Land Use Optimization for Coastal Urban Agglomerations Based on Economic and Ecological Gravitational Linkages and Accessibility
文献类型：期刊论文
| 作者 | Pan, Tingting1,2,3; Yan, Fengqin1,3; Su, Fenzhen1,2,3; Lyne, Vincent4; Zhou, Chaodong1,3 |
| 刊名 | LAND
 |
| 出版日期 | 2022-07-01 |
| 卷号 | 11期号:7页码:18 |
| 关键词 | urban agglomerations land use optimization parallel NSGA-II economic linkage intensity ecosystem services value |
| DOI | 10.3390/land11071003 |
| 通讯作者 | Su, Fenzhen(sufz@lreis.ac.cn) |
| 英文摘要 | Urban agglomerations (UA) are attracting increasing research attention as a global emergent phenomenon, whereby regional collaborative linkages between cities attracts and agglomerates development. However, these studies also acknowledge that ecological values may be negatively impacted by re-development, ecological fragmentation, and proximity or downstream impacts. Sustainable development, therefore, requires balancing forces from economic attraction and ecological repulsion. Forces similar to economic ones may also operate in attracting ecological enhancement towards higher-valued ecological regions; however, research regarding the role of the self-collaborative gravity-like forces shaping UA is limited in land use optimization. To assist planners, this study developed a new multi-objective land use optimization of UA that explored the intensity of economic ties and ecological gradients using the multi-objective NSGA-II algorithm. In this model, economic linkage intensity (ELI) and accessibility were used to calculate a modified GDP (gross domestic product), while the NDVI (normalized difference vegetation index) was used for the modified ESV (ecosystem services value). Spatial allocation with implicit economic accessibility relationships was enhanced through a two-step mutation operator, including a "gravity flip" spatial orientation factor. Compared to the standard NSGA-II algorithm, models of future land use of the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) in 2030 have shown that the modified GDP value in our model increased by 7.41%, while the conversion rate of high-density vegetation reduced by 7.92%. The results highlighted the importance of linkage and accessibility factors in enhancing the clustering of cities. In tandem, the modified ESV also enhances ecosystem services contributions of higher value vegetated land through decentralized built-up developments. The proposed model provides managers with a comprehensive and efficient land use solution model that accounts for intrinsic linkage factors shaping the development of compact urban agglomerations. |
| WOS关键词 | SIMULATED ANNEALING ALGORITHM ; USE ALLOCATION ; NSGA-II ; SPATIAL OPTIMIZATION ; GENETIC ALGORITHM ; AGRICULTURAL LAND ; RIVER DELTA ; REGION |
| 资助项目 | National Natural Science Foundation of China[41890854] |
| WOS研究方向 | Environmental Sciences & Ecology |
| 语种 | 英语 |
| WOS记录号 | WOS:000831971700001 |
| 出版者 | MDPI |
| 资助机构 | National Natural Science Foundation of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/181236]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Su, Fenzhen |
| 作者单位 | 1.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China 2.Nanjing Univ, Collaborat Innovat Ctr South China Sea Studies, Nanjing 210093, Peoples R China 3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 4.Univ Tasmania, IMAS Hobart, Hobart, Tas 7004, Australia |
| 推荐引用方式 GB/T 7714 | Pan, Tingting,Yan, Fengqin,Su, Fenzhen,et al. Land Use Optimization for Coastal Urban Agglomerations Based on Economic and Ecological Gravitational Linkages and Accessibility[J]. LAND,2022,11(7):18. |
| APA | Pan, Tingting,Yan, Fengqin,Su, Fenzhen,Lyne, Vincent,&Zhou, Chaodong.(2022).Land Use Optimization for Coastal Urban Agglomerations Based on Economic and Ecological Gravitational Linkages and Accessibility.LAND,11(7),18. |
| MLA | Pan, Tingting,et al."Land Use Optimization for Coastal Urban Agglomerations Based on Economic and Ecological Gravitational Linkages and Accessibility".LAND 11.7(2022):18. |
入库方式： OAI收割
来源：地理科学与资源研究所
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