发射率
遥感
环境科学
植被(病理学)
土地覆盖
表面粗糙度
航程(航空)
气象学
材料科学
地质学
光学
物理
土地利用
工程类
病理
土木工程
复合材料
医学
作者
Sofia L. Ermida,Glynn Hulley,Frank-M. Göttsche,Isabel F. Trigo
出处
期刊:IEEE Transactions on Geoscience and Remote Sensing
[Institute of Electrical and Electronics Engineers]
日期:2023-01-01
卷期号:61: 1-18
被引量:4
标识
DOI:10.1109/tgrs.2023.3301615
摘要
Land Surface Emissivity (LSE) is a critical variable in the quantification of the surface energy budget and for the estimation of surface parameters from earth observation data, in particular the Land Surface Temperature (LST). A new LSE product is proposed that combines two widely used methods: the Vegetation Cover Method (VCM) and the Temperature Emissivity Separation (TES) algorithm. The so-called V-TES approach maximizes the strengths of each method, considering their different performance over a wide range of surface conditions. As such, over vegetated areas, where thermal spectral contrasts are low and retrievals using TES are less accurate, we use the VCM method, while over bare areas, where the VCM relies entirely on ancillary information, the TES method is preferred. The proposed methodology was applied to observations from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard Meteosat Second Generation (MSG) satellites to derive emissivity channel and broad-band emissivities in the 3-14 μm range. Daily LSE maps are then derived using estimates of fraction of vegetation cover and snow cover. The product shows good agreement with in-situ data, with accuracies of 0.009 and 0.014 in the 8-14 μm and 3-8 μm regions, respectively. The methodology described in this article will be used to improve LST estimates and will be applied by the LSA-SAF for LST production from EUMETSAT’s Meteosat Second and Third Generation (MSG/MTG) and the Polar System-Second Generation (EPS-SG) missions.
科研通智能强力驱动
Strongly Powered by AbleSci AI