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Algorithms Comparison of Land Surface Temperature Retrieval from Landsat Series Data:A Case Study in Qiqihar,China |
Jin Diandian 1,2,3,Gong Zhaoning 1,2,3 |
(1.College of Resources Environment & Tourism,Capital Normal University,Beijing 100048,China;2.Base of the State Laboratory of Urban Environmental Processes and Digital Modeling,Beijing 100048,China;3.Key Lab of Three-dimensional Information Acquisition and Applicationof the Ministry of Education,Beijing 100048,China) |
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Abstract Land Surface Temperature(LST)is considered to be one of the significant indicators of urban environment analysis.Landsat thermal infrared series data is an important data source for retrieving surface temperature.In this paper,the thermal infrared band of the Landsat data in 2002,2008 and 2016 were used to retrieve LST by three different algorithms in municipal area of Qiqihar,China.These algorithms were the Mono-Window algorithm(MW algorithm),the Single Channel algorithm(SC algorithm) and the Radiation Transport Equation method(RTE algorithm).And the results of the retrieval were compared to each other and verified by MODIS surface temperature products.The LST distribution maps were accomplished according to the retrieval results.The results showed that:(1)The spatial distribution of the LST obtained by the retrieval of the Landsat series by the three algorithms is consistent,and the LSTof the urban center is higher and thetemperature of water is the lowest;(2)Based on ETM+ data,the consistency between SC and RTE algorithm results is good,among which the SC algorithm has the highest precision,and the MW algorithm has large errors in different land cover areas;(3)The retrieval results by MW algorithm based on the TM data has the highest accuracy,RTE algorithm results is second,and the LST form SC algorithm is less consistent with the corresponding MODIS temperature products;(4)Based on the Landsat 8 TIRS data,the SC algorithm has the highest accuracy and the RTE algorithm has a large error.
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Received: 25 January 2018
Published: 01 March 2019
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