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Reconstruction of daytime land surface temperatures under cloud-covered conditions using integrated MODIS/Terra land products and MSG geostationary satellite data

文献类型：期刊论文

作者Zhao Wei1,3; Duan Si-Bo2
刊名Remote Sensing of Environment
出版日期2020
卷号247页码:111931
关键词Atmospheric temperature Decision trees Geostationary satellites Incident solar radiation Pixels Radiometers Surface measurement Surface properties Temperature measurement Topography Vegetation
ISSN号0034-4257
DOI10.1016/j.rse.2020.111931
产权排序1
通讯作者Duan, Si-Bo(duansibo@caas.cn)
文献子类Article
英文摘要There is considerable demand for satellite observations that can support spatiotemporally continuous mapping of land surface temperature (LST) because of its strong relationships with many surface processes. However, the frequent occurrence of cloud cover induces a large blank area in current thermal infrared-based LST products. To effectively fill this blank area, a new method for reconstructing the cloud-covered LSTs of Terra Moderate Resolution Imaging Spectroradiometer (MODIS) daytime observations is described using random forest (RF) regression approach. The high temporal resolution of the Meteosat Second Generation (MSG) LST product assisted in identifying the temporal variations in cloud cover. The cumulative downward shortwave radiation flux (DSSF) was estimated as the solar radiation factor for each MODIS pixel based on the MSG DSSF product to represent the impact from cloud cover on incident solar radiation. The RF approach was used to fit an LST linking model based on the datasets collected from clear-sky pixels that depicted the complicated relationship between LST and the predictor variables, including the surface vegetation index (the normalized difference vegetation index and the enhanced vegetation index), normalized difference water index, solar radiation factor, surface albedo, surface elevation, surface slope, and latitude. The fitted model was then used to reconstruct the LSTs of cloud-covered pixels. The proposed method was applied to the Terra/MODIS daytime LST product for four days in 2015, spanning different seasons in southwestern Europe. A visual inspection indicated that the reconstructed LSTs thoroughly captured the distribution of surface temperature associated with surface vegetation cover, solar radiation, and topography. The reconstructed LSTs showed similar spatial pattern according to the comparison with clear-sky LSTs from temporally adjacent days. In addition, evaluations against Global Land Data Assimilation System (GLDAS) NOAH 0.25° 3-h LST data and reference LST data derived based on in-situ air temperature measurements showed that the reconstructed LSTs presented a stable and reliable performance. The coefficients of determination derived with the GLDAS LST data were all above 0.59 on the four examined days. These results indicate that the proposed method has a strong potential for reconstructing LSTs under cloud-covered conditions and can also accurately depict the spatial patterns of LST. © 2020 Elsevier Inc.
WOS关键词POLAR ORBITING SATELLITES ; SPLIT-WINDOW ALGORITHM ; NDVI TIME-SERIES ; RANDOM FOREST ; SOLAR-RADIATION ; MODIS LST ; SPATIOTEMPORAL ANALYSIS ; AIR-TEMPERATURE ; DIURNAL CYCLE ; IN-SITU
资助项目National Natural Science Foundation of China[41771409] ; Strategic Priority Research Program of the Chinese Academy of Sciences (CAS)[XDA20020401] ; CAS Light of West China Program ; Youth Innovation Promotion Association CAS[2016333]
WOS研究方向Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology
语种英语
WOS记录号WOS:000549189200031
出版者ELSEVIER SCIENCE INC
资助机构National Natural Science Foundation of China ; Strategic Priority Research Program of the Chinese Academy of Sciences (CAS) ; CAS Light of West China Program ; Youth Innovation Promotion Association CAS
源URL[http://ir.imde.ac.cn/handle/131551/34910]  
专题成都山地灾害与环境研究所_数字山地与遥感应用中心
通讯作者Duan Si-Bo
作者单位1.Kathmandu Center for Research and Education, Chinese Academy of Sciences-Tribhuvan University, Beijing, 100101, China;
2.Key Laboratory of Agricultural Remote Sensing, Ministry of Agriculture/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
3.Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, 610041, China;
推荐引用方式
GB/T 7714		 Zhao Wei,Duan Si-Bo. Reconstruction of daytime land surface temperatures under cloud-covered conditions using integrated MODIS/Terra land products and MSG geostationary satellite data[J]. Remote Sensing of Environment,2020,247:111931.
APA Zhao Wei,&Duan Si-Bo.(2020).Reconstruction of daytime land surface temperatures under cloud-covered conditions using integrated MODIS/Terra land products and MSG geostationary satellite data.Remote Sensing of Environment,247,111931.
MLA Zhao Wei,et al."Reconstruction of daytime land surface temperatures under cloud-covered conditions using integrated MODIS/Terra land products and MSG geostationary satellite data".Remote Sensing of Environment 247(2020):111931.

入库方式： OAI收割

来源：成都山地灾害与环境研究所

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