Spatial Autocorrelation Analysis of Multi-Scale Damaged Vegetation in the Wenchuan Earthquake-Affected Area, Southwest China
Li, Jian1,2; He, Jingwen1; Liu, Ying1; Wang, Daojie3; Rafay, Loretta4; Chen, Can1,2; Hong, Tao1,2; Fan, Hailan1,2; Lin, Yongming1,2
刊名FORESTS
2019-02-01
卷号10期号:2页码:21
关键词Vegetation destruction Spatial autocorrelation Spatial autoregressive model Wenchuan earthquake Multi-scale
ISSN号1999-4907
DOI10.3390/f10020195
通讯作者Lin, Yongming(000q131082@fafu.edu.cn)
英文摘要Major earthquakes can cause serious vegetation destruction in affected areas. However, little is known about the spatial patterns of damaged vegetation and its influencing factors. Elucidating the main influencing factors and finding out the key vegetation type to reflect spatial patterns of damaged vegetation are of great interest in order to improve the assessment of vegetation loss and the prediction of the spatial distribution of damaged vegetation caused by earthquakes. In this study, we used Moran's I correlograms to study the spatial autocorrelation of damaged vegetation and its potential driving factors in the nine worst-hit Wenchuan earthquake-affected cities and counties. Both dependent and independent variables showed a positive spatial autocorrelation but with great differences at four aggregation levels (625 x 625 m, 1250 x 1250 m, 2500 x 2500 m, and 5000 x 5000 m). Shrubs can represent the characteristics of all damaged vegetation due to the significant linear relationship between their Moran's I at the four aggregation levels. Clustering of similar high coverage of damaged vegetation occurred in the study area. The residuals of the standard linear regression model also show a significantly positive autocorrelation, indicating that the standard linear regression model cannot explain all the spatial patterns in damaged vegetation. Spatial autoregressive models without spatially autocorrelated residuals had the better goodness-of-fit to deal with damaged vegetation. The aggregation level 8 x 8 is a scale threshold for spatial autocorrelation. There are other environmental factors affecting vegetation destruction. Our study provides useful information for the countermeasures of vegetation protection and conservation, as well as the prediction of the spatial distribution of damaged vegetation, to improve vegetation restoration in earthquake-affected areas.
资助项目National Natural Science Foundation of China[41471010] ; National Natural Science Foundation of China[41201564] ; Excellent Youth Talents Foundation of Fujian Agriculture and Forestry University[xjq2017016] ; Scientific and Technological Innovation Foundation of Fujian Agriculture and Forestry University[CXZX2016058]
WOS关键词CATASTROPHIC EARTHQUAKE ; RED HERRINGS ; LAND-USE ; LANDSLIDES ; RECOVERY ; RESTORATION ; DISTURBANCE ; IMPACTS ; HABITAT ; RIVER
WOS研究方向Forestry
语种英语
出版者MDPI
WOS记录号WOS:000460744000119
资助机构National Natural Science Foundation of China ; Excellent Youth Talents Foundation of Fujian Agriculture and Forestry University ; Scientific and Technological Innovation Foundation of Fujian Agriculture and Forestry University
内容类型期刊论文
源URL[http://ir.imde.ac.cn/handle/131551/25318]  
专题成都山地灾害与环境研究所_山地灾害与地表过程重点实验室
通讯作者Lin, Yongming
作者单位1.Fujian Agr & Forestry Univ, Coll Forestry, Fuzhou 350002, Fujian, Peoples R China
2.Key Lab Forest Ecosyst Proc & Management Fujian P, Fuzhou 350002, Fujian, Peoples R China
3.Chinese Acad Sci, Inst Mt Hazards & Environm, Chengdu 610041, Sichuan, Peoples R China
4.Antioch Univ Writers Exchange, Yellow Springs, OH 45387 USA
推荐引用方式
GB/T 7714
Li, Jian,He, Jingwen,Liu, Ying,et al. Spatial Autocorrelation Analysis of Multi-Scale Damaged Vegetation in the Wenchuan Earthquake-Affected Area, Southwest China[J]. FORESTS,2019,10(2):21.
APA Li, Jian.,He, Jingwen.,Liu, Ying.,Wang, Daojie.,Rafay, Loretta.,...&Lin, Yongming.(2019).Spatial Autocorrelation Analysis of Multi-Scale Damaged Vegetation in the Wenchuan Earthquake-Affected Area, Southwest China.FORESTS,10(2),21.
MLA Li, Jian,et al."Spatial Autocorrelation Analysis of Multi-Scale Damaged Vegetation in the Wenchuan Earthquake-Affected Area, Southwest China".FORESTS 10.2(2019):21.
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