Article(id=1281678087834284955, tenantId=1146029695717560320, journalId=1281213114968444942, issueId=1281678071572968253, articleNumber=null, orderNo=null, doi=10.19775/j.cla.2026.03.0115, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1706198400000, receivedDateStr=2024-01-26, revisedDate=1746547200000, revisedDateStr=2025-05-07, acceptedDate=null, acceptedDateStr=null, onlineDate=1783505468567, onlineDateStr=2026-07-08, pubDate=1773072000000, pubDateStr=2026-03-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1783505468567, onlineIssueDateStr=2026-07-08, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1783505468567, creator=13701087609, updateTime=1783505468567, updator=13701087609, issue=Issue{id=1281678071572968253, tenantId=1146029695717560320, journalId=1281213114968444942, year='2026', volume='42', issue='3', pageStart='6', pageEnd='152', issueExtLink='null', onlineDate='null', pubDate='1773072000000', pubDateStr='2026-03-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1783505464690, creator='13701087609', updateTime=1783507756103, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1281687682514399699, tenantId=1146029695717560320, journalId=1281213114968444942, issueId=1281678071572968253, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1281687682514399700, tenantId=1146029695717560320, journalId=1281213114968444942, issueId=1281678071572968253, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=115, endPage=123, ext={EN=ArticleExt(id=1281678088031417244, articleId=1281678087834284955, tenantId=1146029695717560320, journalId=1281213114968444942, language=EN, title=Spatial Identification and Representation of Damaged Landscapes in Coastal City Zones: A Case Study of the Yancheng Coastal Zone, columnId=1281678085766484902, journalTitle=Chinese Landscape Architecture, columnName=LA Ecological, runingTitle=null, highlight=null, articleAbstract=

Addressing the Land-Sea Coordination plan and the development of resilient cities, the systematic identification and dynamic evaluation of damaged coastal landscape areas have increasingly emerged as critical concerns for the high-quality advancement of coastal city landscapes in China. Damaged space, which exhibits clear signs of problems such as reduced function, weakened structure, and lower health in coastal landscapes, is the primary target for assessing the quality and strength of urban coastal areas. In recent years, mechanisms for evaluating environmental quality, exemplified by Urban Physical Examination, have been progressively and comprehensively refined. These identified mechanisms may offer technical support for the identification, assessment, and management of degraded landscape areas and facilitate the transition of coastal landscape research from static evaluation to systematic diagnosis and targeted governance. Despite the rapid advancement of spatial analysis and prediction technologies, it is of paramount importance to develop quantitative, parameterized methods and tools tailored to the needs of damaged landscapes. This development is essential for the precise identification, characterization, and analysis of coastal landscape damage, as well as for effectively interpreting driving mechanisms and ultimately improving the efficacy of decision-making in urban coastal landscape regulation strategies. This study addresses current challenges in research on damaged coastal landscapes, including insufficient systematic analysis, incomplete identification systems, low simulation accuracy, and unclear regulatory strategies. This study integrates landscape resilience theory with existing research in landscape ecology. The researcher concentrates explicitly on elucidating the dynamic evolution patterns inherent in coastal city landscapes and seeks to establish a robust technical framework for the identification and representation of damaged coastal landscape spaces. Regarding the research methodology, the PLUS model is adopted to develop a dynamic simulation and representation analysis system that is specifically designed for landscape degradation. By leveraging GIS platforms to integrate land-use transfer matrix analysis and spatial autocorrelation techniques, this study distills core degradation trends and reveals spatial aggregation patterns. Additionally, it incorporates both single-factor and interaction-detection algorithms from geographic detector models to conduct precise identification, dynamic simulation, and mechanistic analysis of degradation spaces within urban coastal landscapes. In terms of empirical investigation, the researcher specifically selected the coastal zone of Yancheng City in Jiangsu Province to conduct a representative case study. Specifically, landscape-type data spanning 2010-2020, together with a comprehensive database of natural and socio-economic driving factors, were used for the assessment. The PLUS model and geographic detector were employed to simulate and analyze the evolutionary trajectories and spatial clustering characteristics of degraded areas. The analytical process then examined the pathways of landscape transformation and assessed the impacts of various driving processes. The empirical findings of this study reveal that damaged landscape areas within the study region exhibit a general spatial pattern characterized by aggregation along the coastline and expansion toward the interior. Specific locales, including coastal wetlands, reclaimed land areas, and the peripheries of urban expansion zones, are identified as notably high-value clusters of landscape degradation. Among natural landscape types, forests and wetlands have undergone considerable damage. The results from factor detection indicate that vegetation cover scale, climatic temperature conditions, population density, and land-use changes are the primary determinants of the evolution of degraded areas. These factors demonstrate not only significant individual explanatory power but also notable synergistic effects and interactive influences. Consequently, restoration and rehabilitation initiatives should be executed in a scientifically coordinated manner. In addition, strategic focus should be directed towards the multi-level governance of affected landscape areas and the integrated management of the principal driving variables and their interaction mechanisms. This paper presents a methodological framework for identifying and representing damaged coastal landscapes using the PLUS model. This framework allows researchers to perform accurate detection and simulation of damaged areas by integrating multi-source spatiotemporal data. Apart from that, the proposed approach offers robust technical support for the systematic diagnosis and strategic spatial planning of urban coastal landscapes. Furthermore, this paper provides a replicable methodological reference for future practices in landscape assessment, monitoring, and regulatory decision-making. The study results can also offer contributions to the broader goals of sustainable coastal zone management and resilient urban development.

