An integrated model for generating hourly Landsat-like land surface temperatures over heterogeneous landscapes

doi:10.1016/j.rse.2017.12.003

	An integrated model for generating hourly Landsat-like land surface temperatures over heterogeneous landscapes
	Quan, Jinling 1,2; Zhan, Wenfeng 3; Ma, Ting 1,2; Du, Yunyan 1,2; Guo, Zheng 4; Qin, Bangyong 5
刊名	REMOTE SENSING OF ENVIRONMENT
	2018-03-01
卷号	206 页码:403-423
关键词	Data fusion Land surface temperature Landsat MODIS Geostationary satellite Heterogeneity
ISSN号	0034-4257
DOI	10.1016/j.rse.2017.12.003
通讯作者	Quan, Jinling(quanjl@lreis.ac.cn)
英文摘要	The trade-off between spatial and temporal resolutions in remote sensing has greatly limited the availability of concurrently high spatiotemporal land surface temperature (LST) data for wide applications. Although many efforts have been made to resolve this dilemma, most have difficulties in generating diurnal fine-resolution LSTs with high spatial details for landscapes with significant heterogeneity and land cover type change. This study proposes an integrated framework to BLEnd Spatiotemporal Temperatures (termed BLEST) of Landsat, MODIS and a geostationary satellite (FY-2F) to one hour interval and 100 m resolution, where (1) a linear temperature mixing model with conversion coefficients is combined to better characterize heterogeneous landscapes and generate more accurate predictions for small and linear objects; (2) residuals are downscaled by a thin plate spline interpolator and restored to the primary fine-resolution estimations to include information about land cover type change; and (3) separate operations at annual and diurnal scales with nonlinear temperature modeling are designed to neutralize the hybrid impacts of large scale gap and land cover type change. BLEST was tested on both simulated data and actual satellite data at annual, diurnal and combined scales, and evaluations were conducted with the simulated/actual fine-resolution data, in-situ data, and with three popular fusion methods, i.e., the spatial and temporal adaptive reflectance fusion model (STARFM), the Enhanced STARFM (ESTARFM) and the spatiotemporal integrated temperature fusion model (STITFM). Results show higher accuracy by BLEST with more spatial details and pronounced temporal evolutions, particularly over heterogeneous landscapes and changing land cover types. BLEST is proposed to augment the spatiotemporal fusion system and further support diurnal dynamic studies in land surfaces.
资助项目	National Natural Science Foundation of China[41601462] ; National Natural Science Foundation of China[41590845] ; National Natural Science Foundation of China[41421001] ; Major State Basic Research Development Program of China[2015CB954101] ; Key Research Project on Frontier Science, CAS[QYZDY-SSW-DQC007-1] ; Youth Science Funds of LREIS, CAS[O8R8A083YA] ; Key Laboratory of Space Utilization, CAS[LSU-2016-06-03]
WOS关键词	URBAN HEAT-ISLAND ; REFLECTANCE FUSION MODEL ; SATELLITE DATA ; CLEAR-SKY ; SPARSE REPRESENTATION ; SPATIAL-RESOLUTION ; IMAGE FUSION ; TIME-SERIES ; MODIS DATA ; IN-SITU
WOS研究方向	Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology
语种	英语
出版者	ELSEVIER SCIENCE INC
WOS记录号	WOS:000427342700030
资助机构	National Natural Science Foundation of China ; Major State Basic Research Development Program of China ; Key Research Project on Frontier Science, CAS ; Youth Science Funds of LREIS, CAS ; Key Laboratory of Space Utilization, CAS
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/57224]
专题	中国科学院地理科学与资源研究所
通讯作者	Quan, Jinling
作者单位	1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 2.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100190, Peoples R China 3.Nanjing Univ, Int Inst Earth Syst Sci, Jiangsu Prov Key Lab Geog Informat Sci & Technol, Nanjing 210046, Jiangsu, Peoples R China 4.Natl Satellite Meteorol Ctr, Beijing 100081, Peoples R China 5.Chinese Acad Sci, Technol & Engn Ctr Space Utilizat, Key Lab Space Utilizat, Beijing 100094, Peoples R China
推荐引用方式 GB/T 7714	Quan, Jinling,Zhan, Wenfeng,Ma, Ting,et al. An integrated model for generating hourly Landsat-like land surface temperatures over heterogeneous landscapes[J]. REMOTE SENSING OF ENVIRONMENT,2018,206:403-423.
APA	Quan, Jinling,Zhan, Wenfeng,Ma, Ting,Du, Yunyan,Guo, Zheng,&Qin, Bangyong.(2018).An integrated model for generating hourly Landsat-like land surface temperatures over heterogeneous landscapes.REMOTE SENSING OF ENVIRONMENT,206,403-423.
MLA	Quan, Jinling,et al."An integrated model for generating hourly Landsat-like land surface temperatures over heterogeneous landscapes".REMOTE SENSING OF ENVIRONMENT 206(2018):403-423.