Measuring the Green Infrastructure Network Resilience: Based on Disturbance Scenario Simulations
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 develop...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
American Association for the Advancement of Science (AAAS)
2025-01-01
|
| Series: | Ecosystem Health and Sustainability |
| Online Access: | https://spj.science.org/doi/10.34133/ehs.0337 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850238686840487936 |
|---|---|
| author | Xuan Wang Jialu Shi Chengxin Wang Xumin Jiao |
| author_facet | Xuan Wang Jialu Shi Chengxin Wang Xumin Jiao |
| author_sort | Xuan Wang |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-77f8238fbda1469183b2b4c6d462f5e8 |
| institution | OA Journals |
| issn | 2332-8878 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | American Association for the Advancement of Science (AAAS) |
| record_format | Article |
| series | Ecosystem Health and Sustainability |
| spelling | doaj-art-77f8238fbda1469183b2b4c6d462f5e82025-08-20T02:01:24ZengAmerican Association for the Advancement of Science (AAAS)Ecosystem Health and Sustainability2332-88782025-01-011110.34133/ehs.0337Measuring the Green Infrastructure Network Resilience: Based on Disturbance Scenario SimulationsXuan Wang0Jialu Shi1Chengxin Wang2Xumin Jiao3College of Geography and Environment, Shandong Normal University, Jinan 250358, China.College of Tourism, Shandong Women’s University, Jinan 250358, China.College of Geography and Environment, Shandong Normal University, Jinan 250358, China.College of Geography and Environment, Shandong Normal University, Jinan 250358, China.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.https://spj.science.org/doi/10.34133/ehs.0337 |
| spellingShingle | Xuan Wang Jialu Shi Chengxin Wang Xumin Jiao Measuring the Green Infrastructure Network Resilience: Based on Disturbance Scenario Simulations Ecosystem Health and Sustainability |
| title | Measuring the Green Infrastructure Network Resilience: Based on Disturbance Scenario Simulations |
| title_full | Measuring the Green Infrastructure Network Resilience: Based on Disturbance Scenario Simulations |
| title_fullStr | Measuring the Green Infrastructure Network Resilience: Based on Disturbance Scenario Simulations |
| title_full_unstemmed | Measuring the Green Infrastructure Network Resilience: Based on Disturbance Scenario Simulations |
| title_short | Measuring the Green Infrastructure Network Resilience: Based on Disturbance Scenario Simulations |
| title_sort | measuring the green infrastructure network resilience based on disturbance scenario simulations |
| url | https://spj.science.org/doi/10.34133/ehs.0337 |
| work_keys_str_mv | AT xuanwang measuringthegreeninfrastructurenetworkresiliencebasedondisturbancescenariosimulations AT jialushi measuringthegreeninfrastructurenetworkresiliencebasedondisturbancescenariosimulations AT chengxinwang measuringthegreeninfrastructurenetworkresiliencebasedondisturbancescenariosimulations AT xuminjiao measuringthegreeninfrastructurenetworkresiliencebasedondisturbancescenariosimulations |