Abstract
The Wenchuan earthquake (Richter scale 8) on 12 May 2008 in southwestern China caused widespread ecosystem damage in the Longmenshan area. It is important to evaluate natural vegetation recovery processes and provide basic information on ecological aspects of the recovering environment after the earthquake. To circumvent the weather limits of remote sensing in the Wenchuan earthquake-hit areas, and to meet the need for regional observation analyses, three Landsat TM images pre- and post-earthquake in Mao County were used for analysis. Post-earthquake normalized difference vegetation index (NDVI) values were compared to pre-earthquake values with an NDVI-based index differencing method to determine the extent to which the vegetation was damaged in relation to the pre-earthquake pattern, and the rate of recovery was evaluated. The spatial characteristics of vegetation loss and natural recovery patterns were analyzed in relation to elevation, slope and aspect. The results indicated that severely damaged sites occurred mainly in river valleys, within a range of 1,500–2,500 m elevation and on slopes of 25–55°. The distance from rivers, rather than the distance from active faults, controls the damage patterns. After 1 year of natural regeneration, 36 % of the destroyed areas showed a decrease in NDVI value, 28.8 % showed very little change, 19.1 % showed an increase, and 16.1 % also increased with a recovery rate greater than 100 %. Moreover, there is a good correlation between recovery rate and both slope and elevation, but recovery patterns in the damaged area are complicated. Our results indicate that natural recovery in this arid valley is a slow process.
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Acknowledgments
This work was supported in part by the Knowledge Innovation Program of the Chinese Academy of Sciences (Grant No. KSCX2-YW-Z-0959 and KSCX2-EW-J-22) and the National Natural Science Foundation of China (Grant No. 30900214).
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Lu, T., Zeng, H., Luo, Y. et al. Monitoring vegetation recovery after China’s May 2008 Wenchuan earthquake using Landsat TM time-series data: a case study in Mao County. Ecol Res 27, 955–966 (2012). https://doi.org/10.1007/s11284-012-0976-y
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DOI: https://doi.org/10.1007/s11284-012-0976-y