Climate Change Impact Assessment in Alpine region of Central Himalaya using Remote Sensing: A case study of Uttarakhand Himalaya

Abstract ID: 3.13455
| Accepted as Poster
| Abstract not registered
| TBA
| TBA
Parashar, D. (1)
Kashyap, A. (2); Palni, S. (2); Kumar, A. (1); Pandey, A. (3); and Singh, A. P. (4)
(1) Map Earth Educational Society, Dhar, 262541 Pithoragarh, IN
(2) Department of Remote Sensing and GIS, Soban Singh Jeena University, Almora, Mall Road Almora, Uttarakhand, India-263601
(3) Global Tiger Forum, E 18,, First Floor, East of Kailash, 110065, Delhi, New Delhi, IN
(4) Civil Engineering Department, Birla Institute of Technology and Science,, Pilani, 333031, India
How to cite: Parashar, D.; Kashyap, A.; Palni, S.; Kumar, A.; Pandey, A.; and Singh, A. P.: Climate Change Impact Assessment in Alpine region of Central Himalaya using Remote Sensing: A case study of Uttarakhand Himalaya, International Mountain Conference 2025, Innsbruck, Sep 14 - 18 2025, #IMC25-3.13455, 2025.
Categories: Monitoring
Keywords: Himalaya, Modis, Statistical test, Land surface temperature, trend analysis
Categories: Monitoring
Keywords: Himalaya, Modis, Statistical test, Land surface temperature, trend analysis
Abstract

Remote sensing techniques have significantly facilitated the study of long-term meteorological trends in high-altitude locations. Factors such as the burning of fossil fuels, anthropogenic activities, and increasing concentrations of black carbon are the main causes responsible for the rapid climate change. Due to climate change, the overall trend of different metrological variables like temperature and precipitation are shifting rapidly over the mountainous regions. This study focuses on the alpine region of Uttarakhand, a part of the Central Himalayan region. This study’s objectives include analyzing the meteorological trend analysis, analyzing the trend of LST (land surface temperature), and spatio-temporal shift monitoring of snow cover in the aoi. The datasets for this study includes- Modis Terra Land Surface Temperature and Emissivity datasets, Modis Terra Snow Cover Daily Global dataset for the extraction of snow cover area from 2000 to 2022, and Power Data Access Viewer datasets for analyzing the trend of meteorological variables. the Mann-Kendall and Sen’s slope test were used for the trend analysis. The study outcomes highlight that the Mann-Kendall test shows an upward shift in temperature, and the Sen’s slope test also represents an upward shift in trend for annual temperature of the last 34 years from 1990 – 2022. The outcome of this study is important for understanding the effect of climate change in the Himalayan cryosphere region.