Urban landscape patterns and residents’ perceptions of safety under extreme city flood disasters

Context: Urban areas are increasingly susceptible to extreme flooding events, posing significant challenges to residents’ safety and well-being. In this context, understanding the relationship between urban landscape patterns (ULP) and residents’ perceptions of safety (RPS) is crucial for effective...

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Main Authors: Wei Ma, Yingjie Du, Yuxiao Wang, Quanxiu Chen, Huaxiong Jiang, Runting Cai, Tianshun Gu, Wenxin Zhang
Format: Article
Language:English
Published: Elsevier 2025-01-01
Series:Ecological Indicators
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S1470160X24014602
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author Wei Ma
Yingjie Du
Yuxiao Wang
Quanxiu Chen
Huaxiong Jiang
Runting Cai
Tianshun Gu
Wenxin Zhang
author_facet Wei Ma
Yingjie Du
Yuxiao Wang
Quanxiu Chen
Huaxiong Jiang
Runting Cai
Tianshun Gu
Wenxin Zhang
author_sort Wei Ma
collection DOAJ
description Context: Urban areas are increasingly susceptible to extreme flooding events, posing significant challenges to residents’ safety and well-being. In this context, understanding the relationship between urban landscape patterns (ULP) and residents’ perceptions of safety (RPS) is crucial for effective flood disaster management. Objectives: This study explores the relationship between ULP and RPS during extreme flooding events, using Zhengzhou city as a case study. The goal is to offer strategic insights for managing extreme flood disasters. Methods: Surveying 1329 residents impacted by urban flooding in Zhengzhou, this study employed the Gradient Boosting Decision Tree (GBDT) model to examine the nonlinear relationship between ULP and RPS amidst extreme flood disasters. Results: Results indicate: (1) ULP significantly impacts RPS, with a relative importance of 44.8%, particularly influenced by the Largest Patch Index (LPI), Landscape Connectivity Index (CONTAG), and Patch Density (PD); (2) The effect of landscape pattern indices on RPS reveals a complex nonlinear relationship, exhibiting various patterns such as ’stage-wise negative correlation,’ ’U-shaped,’ and ’inverted V-shaped’ with noticeable threshold effects. The interaction effect also shows that the internal interplay of the ULP indicator, along with its interactions with flood-relevant contextual variables, significantly enhances RPS. (3) As covariates, flood impact and emergency resource accessibility also influence RPS with nonlinear trends. Conclusions: This study offers a new perspective on the relationship between ULP and RPS, emphasizing the critical role of flood response strategies tailored to ULP differences in enhancing RPS.
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spelling doaj-art-ee96f95daa764abba6e47a7da737cb202025-01-31T05:10:26ZengElsevierEcological Indicators1470-160X2025-01-01170113003Urban landscape patterns and residents’ perceptions of safety under extreme city flood disastersWei Ma0Yingjie Du1Yuxiao Wang2Quanxiu Chen3Huaxiong Jiang4Runting Cai5Tianshun Gu6Wenxin Zhang7Faculty of Geographical Science, Beijing Normal University, 100875 Beijing, ChinaFaculty of Geographical Science, Beijing Normal University, 100875 Beijing, ChinaFaculty of Geographical Science, Beijing Normal University, 100875 Beijing, ChinaFaculty of Geographical Science, Beijing Normal University, 100875 Beijing, ChinaFaculty of Geographical Science, Beijing Normal University, 100875 Beijing, China; Corresponding author at: Shengdi Building Room 550, No.19, Xinjiekouwai Street, Haidian District, Beijing 100875, China.Faculty of Geographical Science, Beijing Normal University, 100875 Beijing, ChinaDepartment of Atmospheric Science, School of Environmental Studies, China University of Geosciences, 430074 Wuhan, ChinaFaculty of Geographical Science, Beijing Normal University, 100875 Beijing, ChinaContext: Urban areas are increasingly susceptible to extreme flooding events, posing significant challenges to residents’ safety and well-being. In this context, understanding the relationship between urban landscape patterns (ULP) and residents’ perceptions of safety (RPS) is crucial for effective flood disaster management. Objectives: This study explores the relationship between ULP and RPS during extreme flooding events, using Zhengzhou city as a case study. The goal is to offer strategic insights for managing extreme flood disasters. Methods: Surveying 1329 residents impacted by urban flooding in Zhengzhou, this study employed the Gradient Boosting Decision Tree (GBDT) model to examine the nonlinear relationship between ULP and RPS amidst extreme flood disasters. Results: Results indicate: (1) ULP significantly impacts RPS, with a relative importance of 44.8%, particularly influenced by the Largest Patch Index (LPI), Landscape Connectivity Index (CONTAG), and Patch Density (PD); (2) The effect of landscape pattern indices on RPS reveals a complex nonlinear relationship, exhibiting various patterns such as ’stage-wise negative correlation,’ ’U-shaped,’ and ’inverted V-shaped’ with noticeable threshold effects. The interaction effect also shows that the internal interplay of the ULP indicator, along with its interactions with flood-relevant contextual variables, significantly enhances RPS. (3) As covariates, flood impact and emergency resource accessibility also influence RPS with nonlinear trends. Conclusions: This study offers a new perspective on the relationship between ULP and RPS, emphasizing the critical role of flood response strategies tailored to ULP differences in enhancing RPS.http://www.sciencedirect.com/science/article/pii/S1470160X24014602Flood disasterFlood risk managementNonlinear associationsPartial dependence plotZhengzhou
spellingShingle Wei Ma
Yingjie Du
Yuxiao Wang
Quanxiu Chen
Huaxiong Jiang
Runting Cai
Tianshun Gu
Wenxin Zhang
Urban landscape patterns and residents’ perceptions of safety under extreme city flood disasters
Ecological Indicators
Flood disaster
Flood risk management
Nonlinear associations
Partial dependence plot
Zhengzhou
title Urban landscape patterns and residents’ perceptions of safety under extreme city flood disasters
title_full Urban landscape patterns and residents’ perceptions of safety under extreme city flood disasters
title_fullStr Urban landscape patterns and residents’ perceptions of safety under extreme city flood disasters
title_full_unstemmed Urban landscape patterns and residents’ perceptions of safety under extreme city flood disasters
title_short Urban landscape patterns and residents’ perceptions of safety under extreme city flood disasters
title_sort urban landscape patterns and residents perceptions of safety under extreme city flood disasters
topic Flood disaster
Flood risk management
Nonlinear associations
Partial dependence plot
Zhengzhou
url http://www.sciencedirect.com/science/article/pii/S1470160X24014602
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