Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/157961
Title: Estimation of Land Surface Temperature Using FengYun-2E (FY-2E) Data: A Case Study of the Source Area of the Yellow River
Authors: Xiaoning Song;Yawei Wang;Bohui Tang;Pei Leng;Sun Chuan;Jian Peng;Alexander Loew
Year: 2017
Publisher: IEEE
Abstract: Land surface temperature (LST) is a key variable used for studies of water cycles and energy budgets of land&x2013;atmosphere interfaces. This study addresses the theory of LST retrieval from data acquired by the Chinese operational geostationary meteorological satellite FengYun-2E (FY-2E) in two thermal infrared channels (IR1: 10.29&x2013;11.45 &x03BC;m and IR2: 11.59&x2013;12.79 &x03BC;m) using a generalized split-window algorithm. Specifically, land surface emissivity (LSE) in the two thermal infrared channels is estimated from the LSE in channels 31 and 32 of the moderate-resolution imaging spectroradiometer (MODIS) product. In addition, an eight-day composition MODIS LSE product (MOD11A2) and the daily MODIS LSE product (MOD11A1) are used in the algorithm to estimate FY-2E emissivities. The results indicate that the LST derived from MOD11A1 is more accurate and, therefore, more appropriate for daily cloud-free LST estimation. Finally, the estimated LST was validated using the MODIS LST product for the heterogeneous source area of the Yellow River. The results show a significant correlation between the two datasets, with a correlation coefficient (<italic>R</italic>) varying from 0.60 to 0.94 and a root mean square error ranging from 1.89 to 3.71 K. Moreover, the estimated LST agrees well with ground-measured soil temperatures, with an <italic>R</italic> of 0.98.
URI: http://localhost/handle/Hannan/157961
volume: 10
issue: 8
More Information: 3744,
3751
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7896521.pdf1.1 MBAdobe PDF
Title: Estimation of Land Surface Temperature Using FengYun-2E (FY-2E) Data: A Case Study of the Source Area of the Yellow River
Authors: Xiaoning Song;Yawei Wang;Bohui Tang;Pei Leng;Sun Chuan;Jian Peng;Alexander Loew
Year: 2017
Publisher: IEEE
Abstract: Land surface temperature (LST) is a key variable used for studies of water cycles and energy budgets of land&x2013;atmosphere interfaces. This study addresses the theory of LST retrieval from data acquired by the Chinese operational geostationary meteorological satellite FengYun-2E (FY-2E) in two thermal infrared channels (IR1: 10.29&x2013;11.45 &x03BC;m and IR2: 11.59&x2013;12.79 &x03BC;m) using a generalized split-window algorithm. Specifically, land surface emissivity (LSE) in the two thermal infrared channels is estimated from the LSE in channels 31 and 32 of the moderate-resolution imaging spectroradiometer (MODIS) product. In addition, an eight-day composition MODIS LSE product (MOD11A2) and the daily MODIS LSE product (MOD11A1) are used in the algorithm to estimate FY-2E emissivities. The results indicate that the LST derived from MOD11A1 is more accurate and, therefore, more appropriate for daily cloud-free LST estimation. Finally, the estimated LST was validated using the MODIS LST product for the heterogeneous source area of the Yellow River. The results show a significant correlation between the two datasets, with a correlation coefficient (<italic>R</italic>) varying from 0.60 to 0.94 and a root mean square error ranging from 1.89 to 3.71 K. Moreover, the estimated LST agrees well with ground-measured soil temperatures, with an <italic>R</italic> of 0.98.
URI: http://localhost/handle/Hannan/157961
volume: 10
issue: 8
More Information: 3744,
3751
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7896521.pdf1.1 MBAdobe PDF
Title: Estimation of Land Surface Temperature Using FengYun-2E (FY-2E) Data: A Case Study of the Source Area of the Yellow River
Authors: Xiaoning Song;Yawei Wang;Bohui Tang;Pei Leng;Sun Chuan;Jian Peng;Alexander Loew
Year: 2017
Publisher: IEEE
Abstract: Land surface temperature (LST) is a key variable used for studies of water cycles and energy budgets of land&x2013;atmosphere interfaces. This study addresses the theory of LST retrieval from data acquired by the Chinese operational geostationary meteorological satellite FengYun-2E (FY-2E) in two thermal infrared channels (IR1: 10.29&x2013;11.45 &x03BC;m and IR2: 11.59&x2013;12.79 &x03BC;m) using a generalized split-window algorithm. Specifically, land surface emissivity (LSE) in the two thermal infrared channels is estimated from the LSE in channels 31 and 32 of the moderate-resolution imaging spectroradiometer (MODIS) product. In addition, an eight-day composition MODIS LSE product (MOD11A2) and the daily MODIS LSE product (MOD11A1) are used in the algorithm to estimate FY-2E emissivities. The results indicate that the LST derived from MOD11A1 is more accurate and, therefore, more appropriate for daily cloud-free LST estimation. Finally, the estimated LST was validated using the MODIS LST product for the heterogeneous source area of the Yellow River. The results show a significant correlation between the two datasets, with a correlation coefficient (<italic>R</italic>) varying from 0.60 to 0.94 and a root mean square error ranging from 1.89 to 3.71 K. Moreover, the estimated LST agrees well with ground-measured soil temperatures, with an <italic>R</italic> of 0.98.
URI: http://localhost/handle/Hannan/157961
volume: 10
issue: 8
More Information: 3744,
3751
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7896521.pdf1.1 MBAdobe PDF