Publication

Abstract : Climate change and the resulting modifications to the patterns of extreme weather events affect the sustainable development of a community. Advances made in the realms of remote sensing and computing provide robust tools for understanding such events. The current study uses Python to identify heatwaves during summer over the study region. Furthermore, the relation of heatwaves with soil moisture and vegetation is identified by utilizing Google Earth Engine. The study identifies the heatwave pattern in the region covering parts of Panjab, Haryana, and Rajasthan from 1951 to 2022 - that is, long-term temperature data for 71 years. Remote sensing observations from MODIS satellites are utilized to analyze the relationship between heatwave incidents with the soil moisture and vegetation of the region. The spectral indices, namely, normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) are used for this purpose. Land surface temperature (LST) product from MODIS indicates that an increase in LST adversely affects vegetation health.