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Article: Estimating land surface temperature from Feng Yun-3C/MERSI data using a new land surface emissivity scheme
Title | Estimating land surface temperature from Feng Yun-3C/MERSI data using a new land surface emissivity scheme |
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Authors | |
Keywords | FY-3C/MERSI GLASS Land surface emissivity Land surface temperature |
Issue Date | 2017 |
Citation | Remote Sensing, 2017, v. 9, n. 12, article no. 1247 How to Cite? |
Abstract | Land surface temperature (LST) is a key parameter for a wide number of applications, including hydrology, meteorology and surface energy balance. In this study, we first proposed a new land surface emissivity (LSE) scheme, including a lookup table-based method to determine the vegetated surface emissivity and an empirical method to derive the bare soil emissivity from the Global LAnd Surface Satellite (GLASS) broadband emissivity (BBE) product. Then, the Modern Era Retrospective-Analysis for Research and Applications (MERRA) reanalysis data and the Feng Yun-3C/Medium Resolution Spectral Imager (FY-3C/MERSI) precipitable water vapor product were used to correct the atmospheric effects. After resolving the land surface emissivity and atmospheric effects, the LST was derived in a straightforward manner from the FY-3C/MERSI data by the radiative transfer equation algorithm and the generalized single-channel algorithm. The mean difference between the derived LSE and field-measured LSE over seven stations is approximately 0.002. Validation of the LST retrieved with the LSE determined by the new scheme can achieve an acceptable accuracy. The absolute biases are less than 1 K and the STDs (RMSEs) are less than 1.95 K (2.2 K) for both the 1000 m and 250 m spatial resolutions. The LST accuracy is superior to that retrieved with the LSE determined by the commonly used Normalized Difference Vegetation Index (NDVI) threshold method. Thus, the new emissivity scheme can be used to improve the accuracy of the LSE and further the LST for sensors with broad spectral ranges such as FY-3C/MERSI. |
Persistent Identifier | http://hdl.handle.net/10722/322045 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Meng, Xiangchen | - |
dc.contributor.author | Cheng, Jie | - |
dc.contributor.author | Liang, Shunlin | - |
dc.date.accessioned | 2022-11-03T02:23:14Z | - |
dc.date.available | 2022-11-03T02:23:14Z | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | Remote Sensing, 2017, v. 9, n. 12, article no. 1247 | - |
dc.identifier.uri | http://hdl.handle.net/10722/322045 | - |
dc.description.abstract | Land surface temperature (LST) is a key parameter for a wide number of applications, including hydrology, meteorology and surface energy balance. In this study, we first proposed a new land surface emissivity (LSE) scheme, including a lookup table-based method to determine the vegetated surface emissivity and an empirical method to derive the bare soil emissivity from the Global LAnd Surface Satellite (GLASS) broadband emissivity (BBE) product. Then, the Modern Era Retrospective-Analysis for Research and Applications (MERRA) reanalysis data and the Feng Yun-3C/Medium Resolution Spectral Imager (FY-3C/MERSI) precipitable water vapor product were used to correct the atmospheric effects. After resolving the land surface emissivity and atmospheric effects, the LST was derived in a straightforward manner from the FY-3C/MERSI data by the radiative transfer equation algorithm and the generalized single-channel algorithm. The mean difference between the derived LSE and field-measured LSE over seven stations is approximately 0.002. Validation of the LST retrieved with the LSE determined by the new scheme can achieve an acceptable accuracy. The absolute biases are less than 1 K and the STDs (RMSEs) are less than 1.95 K (2.2 K) for both the 1000 m and 250 m spatial resolutions. The LST accuracy is superior to that retrieved with the LSE determined by the commonly used Normalized Difference Vegetation Index (NDVI) threshold method. Thus, the new emissivity scheme can be used to improve the accuracy of the LSE and further the LST for sensors with broad spectral ranges such as FY-3C/MERSI. | - |
dc.language | eng | - |
dc.relation.ispartof | Remote Sensing | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.subject | FY-3C/MERSI | - |
dc.subject | GLASS | - |
dc.subject | Land surface emissivity | - |
dc.subject | Land surface temperature | - |
dc.title | Estimating land surface temperature from Feng Yun-3C/MERSI data using a new land surface emissivity scheme | - |
dc.type | Article | - |
dc.description.nature | published_or_final_version | - |
dc.identifier.doi | 10.3390/rs9121247 | - |
dc.identifier.scopus | eid_2-s2.0-85038208074 | - |
dc.identifier.volume | 9 | - |
dc.identifier.issue | 12 | - |
dc.identifier.spage | article no. 1247 | - |
dc.identifier.epage | article no. 1247 | - |
dc.identifier.eissn | 2072-4292 | - |
dc.identifier.isi | WOS:000419235700043 | - |