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基于自然资源大数据的城市多功能景观识别与国土空间规划分区
引用本文:黄隆杨,王静,李泽慧,赵晓东,刘晶晶,方莹. 基于自然资源大数据的城市多功能景观识别与国土空间规划分区[J]. 地球信息科学学报, 2021, 23(9): 1617-1631. DOI: 10.12082/dqxxkx.2021.200727
作者姓名:黄隆杨  王静  李泽慧  赵晓东  刘晶晶  方莹
作者单位:1. 武汉大学 资源与环境科学学院,武汉 4300722. 北京师范大学 水科学研究院,北京 100875
基金项目:国家自然科学基金项目(41871203)
摘    要:
多功能景观能够同时提供多种景观功能,可以充分缓解生态环境压力.在自然资源大数据支撑下基于基层行政管理单元开展的多功能景观研究,可以更加快速准确地反映区域自然地理格局与社会经济发展格局的空间特征与区域差异,其将景观功能管理和行政管理有效结合,能为市县级国土空间规划中控制线的划定和国土空间规划分区提供从功能评估到空间识别等...

关 键 词:自然资源大数据  多功能景观  热点分析  协同与权衡  二阶聚类  国土空间规划分区  烟台
收稿时间:2020-12-02

Multi-functional Landscape Identification and Territorial Space Planning Zoning in Yantai City based on Big Data of Natural Resources
HUANG Longyang,WANG Jing,LI Zehui,ZHAO Xiaodong,LIU Jingjing,FANG Ying. Multi-functional Landscape Identification and Territorial Space Planning Zoning in Yantai City based on Big Data of Natural Resources[J]. Geo-information Science, 2021, 23(9): 1617-1631. DOI: 10.12082/dqxxkx.2021.200727
Authors:HUANG Longyang  WANG Jing  LI Zehui  ZHAO Xiaodong  LIU Jingjing  FANG Ying
Affiliation:1. School of Resource and Environmental sciences, Wuhan University, Wuhan 430072, China2. College of Water Science, Beijing Normal University, Beijing 100875, China
Abstract:
By virtue of providing multiple landscape functions, multi-functional landscape is considered as an important way to relieve the pressure of ecological environment. Supported by the big data of natural resources, the multi-functional landscape research, based on the grass-roots administrative management unit, can more quickly and accurately reflect the spatial characteristics and regional differences of regional physical geography pattern and social-economic development pattern. It can also effectively combine the landscape function management with administrative management, providing technically support for the planning and zoning of territorial space in the aspects of functional assessment and spatial identification. Taking Yantai City as an example, we extensively collected the big data of natural resources, including land use data, natural resource survey and evaluation data, climate data, and multi-source remote sensing data. The natural resource data were used along with the social economy data and Point Of Interest (POI) data to quantify the spatial patterns of Yantai’s six typical landscape functions (Biodiversity maintenance, Carbon sequestration, Soil retention, Crop production, Residential support, Economic activity support) using InVEST model, CASA model, Universal soil loss equations, kernel density analysis, and other methods. The village-level management unit was selected as the basic spatial unit to identify multi-functional landscape areas through the spatial superposition method as well as hot spot analysis. Meanwhile, the trade-offs and coordination between various landscape functions were explored by Spearman's correlation coefficient analysis. Finally, based on the second-order clustering method, the functional clustering of the landscape was conducted and the planning and zoning of territorial space in Yantai City was carried out. The protection and development strategies of various functional zoning were proposed. Results showed that 35.5% of village-level management units are multi-functional landscape hot spots, most of which locate in the contiguous mountain forest in the middle of Yantai City, namely, the junction of various cities. The other 24.1% of village-level management units are hot spots of two landscape functions, indicating a good landscape functional diversity of Yantai City. Meanwhile, the significant correlation between landscape functions shows a synergistic effect of the natural landscape functions. However, there is a significant spatial conflict between the residential and economic support functions. Based on the clustering results of landscape functions at village-level management units, Yantai City was divided into ecological protection areas, agricultural and rural development areas, urban functional development areas, and urban core areas, whose area proportions are 30%, 55%, 11% and 4%, respectively. There was a strong spatial consistency and coordination between the planning division and the current management boundary, indicating that under the support of big data of natural resources, the planning and zoning of territorial space based on landscape function clustering analysis is quite accurate and practical.
Keywords:Big data of natural resources  Multi-functional landscape  Hot spot analysis  Coordination and trade-off  two-step cluster  Planning zoning of territorial space  Yantai City  
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