Multi-dimensional landscape ecological risk assessment and its drivers in coastal areas

被引:16
|
作者
Xu, Menglin [1 ]
Matsushima, Hajime [2 ]
机构
[1] Hokkaido Univ, Grad Sch Agr, Kita 9 Nishi 9,Kita Ward, Sapporo, Hokkaido 0608589, Japan
[2] Hokkaido Univ, Res Fac Agr, Kita 9 Nishi 9,Kita Ward, Sapporo, Hokkaido 0608589, Japan
关键词
The 2011 Great East Japan Earthquake and; Tsunami disaster; Spatial cluster analysis; Spatial principal component analysis; PRINCIPAL COMPONENT ANALYSIS; LAND-USE; SPATIAL AUTOCORRELATION; SCALE; REGIONALIZATION; MULTISCALE; VEGETATION; SECURITY; PATTERNS; MODELS;
D O I
10.1016/j.scitotenv.2023.168183
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The eastern coastal areas of Japan are threatened by multiple ecological risks due to frequent natural disasters, climate changes, human activities, etc. Identification spatio-temporal variations and driving mechanisms of landscape ecological risk could be used as significant basis for policymakers. In this study, taking the eastern coastal areas of Japan affected by the 2011 Great East Japan Earthquake and Tsunami Disaster as the study area, the "Nature-Landscape Pattern-Human Society" (NA-LP-HS) multi-dimensional ecological risk assessment framework was established to analyze the spatio-temporal patterns, and identity driving factors using spatial cluster analysis and spatial principal component analysis (SPCA) based on ArcGIS from 2009 to 2021. The findings revealed the distinct geographic patterns in landscape ecological risk, with a noticeable decline from the southwest to the northeast. During the period from 2009 to 2015, the driving factors leading to a sharp risk increase were natural disasters and vegetation coverage. These high-risk areas were concentrated in Sendai Bay and its surroundings. From 2015 to 2021, ecological instability was primarily attributed to a reduction in vegetation coverage, the occurrence of natural disasters, and heightened rainfall erosion. These high-risk areas were mainly clustered within the Tokyo-centered urban agglomeration. Spatial clustering of ecological risks was obvious across all time periods. The key factors contributing to the clustering of high ecological landscape risks focused on the "landscape pattern" criterion, specifically including vegetation coverage, land use land cover. This study demonstrated the ability of multi-dimensional ecological risk assessment to identify high-risk areas and driving factors, and these results could provide a visual analysis and decision-making basis for sustainable development of coastal areas.
引用
收藏
页数:12
相关论文
共 50 条
  • [41] Multi-Dimensional Assessment in Idiopathic Pulmonary Fibrosis
    Serajeddini, Hana
    Mura, Marco
    Rogliani, Paola
    CHEST, 2017, 152 (04) : 446A - 446A
  • [42] WAVE RISK ASSESSMENT ON COASTAL AREAS IN KOREA
    OH, H. M.
    Jeong, K. Y.
    Kim, H. K.
    Lee, E.
    Hwang, S. M.
    Kim, S. M.
    Kang, T. S.
    PROCEEDINGS OF THE 10TH INTERNATIONAL CONFERENCE ON ASIAN AND PACIFIC COASTS, APAC 2019, 2020, : 1351 - 1358
  • [43] Neural network based multi-dimensional and nonlinear landscape design
    Chen, Yang
    Xie, Yihuai
    JOURNAL OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING, 2023, 23 (03) : 1279 - 1293
  • [44] Nitrogen deposition and multi-dimensional plant diversity at the landscape scale
    Roth, Tobias
    Kohli, Lukas
    Rihm, Beat
    Amrhein, Valentin
    Achermann, Beat
    ROYAL SOCIETY OPEN SCIENCE, 2015, 2 (04):
  • [45] A General-Purpose Multi-Dimensional Convex Landscape Generator
    Liu, Wenwen
    Yuen, Shiu Yin
    Chung, Kwok Wai
    Sung, Chi Wan
    MATHEMATICS, 2022, 10 (21)
  • [46] Mapping Out the Landscape: A Multi-dimensional Approach to Behavioral Innovation
    Brown, Rachael L.
    PHILOSOPHY OF SCIENCE, 2022, 89 (05) : 1176 - 1185
  • [47] The Implementation and Development of Landscape Design and Ecological Environment Standardization in Coastal Residential Areas
    He, Meilin
    JOURNAL OF COASTAL RESEARCH, 2020, : 55 - 58
  • [48] On a multi-dimensional risk model with regime switching
    Wang, Guanqing
    Wang, Guojing
    Yang, Hailiang
    INSURANCE MATHEMATICS & ECONOMICS, 2016, 68 : 73 - 83
  • [49] Multi-dimensional risk and the cost of business cycles
    Krebs, Tom
    REVIEW OF ECONOMIC DYNAMICS, 2006, 9 (04) : 640 - 658
  • [50] Clustering for multi-dimensional data and its visualization
    Ren, Y.-G. (renyg@dl.cn), 1861, Science Press (28):