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Remote Sens. 2016, 8(5), 413; doi:10.3390/rs8050413

Application of Open Source Coding Technologies in the Production of Land Surface Temperature (LST) Maps from Landsat: A PyQGIS Plugin

Institute of Space and Earth Sciences, Anadolu University, Iki Eylul Campus, Eskisehir 26555, Turkey
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Author to whom correspondence should be addressed.
Academic Editors: Richard Müller and Prasad S. Thenkabail
Received: 29 March 2016 / Revised: 13 April 2016 / Accepted: 9 May 2016 / Published: 13 May 2016

Abstract

This paper presents a Python QGIS (PyQGIS) plugin, which has been developed for the purpose of producing Land Surface Temperature (LST) maps from Landsat 5 TM, Landsat 7 ETM+ and Landsat 8 TIRS, Thermal Infrared (TIR) imagery. The plugin has been developed purposely to ease the process of LST extraction from Landsat Visible, Near Infrared (VNIR) and TIR imagery. It has the ability to estimate Land Surface Emissivity (LSE), calculating at-sensor radiance, calculating brightness temperature and performing correction of brightness temperature against atmospheric interference though the Plank function, Mono Window Algorithm (MWA), Single Channel Algorithm (SCA) and the Radiative Transfer Equation (RTE). Using the plugin, LST maps of Moncton, New Brunswick, Canada have been produced for Landsat 5 TM, Landsat 7 ETM+ and Landsat 8 TIRS. The study put much more emphasis on the examination of LST derived from the different algorithms of LST extraction from VNIR and TIR satellite imagery. In this study, the best LST values derived from Landsat 5 TM were obtained from the RTE and the Planck function with RMSE of 2.64 °C and 1.58 °C, respectively. While the RTE and the Planck function produced the best results for Landsat 7 ETM+ with RMSE of 3.75 °C and 3.58 °C respectively and for Landsat 8 TIRS LST retrieval, the best results were obtained from the Planck function and the SCA with RMSE of 2.07 °C and 3.06 °C, respectively. View Full-Text
Keywords: Landsat Surface Temperature (LST); Land Surface Emissivity (LSE); Thermal Infrared (TIR); Landsat TM; Landsat ETM+; Landsat TIRS; Mono Window Algorithm (MWA); Single Channel Algorithm (SCA); Radiative Transfer Equation (RTE); Planck Equation Landsat Surface Temperature (LST); Land Surface Emissivity (LSE); Thermal Infrared (TIR); Landsat TM; Landsat ETM+; Landsat TIRS; Mono Window Algorithm (MWA); Single Channel Algorithm (SCA); Radiative Transfer Equation (RTE); Planck Equation
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Isaya Ndossi, M.; Avdan, U. Application of Open Source Coding Technologies in the Production of Land Surface Temperature (LST) Maps from Landsat: A PyQGIS Plugin. Remote Sens. 2016, 8, 413.

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