Analyzing Climatic Variability Using The Geospatial Technique In Sikkim Himalaya
Suresh Chand RAI, University of Delhi, India
Aakash UPADHYAY, University of Delhi, India
Climatic changes, variability, and differential land surface temperature have significantly impacted biodiversity and menkind unequivocally. The entire Himalayan region and Sikkim Himalaya are no exception, showing signs of climatic variability. Land surface temperature is an essential determinant of climate anomalies and patterns over an area. It has a direct bearing on local vegetation (species richness), land use, and water resources. The region is witnessing changing vegetation cover, declining yield, erratic rainfall, rising temperature, water availability, and associated land-use/cover change, all having direct bearing with climate. The present research delves into analyzing the climatic variability by analyzing land-use-cover using geo-spatial tools like land surface temperature, vegetation cover, and water bodies. Landsat 5 and Landsat 8 satellite imageries of April and October 1988, 2004, and 2020 were acquired, and Land Surface Temperature, vegetation cover, and area under water bodies have been analyzed using Arc-GIS 10.5. Further, Meteorological data from 1985-2017 were analyzed to understand the observed data trend using regression analysis in E-Views 9. A primary survey was conducted at the household and community level in 2017-18 to understand climate change perceptions and impacts. The results suggest fluctuating temperature trends, the declining area under various forest covers, and fluctuating water availability in 32 years. Data from the Indian Meteorological Department data projected increasing temperature and precipitation with a high level of significance. The trend is a poor sign for a fragile ecosystem like Sikkim Himalaya. The region needs a sustainable and effective climate change coping mechanism whereby adopting indigenous local knowledge and practices could play a vital role.
Keywords: Climate Change; Geo-Spatial; Indigenous Local Knowledge; Land Surface Temperature; Meteorological Data; Sikkim Himalaya.