Improving the spatiotemporal fusion accuracy of fractional vegetation cover in agricultural regions by combining vegetation growth models

Improving the spatiotemporal fusion accuracy of fractional vegetation cover in agricultural regions by combining vegetation growth models

Spatiotemporal fusion has provided a feasible way to generate fractional vegetation cover (FVC) data with high spatial and temporal resolution. However, when the currently available spatiotemporal fusion methods are applied over agricultural regions, they usually underestimate high FVC values at the...

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Bibliographic Details
Main Authors: Guofeng Tao, Kun Jia, Xiangqin Wei, Mu Xia, Bing Wang, Xianhong Xie, Bo Jiang, Yunjun Yao, Xiaotong Zhang
Format: Article
Language:English
Published: Elsevier 2021-09-01
Series:International Journal of Applied Earth Observations and Geoinformation
Subjects:
Spatiotemporal fusion
Vegetation growth model
Fractional vegetation cover
GF-1 WFV
Online Access:http://www.sciencedirect.com/science/article/pii/S0303243421000696

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http://www.sciencedirect.com/science/article/pii/S0303243421000696

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