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Showing 2 results for Feyzolahpour

M. Feyzolahpour, M. Ahmadi,
Volume 29, Issue 3 (Fall 2025)
Abstract

Drought is a hazard that can have widespread impacts on biodiversity, wildlife habitats, and ecosystem stability. The present study investigated the drought situation in the Bonab rural district. To assess the drought situation during the period 2013 to 2024, the Normalized Difference Vegetation Index (NDVI), Water Index (NDWI), Moisture Index (NDMI), Soil Adjusted Vegetation Index (MSAVI), and Land Surface Temperature (LST) were used. The results showed that the maximum value of the NDWI index reached from 0.16 in 2013 to 0.14 in 2024, which indicates an intensification of drought. However, the maximum value of the NDVI increased from 0.53 in 2013 to 0.58 in 2024, and the value for the MSAVI index for the years 2013 and 2024 was 0.69 and 0.73, respectively. All indices except the NDWI index had a negative correlation with the LST index, and the MSAVI index had the highest negative correlation with a Pearson coefficient of -0.39 in 2013. The results are also consistent with the results obtained from the SVM model. It is also observed that the area of barren lands has decreased from 887 square kilometers in 2013 to 851 square kilometers in 2024.

M. Feyzolahpour, B. Mohamady Yeganeh, M. Amri,
Volume 29, Issue 4 (Winter 2025)
Abstract

By utilizing land surface temperature (LST), valuable insights can be gained regarding the impact of land use on energy balance processes. Therefore, this study aimed to investigate the trend of LST changes due to land use changes in the Gorab rural district. Four land use types, including water bodies, bare land, Agricultural area, and forest, were determined from 2013 to 2024 for the maximum likelihood classification (MLC) and support vector machine (SVM) models. The surveys showed that the area of water in the dry period decreased from 0.9 km2 in 2013 to 0.4 km2 in 2024, a decrease of 0.5 km2. In contrast, the area of forest areas increased from 136.1 km2 in the dry period of 2013 to 147.2 km2 in 2024. The Kappa coefficient values for the SVM and MLC models during the wet season of 2021 were 53.94 and 68.7, respectively. Based on this, it was found that the MLC model has higher accuracy. To match spectral indices with LST values, NDVI, NDSI, and NDWI were calculated. Land use changes during the 2013-2024 period affected land surface temperatures, causing fluctuations from 11.5°C to 21.18°C in the wet season and from 13.81°C to 31.45°C in the dry season. The highest LST values were associated with barren land, while water bodies and vegetation cover had the lowest LST values. Among the spectral indices, the highest positive correlation was observed with NDWI, with a value of 0.64 in 2024. The highest negative correlation, -0.66, was observed with NDVI in the same year. Over the 11 years, the area of forest cover increased by 8.15%, while agricultural land decreased by 33.5%. The most significant change occurred in agricultural lands, which declined in area from 35.5 km² to 23.6 km².


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