Land Surface Temperature Estimation of Mandya district using LANDSAT-8 data

B. N. Aryalekshmi; Mohammed Ahamed J. Ahamed J.; R. C.  Biradar; Chandrasekar  K.

doi:10.6180/jase.202012_23(4).0002

Land Surface Temperature Estimation of Mandya district using LANDSAT-8 data

Aryalekshmi B. N. This email address is being protected from spambots. You need JavaScript enabled to view it.¹, Mohammed Ahamed J.², Dr. R. C. Biradar¹, and Dr. Chandrasekar K.³

¹School of ECE, REVA University, Bangalore, India
²RRSC – South, NRSC, ISRO, Bengaluru, India
³RRSC-Hyderabad, NRSC, ISRO, India

Received: December 10, 2019
Accepted: May 29, 2020
Publication Date: December 1, 2020

Download Citation: ||https://doi.org/10.6180/jase.202012_23(4).0002

ABSTRACT

This paper focuses on the estimation of LST over Mandya district (120^o31’N, 760^o53’E), which is a part of the Cauvery river basin in Karnataka, India, using LANDSAT-8 satellite data for 12 meteorological stations. Landsat 8 data is used for experimentation during 21st Jan 2018 and 6th Feb 2018 for LST analysis of identiﬁed area. More than half of the land area in the Mandya district is under agricultural use. Fluctuations in LST affects the quality of agricultural production. As a result, proper estimation of LST is very much required for the management of crop growth, development, and yield component. Spectral radiance from band 10 and emissivity of thermal infrared bands was used as input for LST estimation. Surface emissivity was obtained with the help of NDVI (Normalized Difference Vegetation Index), Leaf Area Index (LAI), and Albedo in the Mandya region. ERDAS IMAGINE and ArcGIS software were used for modeling. The obtained data compared with weather station data collected by KSNDMC (Karnataka State Natural Disaster Monitoring Centre). For this analysis, we considered two sets of data taken on different dates during the said period. The Root Mean Square Error (RMSE) and correlation coefﬁcient are used as statistical criteria for evaluating the model efﬁciency. From the comparison, it is found that RMSE and R for the ﬁrst date are 0.94^oC, 0.62, and for the second date, it is 1.26^oC, 0.88, respectively. It is observed that LST and weather data do follow the same pattern for the selected 12 meteorological stations.

Keywords: Emissivity; Land surface temperature (LST); NDVI; LAI; LANDSAT-8; Mandya

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