This paper is published in Volume-6, Issue-2, 2020
Area
Remote Sensing
Author
Deepika Vashishtha, Seeta Meena, Amit Sharma
Org/Univ
Aligarh Muslim University, Aligarh, Uttar Pradesh, India
Pub. Date
01 April, 2020
Paper ID
V6I2-1318
Publisher
Keywords
Remote sensing, GIS, Land surface temperature (LST), Urbanization, Industrialization, Normalized difference vegetation index (NDVI), Normalized difference built-up index (NDBI).

Citationsacebook

IEEE
Deepika Vashishtha, Seeta Meena, Amit Sharma. Estimation of the land surface temperature using Landsat data 8 and 5: A comparative analysis of an industrial area from Rajasthan, India, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Deepika Vashishtha, Seeta Meena, Amit Sharma (2020). Estimation of the land surface temperature using Landsat data 8 and 5: A comparative analysis of an industrial area from Rajasthan, India. International Journal of Advance Research, Ideas and Innovations in Technology, 6(2) www.IJARIIT.com.

MLA
Deepika Vashishtha, Seeta Meena, Amit Sharma. "Estimation of the land surface temperature using Landsat data 8 and 5: A comparative analysis of an industrial area from Rajasthan, India." International Journal of Advance Research, Ideas and Innovations in Technology 6.2 (2020). www.IJARIIT.com.

Abstract

Land surface temperature (LST) is the radiative skin temperature of the land derived from solar radiation. It helps in understanding various environmental processes from local to a global scale. However, rapid urbanization and industrialization are also contributing substantially to LST. This present study has been carried out to estimate the Land surface temperature of an industrial area called ‘Neem Ka Thana’ in the eastern Rajasthan using Landsat data 8 and 5. A comparative analysis has also been presented for 1990 and 2019 to understand the magnitude and role of industrialization in increasing the temperature of the land. The LST has been estimated with respect to Normalized Difference Vegetation Index (NDVI) values derived from Red and Near-Infrared bands. The Land Surface Temperature has been estimated using a step by step procedure incorporating Thermal band of Landsat 8 and 5 data for the month of May. This study also explains the shift in the area (sq. km) of temperature category over the period of 30 years and reflects the negative association of LST with NDVI while the positive relationship with NDBI.