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A MODIS-based method for detecting large-scale vegetation disturbance due to natural hazards: a case study of Wenchuan earthquake stricken regions in China

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Abstract

In the global carbon cycle, terrestrial biomass plays an important role in both as a sink and source. To evaluate biomass variation due to various natural hazards, it is necessary to detect the location, extent and duration of vegetation disturbance at a large spatial scale with an efficient method. This study contributes to develop such a method, and only the moderate resolution imaging spectroradiometer (MODIS) MOD13Q1 enhanced vegetation index (EVI) products are used to generate a continuous vegetation damage index (CVDI) for detecting severe vegetation disturbance in large areas. To verify the performance of this new index, this study takes the identification of the vegetation damage due to the Wenchuan earthquake in China occurred on 12 May 2008 as a case study. This study calculates the CVDI for the earthquake stricken areas, and delineates the regions with considerable EVI abnormal variation. The study result reveals that those delineated regions with severe vegetation damage are normally consistent with the areas with the landslides caused by the earthquake. Moreover, according to the changes of other vegetation-related MODIS datasets since 12 May 2008, this study discloses that the EVI value in most of the areas, where the vegetation was damaged due to the earthquake, has not reached to the normal value in 2012, which is 4 years after the earthquake. Finally, to validate the vegetation damage areas determined by CVDI method, the high resolution images and field survey information are used. This study confirms that CVDI method can effectively delineate large-scale terrestrial biomass disturbance due to the earthquake and can accurately identify the vegetation recovery process.

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Acknowledgments

We are grateful to the anonymous reviewers who offered insightful comments that led to improvements of this paper. The study is financially support by one General Research Fund (GRF) Project (No.: HKU 710712E) from the Research Grants Council of Hong Kong and a NSFC Project (No.: 51479224).

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Author notes

  1. Liqun Sun

    Present address: Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

Authors and Affiliations

  1. Department of Civil Engineering, The University of Hong Kong, Pokfulam, Hong Kong, China

    Liqun Sun & Ji Chen

  2. State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing, 100084, China

    Tiejian Li

Authors
  1. Liqun Sun
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  2. Ji Chen
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  3. Tiejian Li
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Correspondence to Ji Chen.

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Sun, L., Chen, J. & Li, T. A MODIS-based method for detecting large-scale vegetation disturbance due to natural hazards: a case study of Wenchuan earthquake stricken regions in China. Stoch Environ Res Risk Assess 30, 2243–2254 (2016). https://doi.org/10.1007/s00477-015-1160-z

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