Vegetation restoration and dynamic evolution analysis of landslide activity in the Wenchuan Earthquake area
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摘要: 强烈的山区地震往往会引发大量同震滑坡，对当地植被覆盖和生长造成直接破坏。作为表现滑坡活动强度的重要指标，同震滑坡体表面的植被恢复情况对评估震后地质灾害的活动情况具有重要意义。然而，受观测资料所限，当前对于震区植被恢复进程的研究多为小尺度范围，而对大区域内植被演化机制以及植被与地质灾害活动性的关系认识不足。因此，采用多时相、长时序（2000—2020年）的高精度遥感影像对汶川地震强震区大范围内的植被恢复过程进行研究，计算得到不同时期植被恢复率，以此探究大范围内植被恢复的普适性规律，同时分析植被恢复与滑坡活动强度变化的关系。研究发现：截至2020年，71.34%区域的同震滑坡表面植被已处于恢复程度较好阶段；高活动强度、中活动强度、低活动强度和基本稳定的滑坡面积比分别为17.6%、12.4%、17.7%和52.3%。同震滑坡地表恢复趋势表明，汶川震区植被预计在震后约17 a恢复至震前平均水平。然而，植被恢复过程和滑坡活动性的变化往往受多种因素的综合影响。虽然滑坡地表植被恢复在一定程度上反映了地震后滑坡活动性的下降，但地震对滑坡活动性的影响将比地表植被恢复到震前水平所持续的时间更长。参考前人研究成果，本研究认为震后滑坡活动将持续25 a或更长时间。研究成果可为汶川震区震后地质灾害评估、防治工作提供参考。Abstract: A great mountain seismic often triggers a large number of co-seismic landslides, causing direct damage to local vegetation cover and growth. As an important indicator of landslide activity intensity, the vegetation recovery is of great significance for the activity of post-earthquake geo-hazards. However, due to the limitation of observational data, the current research on vegetation restoration process in earthquake areas is mostly on a small scale. In addition, there is insufficient understanding of the vegetation evolution mechanism in a large area and the relationship between vegetation and the activity of geological disasters. Therefore, this paper uses multi-temporal and long-time series (2000−2020) high-precision remote sensing images to study the vegetation restoration process in the Wenchuan earthquake area. By calculating vegetation recovery rates in different periods, we explore the universal law of vegetation restoration in a large range, and analyze the relationship between vegetation restoration and the change of landslide activity intensity. The results show that by 2020, 71.34% of the landslide area in the earthquake area has been better restored. The proportions of highly active, moderately active, low active and basically stable landslides are 17.6%, 12.4%, 17.7% and 52.3%, respectively. The surface recovery trend of co-seismic landslide indicates that the vegetation in the Wenchuan earthquake area is expected to recover to the pre-earthquake average level about 17 years after the earthquake. However, the process of vegetation recovery and changes in landslide activity are often subject to the combined effects of multiple factors. Although the vegetation recovery of landslide surface reflects the decline of landslide activity after the earthquake to some extent, the effects of the earthquake on landslide activity will last longer than the recovery of surface vegetation to the pre-earthquake level. Referring to the results of previous studies, this paper suggests that the post-earthquake landslide activity will last 25 years or more.The conclusion can provide reference for the assessment and prevention of post earthquake geological disasters in Wenchuan earthquake area.
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Key words:
- Wenchuan earthquake /
- co-seismic landslide /
- vegetation restoration /
- landslide activity
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图 2 2000—2020年间平均NDVI（误差线代表NDVI的标准差）
Figure 2. Average NDVI from 2000 to 2020 （error bars represent standard deviation of NDVI）
图 4 2009—2020年间不同VRR类型面积及所占百分比
Figure 4. Area and percentage of different VRR types from 2009 to 2020
图 5 汶川地区典型区域植被恢复情况空间分布情况示意图
Figure 5. Representative example of the spatial distribution of vegetation restoration in the Wenchuan area
图 6 清平地区典型区域植被恢复情况空间分布情况示意图
Figure 6. Representative example of the spatial distribution of vegetation restoration in the Qingping area
图 7 北川地区典型区域植被恢复情况空间分布情况示意图
Figure 7. Representative example of the spatial distribution of vegetation restoration in the Beichuan area
图 9 历年滑坡活动强度统计
Figure 9. Statistics on the intensity of landslide activities over the years
图 10 不同规模滑坡活动性演化趋势
Figure 10. Evolution trend of landslide activity of different scales
图 11 持续向沟道输送物质的巨大型滑坡
Figure 11. Landslide materials continuing to transfer downstream from giant landslides
图 12 植被恢复与滑坡活动性动态响应
Figure 12. Post-earthquake vegetation and landslide activity evolution trends
表 1 基础数据来源统计
Table 1. Statistic of the basic data source
类型 数据来源 收集时间 分辨率 用途 遥感影像 Landsat5 2000—2010年 30 m 提取NDVI Landsat7 2011—2013年 Landsat8 2014—2020年 同震滑坡数据集 Tang等[21] 2009年3月 — 研究对象 地形数据 https://earthdata.nasa.gov/ — 30 m 因子分析 降雨 https://giovanni.gsfc.nasa.gov/giovanni/ 2008—2019年 0.25° 岩性 成都理工大学地质灾害防治与地质环境保护国家重点实验室 — — 
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