Estimation and Validation of Land Surface Temperature Using Chinese Geostationary FengYun Meteorological Satellite (FY-2D) Data in an Arid Region

Xin Pan; Suyi Liu; Zi Yang; Xi Zhu; Yingbao Yang; Wenying Xie; Jie Yuan; Zhanchuan Wang; Hao Song

doi:10.1109/ACCESS.2023.3271122

IEEE Access (Jan 2023)

Estimation and Validation of Land Surface Temperature Using Chinese Geostationary FengYun Meteorological Satellite (FY-2D) Data in an Arid Region

Xin Pan,
Suyi Liu,
Zi Yang,
Xi Zhu,
Yingbao Yang,
Wenying Xie,
Jie Yuan,
Zhanchuan Wang,
Hao Song

Affiliations

Xin Pan: ORCiD; School of Earth Science and Engineering, Hohai University, Nanjing, China
Suyi Liu: School of Earth Science and Engineering, Hohai University, Nanjing, China
Zi Yang: School of Earth Science and Engineering, Hohai University, Nanjing, China
Xi Zhu: School of Earth Science and Engineering, Hohai University, Nanjing, China
Yingbao Yang: ORCiD; School of Earth Science and Engineering, Hohai University, Nanjing, China
Wenying Xie: ORCiD; School of Earth Science and Engineering, Hohai University, Nanjing, China
Jie Yuan: School of Earth Science and Engineering, Hohai University, Nanjing, China
Zhanchuan Wang: ORCiD; School of Earth Science and Engineering, Hohai University, Nanjing, China
Hao Song: School of Earth Science and Engineering, Hohai University, Nanjing, China

DOI: https://doi.org/10.1109/ACCESS.2023.3271122
Journal volume & issue: Vol. 11
pp. 136033 – 136040

Abstract

Read online

This study calibrated a refined split-window algorithm for land surface temperature (LST) retrieval based on Fengyun-2D (FY-2D) meteorological satellite. First, FY-2D land surface emissivity (LSE) was predicted from Moderate-resolution Imaging Spectroradiometer (MODIS) LSE based on sensors spectral similarities. The retrieved FY-2D LST data were validated in an arid region where the traditional split-window algorithm generally performed unsatisfactorily. Validation results show R2 (coefficient of determination) and RMSE (root mean square error) values range 0.53–0.67 and 2.86–6.21 K, respectively, against ground observed LST. Better LST retrievals were observed over vegetated regions with an RMSE value of ~2.8 K. Spatially, the FY-2D LST was highly correlated (R2 = 0.83) with and showed marginal differences (±2 K) from MODIS LST for ~40% of the whole area.

Published in IEEE Access

ISSN: 2169-3536 (Online)
Publisher: IEEE
Country of publisher: United States
LCC subjects: Technology: Electrical engineering. Electronics. Nuclear engineering
Website: https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6287639

About the journal

Abstract

Keywords