NDLI: Retrieval of land surface temperature from Landsat 8 TIRS for the command area of Mula irrigation project

Content Provider	Springer Nature Link
Author	Nikam, Bhaskar R. Ibragimov, Furkat Chouksey, Arpit Garg, Vaibhav Aggarwal, S. P.
Copyright Year	2016
Abstract	Application of satellite remote sensing in generating various geophysical parameters of land surface has gained tremendous importance in many branches of science and applied research. Out of all geophysical parameters of land surface derived from satellite remote sensing, the land surface temperature (LST) is of prime importance. LST acts as a governing parameter in water and energy exchange between land and atmosphere. It is an essential input to all the numerical weather prediction models, most of the process-based hydrological models and even in irrigation water management activities. Many algorithms for space-based LST retrieval and operational products of LST are available nowadays. However, these products are generally coarser in spatial and/or temporal resolutions. In the sector of irrigation water management, higher spatial resolution of all the geophysical products is prerequisites. Hence, in the present study, LST has been retrieved using two popular algorithms viz. radiative transfer theory (RTT) equation-based method and split-window (SW) algorithm. LST of Mula irrigation project command area has been retrieved using twenty images of Landsat 8 Thermal Infrared Sensor (TIRS) and Operation Land Imager (OLI) for entire Rabi/Winter season. Atmospheric parameters needed for the LST retrieval have been derived using online atmospheric correction tool. The land surface emissivity has been estimated using NDVI threshold technique. The standard daily LST product of MODIS has been used to cross-validate the LST retrieved from both the algorithms. LST retrieved using SW algorithm shows higher correlation coefficient with MODIS LST in entire command area and in agricultural land as well (0.938 and 0.925, respectively) compared to that of LST output of RTT method (0.902 and 0.894, respectively). The relative comparison of the LST products derived from RTT and SW algorithms showed that there is an average difference of ±3 °K between these two products. However, the difference is very small (−0.8 to 0.5°K) in case of agricultural area in the command. The higher correlation coefficient values between retrieved LST using both the algorithms and MODIS LST products hints toward the higher accuracy of derived LST at higher spatial resolution. These high spatial resolution LST products can further be used for irrigation water management.
Starting Page	1
Ending Page	17
Page Count	17
File Format	PDF
ISSN	18666280
Journal	Environmental Earth Sciences
Volume Number	75
Issue Number	16
e-ISSN	18666299
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2016-08-12
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Land surface temperature Split-window algorithm Land surface emissivity Landsat 8 TIRS MODIS Geology Hydrology/Water Resources Geochemistry Environmental Science and Engineering Terrestrial Pollution Biogeosciences
Content Type	Text
Resource Type	Article
Subject	Global and Planetary Change Earth-Surface Processes Soil Science Environmental Chemistry Pollution Geology Water Science and Technology

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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