Journal of Natural Resources, Volume. 35, Issue 1, 174(2020)
Identification and optimization of hierarchical ecological nodes based on multi-target genetic algorithm: Take Jintan district of Changzhou as an example
Effective ecological network construction can guarantee regional ecological security, which is an important path to achieve regional sustainable development. Based on the analysis of the connotation of ecological nodes, this paper establishes a multi-level ecological node identification system based on "resource-based strategic point - structural strategic point - structural weak point", and uses remote sensing images, land use data, POI data, etc. of Jintan district in 2015. This paper also employs multi-target genetic algorithm, minimum resistance model and so on. The hierarchical ecological network in the ideal state of Jintan district was constructed, and the ecological network was quantitatively evaluated by using indexes such as the network topology and nodes utility. Based on the above, the following main conclusions were obtained: (1) Multi-level ecological network is significantly better than the general network in terms of nodes utility and overall network performance. And the water network area has a strong applicability. (2) As the current situation of the ecological network distribution is uneven, the ecological nodes' layout needs to be optimized. The optimized node coverage increased by 17.70%, the uniformity of node distribution decreased by 45.45%, and the average clustering coefficient increased by 87.36%. (3) Multi-level ecological node system has practical application, and different management strategies should be adopted for different types of ecological nodes.
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Xiao-lin ZHANG, Xiao-bin JIN, Qing-li ZHAO, Jie REN, Bo HAN, Xin-yuan LIANG, Yin-kang ZHOU. Identification and optimization of hierarchical ecological nodes based on multi-target genetic algorithm: Take Jintan district of Changzhou as an example[J]. Journal of Natural Resources, 2020, 35(1): 174
Received: Oct. 6, 2019
Accepted: --
Published Online: Sep. 25, 2020
The Author Email: JIN Xiao-bin (jinxb@nju.edu.cn)