EVALUATION OF SPATIOTEMPORAL FUSION MODELS IN LAND SURFACE TEMPERATURE USING POLAR-ORBITING AND GEOSTATIONARY SATELLITE DATA

文献类型： 外文期刊

第一作者： Li, Yitao

作者： Li, Yitao;Wu, Hua;Li, Yitao;Wu, Hua;Li, Zhao-Liang;Duan, Sibo;Li Ni

作者机构：

关键词： Land Surface Temperature; Polar-orbiting Satellite; Geostationary Satellite; Spatiotemporal Fusion; Comparison

期刊名称：IGARSS 2020 - 2020 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM

ISSN： 2153-6996

年卷期： 2020 年

页码：

收录情况： SCI

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.

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