An integrated model for generating hourly Landsat-like land surface temperatures over heterogeneous landscapes
文献类型：期刊论文
| 作者 | Quan, Jinling1,4; Zhan, Wenfeng5; Ma, Ting1,4; Du, Yunyan1,4; Guo, Zheng2; Qin, Bangyong3 |
| 刊名 | REMOTE SENSING OF ENVIRONMENT
 |
| 出版日期 | 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. |
| 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 |
| 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研究方向 | Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:000427342700030 |
| 出版者 | ELSEVIER SCIENCE INC |
| 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 |
| 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.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100190, Peoples R China 2.Natl Satellite Meteorol Ctr, Beijing 100081, Peoples R China 3.Chinese Acad Sci, Technol & Engn Ctr Space Utilizat, Key Lab Space Utilizat, Beijing 100094, Peoples R China 4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 5.Nanjing Univ, Int Inst Earth Syst Sci, Jiangsu Prov Key Lab Geog Informat Sci & Technol, Nanjing 210046, Jiangsu, 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. |
入库方式： OAI收割
来源：地理科学与资源研究所
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