| Impact of anthropogenic activities on Land Use Land Cover Changes and Land Surface Temperature in Parbati Watershed, North-Western Himalaya |
| Paper ID : 1149-ICRSSSA |
| Authors |
|
PAWAN KUMAR THAKUR * GIS Lab, Conifer Campus, Himalayan Forest Research Institute, Panthaghati, Shimla |
| Abstract |
| Land Surface Temperature (LST) is a significant parameter in the processes of surface energy exchange and water cycle between land and the atmosphere as well as studies related to hydrological processes, glacier/snow melt, Land Use Land Cover (LULC), and climate change. The present study was carried out in Parbati Watershed and also identified anthropogenic influences on LST and LULC change dynamics. The LST retrieval using Thermal Infrared Sensor (TIRS), Single-Channel (SC) algorithm for Landsat-7 (ETM+), 2001, and Split-Window (SW) algorithm for Landsat-8 (OLI), 2021. The supervised classification technique using Support Vector Machine (SVM) in ENVI 5.8, and ERDAS Imagine 2020 software were employed in both Landsat datasets, (October 2001-2021). The overall LULC analysis showed a significant decrease (-3.56 %) in glaciers/snow-covered areas as well as there was a notable increment of 22.56 Km2 (1.30 %) and 1.15 Km2 (0.07 %), in the area under rocky/open land and built-up/settlements, respectively during 2001 to 2021. The spatial distribution of LST in 2001 ranged from a lowest of -05.59°C to a highest of 34.60°C; whereas, for 2021 ranged from a lowest of -06.57°C to a highest of 35.49°C. The relative comparison of LST on various LULC categories, derived from SC and SW algorithms showed that there is an average difference of ± 1°C from 2001-2021. The present study observation will provide very useful scientific information on the causes of extreme LST and mitigation measures. Policymakers could use the finding to develop a suitable model for the long-term sustainability of the hilly terrain |
| Keywords |
| Land Surface Temperature, Split Window, Support Vector Machine |
| Status: Accepted (Oral Presentation) |
