Marine Science Faculty Publications

Long-term Vegetation Changes in Four Types of Wetland in China and USA Between 2000 and 2011: Observations from MODIS

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Wetland vegetation assessment is a critical component of evaluating wetland protective policies and providing useful information for global climate change research. In this study, four types of wetland are chosen to evaluate their long-term changes and potential linkage to anthropogenic (e. g., agricultural activities) and natural influences (e. g., hydrometeorological effects). These wetland types include the Yancheng wetland (coastal wetland), the Chongming wetland (river wetland), the Hongze Lake wetland (lake wetland) and the Everglades wetland (marsh wetland) in the contrasting environments of China and USA. The vegetation coverages of these wetlands were evaluated from 2000 to 2011 by using over 2,200 Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m resolution images. Four vegetation indices (VIs) were compared to evaluate their effectiveness in assessing relative changes: the Normalized Difference Vegetation Index (NDVI), the Floating Algae Index (FAI), the Enhanced Vegetation Index (EVI), and the Visible Atmospherically Resistance Index (VARI). FAI performance was relatively insensitive in terms of both the statistical error and the aerosol effects compared with other VIs and was thus chosen to study the long-term vegetation changes. The results showed that 1) agricultural influence appeared to be relatively minimal compared with hydrometeorological effects in the Everglades wetland and in the core partitions of the Yancheng, Chongming, and Hongze Lake wetlands over the 12-year period, and 2) the entire partitions of the Yancheng, Chongming and Hongze Lake wetlands showed noticeable influences from agricultural activities in addition to natural variability. The cost-effective method that we demonstrate in this study may be extended to other wetlands near the same geographical location and to other satellite platforms.

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International Journal of Remote Sensing, v. 40, issue 11, p. 4302-4325