index (MNDWI). The area of the studied area is 156.95 square kilometers, out of which in 1401, about 122.7 square kilometers are dedicated to forest area and only 33.2 square kilometers are dedicated to agricultural land. The values of the MNDWI index in the richest region in 2017 had an area equal to 12.27 square kilometers and faced a sharp decrease in 1401 and reached 1.68 square kilometers. Built-up areas (NDBI) increased until 2017 and decreased significantly until 1401. The maximum land surface temperature (LST) has reached from 35.42 degrees Celsius in 2013 to 39.04 degrees Celsius in 1401. The area with a temperature of 20 to 25 degrees Celsius has increased from 67.9 square kilometers to 124 square kilometers. Finally, Pearson correlation relationships showed that NDVI and MNDWI index had a negative correlation with LST index and there was a positive correlation between LST index and NDBI index. The highest positive correlation of 0.77 between LST and NDBI belongs to the spring of 2017, and the highest negative correlation of -0.71 belongs to the MNDWI and LST index, which was registered in the fall of 2017.