, authors=Bingyu HOU, Zhe LI^*, Xinying WU, Yulong ZHAO, Haonan DING, authorsList=Bingyu HOU, Zhe LI, Xinying WU, Yulong ZHAO, Haonan DING, authorCompany=null, correspAuthors=Zhe LI, authorNote=, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1281678088333407133, articleId=1281678087834284955, tenantId=1146029695717560320, journalId=1281213114968444942, language=CN, title=城市海岸景观受损空间识别及其表征研究——以盐城市海岸带为例, columnId=1281678087498732456, journalTitle=中国园林, columnName=风景园林生态, runingTitle=null, highlight=null, articleAbstract=

面向陆海统筹战略与韧性城市建设，系统开展海岸带景观受损空间精准识别与研判，已成为当前城市海岸景观高质量发展的前置问题，相关分析方法有待进一步发展。基于韧性景观研究基础，构建适用于海岸带景观受损空间量化识别与动态表征的分析框架，依托PLUS模型开展海岸带景观受损空间模拟与解析。以盐城市海岸带为例，协同GIS空间统计与地理探测器技术，结合转移矩阵与空间自相关分析，集成2010—2020年数据开展海岸带景观受损空间的量化识别与动态解析实践探索，为海岸带景观策略制定提供分析依据。实证结果表明，研究区受损空间的演变特征呈沿海集聚、梯度扩张的演变特征，在沿海湿地、围垦区及城市扩张区域受损严重，植被规模、气候温度、人口规模及用地类型调整显著影响受损空间变化，受损景观区域的修复与优化有赖于景观空间分区调控的系统开展。研究成果为滨海城市海岸景观的科学管控与可持续治理提供分析基础与参考案例。

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HOU Bingyu, female, born in 1998 in Heze, Shandong Province, Ph.D. candidate of Department of Landscape Architecture, School of Architecture, Southeast University, research area: garden and landscape design (Nanjing 210096)

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HOU Bingyu, female, born in 1998 in Heze, Shandong Province, Ph.D. candidate of Department of Landscape Architecture, School of Architecture, Southeast University, research area: garden and landscape design (Nanjing 210096)

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侯冰钰　1998年生/女/山东菏泽人/东南大学建筑学院景观学系在读博士研究生/研究方向为风景园林规划与设计（南京 210096）

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侯冰钰　1998年生/女/山东菏泽人/东南大学建筑学院景观学系在读博士研究生/研究方向为风景园林规划与设计（南京 210096）

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LI Zhe, male, born in 1976 in Daqing, Heilongjiang Province, Head, Professor, and Doctoral Supervisor of Department of Landscape Architecture, School of Architecture, Southeast University, research area: garden and landscape design, digital landscape and technology (Nanjing 210096)

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LI Zhe, male, born in 1976 in Daqing, Heilongjiang Province, Head, Professor, and Doctoral Supervisor of Department of Landscape Architecture, School of Architecture, Southeast University, research area: garden and landscape design, digital landscape and technology (Nanjing 210096)

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李哲　1976年生/男/黑龙江大庆人/东南大学建筑学院景观学系系主任，教授，博士生导师/研究方向为园林与景观设计、数字景观及其技术（南京 210096）

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李哲　1976年生/男/黑龙江大庆人/东南大学建筑学院景观学系系主任，教授，博士生导师/研究方向为园林与景观设计、数字景观及其技术（南京 210096）

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WU Xinying, female, born in 2002 in Zhongshan, Guangdong Province, Master's student of Department of Landscape Architecture, School of Architecture, Southeast University, research area: digital landscape and technology (Nanjing 210096)

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WU Xinying, female, born in 2002 in Zhongshan, Guangdong Province, Master's student of Department of Landscape Architecture, School of Architecture, Southeast University, research area: digital landscape and technology (Nanjing 210096)

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吴欣莹　2002年生/女/广东中山人/东南大学建筑学院景观学系在读硕士研究生/研究方向为数字景观及其技术（南京 210096）

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吴欣莹　2002年生/女/广东中山人/东南大学建筑学院景观学系在读硕士研究生/研究方向为数字景观及其技术（南京 210096）

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ZHAO Yulong, male, born in 2000 in Shiyan, Hubei Province, Master's student of Department of Landscape Architecture, School of Architecture, Southeast University, research area: garden and landscape design (Nanjing 210096)

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ZHAO Yulong, male, born in 2000 in Shiyan, Hubei Province, Master's student of Department of Landscape Architecture, School of Architecture, Southeast University, research area: garden and landscape design (Nanjing 210096)

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赵玉龙　2000年生/男/湖北十堰人/东南大学建筑学院景观学系在读硕士研究生/研究方向为园林与景观设计（南京 210096）

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赵玉龙　2000年生/男/湖北十堰人/东南大学建筑学院景观学系在读硕士研究生/研究方向为园林与景观设计（南京 210096）

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DING Haonan, male, born in 2001 in Nanjing, Jiangsu Province, Master's student of Department of Landscape Architecture, School of Architecture, Southeast University, research area: garden and landscape design (Nanjing 210096)

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DING Haonan, male, born in 2001 in Nanjing, Jiangsu Province, Master's student of Department of Landscape Architecture, School of Architecture, Southeast University, research area: garden and landscape design (Nanjing 210096)

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丁昊楠　2001年生/男/江苏南京人/东南大学建筑学院景观学系在读硕士研究生/研究方向为园林与景观设计（南京 210096）

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丁昊楠　2001年生/男/江苏南京人/东南大学建筑学院景观学系在读硕士研究生/研究方向为园林与景观设计（南京 210096）

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