Open Access Open Access  Restricted Access Subscription or Fee Access

Estimation of Land Surface Temperature using Landsat Data: a Case Study of Agra City, India

Kamal Bisht


Land surface temperature (LST) is an important indicator for the study of climate change, urban environment, heat balance studies, hydrological and agricultural process, and urban land use and land cover as well as user input for climate models. Landsat data is utilized for the number of applications such as environment study, digester and resource management. Land surface temperate is estimated by the help of ArcGIS through Landsat 8 and 5 satellites images. The normalized difference vegetation index (NDVI) thresholds method was used for land surface emissivity (LSE) estimation; NDVI is calculated by near infrared (NIR) and red spectral bands in its formula. NDVI = (NIR-RED)/(NIR-RED). The thermal infrared band is the source of LSE in this study area. The aim of this study is to calculate the LST and NDVI of Agra city, India, and to accomplish this task, ArcGIS Raster calculator is utilized. The empirical determine value of NDVI, LSE, and LST with appropriate accuracy help to achieve the aim of this study. In the last drive out the temperature variance in different land use and land cover area of Agra city, India.
Keywords: ArcGIS, Landsat satellite images, land surface emissivity, land surface temperature, normalized difference vegetation index, raster calculator, Landsat 8

Full Text:



D Anandababu, BM Purushothaman, Babu S Suresh. Estimation of Land surface Temperature using Landsat 8 Data. International Journal of Advance Research, Ideas and Innovation in Technology. 2018;4(2).

David Parastatidis, Zina Mitraka, Nektrarios Chrysoulakis, Michael Abram. Online global land surface temperature estimation from Landsat. Remote Sensing. November 2017;9(12):1208.

Mani ND, et al. Estimation of LST of Dindigul district using Landsat 8 data. International Journal of Research in Engineering and Technology. May 2014;3(5):122–126.

Prasanjit Dash, Frank M Gottsche, Folke S Olesen et al. Land surface temperature and emissivity estimation from passive sensor

data: theory and practice current trends. International Journal of Remote Sensing. July 2002;23(13):2563.

Stefania Bonafoni, Chaiyapon Keeratikasikorn. Land surface temperature and urban density: multiyear modeling and relationship analysis using MODIS and Landsat Data. Remote Sensing, Remote Sens. 2018;10:1471. doi:10.3390/rs10091471.

Ugur Avdan, Gordana Jovanovska. Algorithm for automated mapping of the land surface temperature using LANDSAT 8 Satellite Data. Journal of Sensors. e 2016; Article ID 1480307; p. 8.

Zhao Liang Le, Hua Wu, Ning Wang, et al. Land surface emissivity retrieval from satellite data. International Journal of Remote Sensing. Oct, 2012;34(9–10):3084–3127. doi: (2013). Using the USGS Landsat Level-1 Data Product. [online] Available from [Accessed November 2019].



  • There are currently no refbacks.

eISSN: 2230-7990