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Evaluation of Spatiotemporal Fusion Models in Land Surface Temperature Using Polar-Orbiting and Geostationary Satellite Data

文献类型： 会议论文

第一作者： Yitao Li

作者： Yitao Li 1 ; Hua Wu 1 ; Zhao-Liang Li 2 ; Sibo Duan 2 ; Li Ni 3 ;

作者机构： 1.University of Chinese Academy of Sciences, Beijing, China

2.Key Laboratory of Agricultural Remote Sensing, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Ministry of Agriculture, Beijing, China

3.Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China

关键词： Land surface temperature;Remote sensing;Spatial resolution;Temperature sensors;Spatiotemporal phenomena;Land surface;Prediction algorithms

会议名称： International Geoscience and Remote Sensing Symposium

主办单位：

页码： 236-239

摘要： The tradeoff between spatial and temporal resolution in satellite observations substantially restrains the potential applications of Land Surface Temperature (LST) products. So far, many spatiotemporal fusion models have been developed to address the issue and a unified comparison in LST data fusion is still required. In this paper, four popular spatiotemporal fusion algorithms including Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM), Unmixing-based data fusion method, Flexible Spatiotemporal Data Fusion (FSDAF) and Spatio-Temporal Integrated Temperature Fusion Model (STITFM) were adopted to generate high spatial resolution LST using polar-orbiting and geostationary satellite data. The predicted LST was evaluated by the actual LST product and the result indicates that the overall accuracy of FSDAF is satisfied (about 2.87K) and the FSDAF algorithm is recommended to generate LSTs at high spatial and temporal resolution in heterogeneous area.

分类号： tp7

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