Effect of landscape pattern changes and environmental indices on land surface temperature in a fragile ecosystem in southeastern Iran

Abstract

Environmental indices and landscape pattern changes alter Land Surface Temperature (LST). Thus, the accurate evaluation of the relationship between these factors and LST is considered as important for managing ecosystems, especially the fragile ones under high stress. In the present study, Landsat TM5 satellite images (1989), Landsat 8 OLI/TIRS ones (2019), and Google Earth Engine (GEE) system were used to prepare the maps of temporal-spatial LST changes, Land Use/Land Cover (LULC), and selected environmental indices including Normalized Difference Vegetation (NDVI), Built-up (NDBI), Water Indices (NDWI), Land Surface Moisture (LSM) and albedo. Then, their correlation with LST was assessed. The results represented an 8.67-degree increase in the mean LST during 1989-2019. Urban and built-up areas had a signi cant effect on increasing the temperature of the region. Additionally, water bodies and vegetation cover in the region were the most crucial parameters in LST reduction. All of the applied indices were strongly related to LST (> 0.70), while some exhibited more correlation in each year. Further, the highest correlation of LST was observed with LSM and NDBI in 1989, as well as with NDVI and NDWI during 2019. Finally, the region rehabilitation based on the sustainable development principles played an important role in the direct and indirect decrease in LST.

Environmental Sustainability Assessment of a Himalayan Catchment With Land Cover Indices and LST Relationship Using Principal Component Analysis – A Geospatial Approach

“…Several studies wer e reported on the environmental sustainability aspects such as Eco-Hydrological sustainability (Khatun et al, 2021;Shiran et al, 2021), eco-environmental vulnerability (Nguyen et al, 2016;Liou et al, 2017;Venkatesh et al, 2020;and Kurn iawan et al, 2022), vegetation dynamics (Qureshi et al, 2020), Soil moisture-LST based drought characterization (Saha et al, 2018). Several hydrological, ecological, environmental, and socio-economic problems and their solutions have been addressed by analyzing the Remote Sensing based land cover changes for environmental sustainability (Liou et al, 2017;Venkatesh et al, 2020;Kurniawan et al, 2022;Saleh et al, 2022). It includes changes in the built-up area, wetlands, f o r es t cover, agricultural cropping patterns, and hydrological responses.…”