Modeling the land surface temperature using thermal remote sensing at Godhra, Gujarat

• Published in: Journal of agrometeorology Vol. 21; no. 1; pp. 107 - 109
• Main Authors: Parmar, Sanjay H, Tiwari, Mukesh K, Pargi, Digvijaysinh L, Pampaniya, Nirav K, Rajani, Nirav V
• Format: Journal Article
• Language: English
• Published: Anand Association of Agrometeorologist 01.03.2019; Association of agrometeorologists
• Subjects: Air temperature; Automatic weather stations; Climatic data; Climatology; Computer simulation; Corn; Imagery; Information technology; Land surface temperature; Minimum temperatures; Modelling; MODIS; Night; Remote sensing; Spatial distribution; Surface temperature; Temperature; Temperature effects; Vegetation index; Watersheds; Gujarat India; United States > US; Maine; India
• ISSN: 0972-1665; 2583-2980
• DOI: 10.54386/jam.v21i1.216

(2012) estimated the spatial distribution of minimum and maximum air temperatures using land surface temperature (LST) and normalized differential vegetation index (NDVI) products from the MODIS sensor and air temperature (Ta) data from collected from automatic weather stations (AWS) over Gujarat region of India. In general, the regression equation were able to model the maximum and minimum temperature in Godhra using LST_NIGHT_1KM remote sensing imagery a promising agreement between the MODIS 1-km land surface temperature products and the ground-measured temperatures for the Godhra station, indicated the applicability of selected MODIS imagery for temperature simulation in the whole Kakanpur watershed and adjoining area. [...]it can be concluded that LST_Night_1km band could be used to calculate temperature over the CAET, Godhra and Kakanpur gauge stations of middle Guj arat. ACKNOWLEDGMENTS The authors convey sincere thanks to the Maine Maize Research Station, AAU, Godhra, Gujarat for providing required climatological data and ITRA, Digital India Corporation, Ministry of Electronics and Information Technology, Govt of India for providing the help for the study.