Establishing forest resilience indicators in the hilly red soil region of southern China from vegetation greenness and landscape metrics using dense Landsat time series
Establishing forest resilience indicators in the hilly red soil region of southern China from vegetation greenness and landscape metrics using dense Landsat time series
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利用密集 Landsat 时间序列从植被绿度和景观指标建立中国南方丘陵红壤地区的森林恢复力指标
DOI：
10.1016/j.ecolind.2020.106985
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发表时间：
2021-02
影响因子：
6.9
通讯作者：
Biyao Zhang
中科院分区：
文献类型：
--
作者：
Meiling Liu;Xiangnan Liu;Ling Wu;Yibo Tang;Yu Li;Yaqi Zhang;Lu Ye;Biyao Zhang
复原力是生态系统从损害或压力中作出反应和恢复的能力。它可以内在地表现出特定时期内受干扰生态系统恢复过程的循环和反馈。目前可获得密集和一致的时间序列卫星图像，这为监测森林复原力带来了希望。以衡阳盆地红壤丘陵区为研究对象，利用Landsat时间序列建立森林恢复力指标，并对最大干扰强度下的森林恢复力进行评价。为了实现这一目标，收集了1987年至2017年研究区域的Landsat图像。归一化植被指数（NDVI），即代表森林绿色特征的斑块数（NP）、平均斑块大小（PS）、斑块周长面积比（PPAR）和聚集指数（AI），即森林景观指标的代理计算从陆地卫星图像。然后是弹性（即，恢复的时间和速率），延展性（即，偏离初始状态的程度）和趋势（即，变化模式）作为森林复原力的指标。利用基于NDVI残差时空Moran's I（STI）的局部时空Moran's I（STI）来表征森林干扰和恢复过程。结果表明：首先，从密集的时间序列NDVI残差计算的STI是成功的监测森林干扰恢复过程中，无论是戏剧性的或微妙的变化。其次，大多数森林干扰（即，> 75%）发生在20世纪80年代末和90年代初。植被指数和景观指标也不同，在他们的干扰响应，植被指数，过氧化物酶体激活受体和AI是更可塑性的干扰比PS和NP。最后，约40%的受干扰森林具有较强的弹性，恢复时间较短（即，一年）。我们的结论是，测量森林恢复力，通过植被绿化和景观指标，使用密集的时间序列卫星图像是实用的操作工具，为决策者，土地所有者，和国家公园管理者。此外，对生态动态的洞察正在从捕捉过程中出现，显示变化前后的差异。
Resilience is the capacity of an ecosystem to respond and recover from damage or stress. It can inherently exhibit the cycle and feedback of the disturbed ecosystem recovery process for a specified period. The current availability of dense and consistent time series of satellite images holds the promise of monitoring forest resilience. The aim of this study is to establish forest resilience indicators using dense Landsat time series and assess forest resilience in response to the maximum disturbance magnitude in the hilly red soil region, Hengyang Basin, Southern China. To achieve this, Landsat images of the study area from 1987 to 2017 were collected. Normalized Difference Vegetation Index (NDVI), i.e., proxy of forest green characteristics, number of patch (NP), average patch size (PS), patch perimeter-area ratio (PPAR) and aggregation index (AI), i.e., proxies of forest landscape metrics were calculated from Landsat images. And then elasticity (i.e., the time and rate of recovery), malleability (i.e., degree of deviation from an initial state) and trend (i.e., the pattern of change) as the indicators of forest resilience were constructed. The local space–time Moran’s I (STI) based on NDVI residual space–time Moran’s I (STI) was employed to characterize the forest disturbance and recovery process. The results revealed the following. Firstly, the STI calculated from dense time series NDVI residuals are successful at monitoring the forest disturbance recovery process, regardless of whether changes were dramatic or subtle. Secondly, the most forest disturbances (i.e., > 75%) occurred in the late 1980s and early 1990s. NDVI and landscape metrics also differed in their response to disturbances; NDVI, PPAR and AI are more malleable to disturbance than PS and NP are. Finally, approximately 40% of the disturbed forest had the strong elasticity with a short recovery time (i.e., a year). We conclude that measuring forest resilience via vegetation greenness and landscape metrics using dense time series satellite images is practical as an operational tool for policy makers, landowners, and national park managers. Moreover, insights into ecological dynamics are emerging from capturing the process showing the difference both before and after the change.
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影响因子：
1.9
作者：
M. D. Behera;M. Murthy;P. Das;E. Sharma
通讯作者：
M. D. Behera;M. Murthy;P. Das;E. Sharma
影响因子：
13.5
作者：
DeVries, Ben;Verbesselt, Jan;Herold, Martin
通讯作者：
Herold, Martin
DOI：
--
发表时间：
2018
期刊：
--
影响因子：
--
作者：
L. Lekha
通讯作者：
L. Lekha
影响因子：
13.5
作者：
Ju, Junchang;Masek, Jeffrey G.
通讯作者：
Masek, Jeffrey G.
影响因子：
13.5
作者：
Czerwinski, Chris J.;King, Douglas J.;Mitchell, Scott W.
通讯作者：
Mitchell, Scott W.