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• W1979138737 abstract "Vegetation plays an important role in atmospheric, hydrologic and biochemical cycles and is an important indicator of the impact of climate and human factors on the environment. In this paper, a method, which combines the empirical orthogonal function (EOF) and temporal unmixing analysis (TUA) methods, is applied to monitor the phenological characteristcs and spatial distribution of vegetation phenology in the middle part of the Huai River region. Based on the variance and EOF curves, the EOF provides the number of phenology modes, information which is the basis for an accurate temporal unmixing model. The TUA describes the temporal vegetation phenological details and spatial distribution. Importantly, this approach does not require assumptions, prior information or pre-defined thresholds. The vegetation phenology curves derived from the MODIS EVI data using the combined EOF and TUA methods display much more detail than the curves from Landsat TM using spectral mixture analysis (SMA). Additionally, the vegetation phenology spatial distribution from MODIS EVI is consistent with the field survey data. The combination method of EOF and TUA can be used to monitor vegetation phenology spatiotemporal change in a large area from time series of MODIS EVI data." @default.
• W1979138737 created "2016-06-24" @default.
• W1979138737 creator A5018695810 @default.
• W1979138737 creator A5025029481 @default.
• W1979138737 date "2015-03-09" @default.
• W1979138737 modified "2023-10-02" @default.
• W1979138737 title "Detection and Modeling of Vegetation Phenology Spatiotemporal Characteristics in the Middle Part of the Huai River Region in China" @default.
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• W1979138737 doi "https://doi.org/10.3390/su7032841" @default.
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