Work

Measuring the Green Infrastructure Network Resilience: Based on Disturbance Scenario Simulations

Year: 2025

Type: article

Abstract: With rapid urban expansion and frequent natural disasters, green infrastructure (GI) networks are highly susceptible to disturbances and impacts. Improving the resilience of GI networks is important for maintaining species migration, improving ecological efficiency, and realizing sustainable development. Therefore, an effective GI network resilience measure must be constructed to measure it more accurately. There is a lack of current research that utilizes dynamic simulation methods to measure GI network resilience. This paper selects Jinan, China as the study area, uses morphological spatial pattern analysis and landscape connectivity analysis methods to select GI sources, and uses minimum cumulative resistance and the gravity model to construct the GI network. We construct the evaluation index of GI network resilience. Using this index to evaluate the GI network resilience to changes under various disturbance scenarios. The results show that the network resilience level is good. Networks exhibit different levels of resilience under random and intentional attack conditions. The nodes in the top 10% of the node degree value are critical to maintaining the operation of the network system. This paper expected that the network resilience evaluation method could be enriched and provide references for decision-makers to formulate sustainable urban development strategies.

Source: Ecosystem Health and Sustainability

DOI: 10.34133/ehs.0337

Authors: Xuan Wang, Jialu Shi, Chengxin Wang, Xumin Jiao

Institutions: Shandong Normal University, Shandong Women’s University, Henan University

Language: English

Topic: Wildlife-Road Interactions and Conservation

Subfield: Ecology

Field: Environmental Science

Domain: Physical Sciences

SDGs: Sustainable cities and communities, Life on land, Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $1,459