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Optimization model for urban ecological network connectivity considering geospatial constraints

Authors :
Wuyang Hong
Yuke Liu
Weixi Wang
Minde Liang
Renzhong Guo
Source :
Geo-spatial Information Science, Pp 1-14 (2024)
Publication Year :
2024
Publisher :
Taylor & Francis Group, 2024.

Abstract

Connectivity enhancement of ecological networks is an efficient and advantageous spatial planning strategy, and it is a hot research topic to analyze ecological networks based on complex systems theory and perform model optimization. As a typical geographic network, the evolution process of ecological network, such as node and edge growth, will be subject to geospatial constraints, and the current research lacks optimization models that take the geospatial constraints into account. This study focused on urban ecological network connectivity and the distribution of nodes as well as structural fractures where the connectivity of the ecological network was hindered were analyzed. Then it introduced a local world network model to optimize network connectivity and designed a network growth mechanism with limited added nodes and optimal connections. An ecological network optimization model considering geospatial constraints was constructed, and the network closeness index was used to fit the objective function curve to select optimization schemes. This study used Shenzhen, China as a case study, and the results indicated that the initial ecological network was significantly fractured by urban construction. In the optimization scenario, the network evolution reached its optimal state at the simulation step size of t = 26. At this point, the closeness index of the optimized network was increased by 15%. The optimization model constructed in this paper emphasizes the importance of functional restoration of existing network nodes, and the results of the study can provide support for ecospatial layout optimization and management.

Details

Language :
English
ISSN :
10095020 and 19935153
Database :
Directory of Open Access Journals
Journal :
Geo-spatial Information Science
Publication Type :
Academic Journal
Accession number :
edsdoj.53e4d368d24d411faa95d52a9155411a
Document Type :
article
Full Text :
https://doi.org/10.1080/10095020.2024.2392704