地球信息科学学报 ›› 2021, Vol. 23 ›› Issue (9): 1617-1631.doi: 10.12082/dqxxkx.2021.200727

• 地球信息科学理论与方法 • 上一篇    下一篇

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

黄隆杨1(), 王静1,2,*(), 李泽慧1, 赵晓东1, 刘晶晶1, 方莹1   

  1. 1. 武汉大学 资源与环境科学学院,武汉 430072
    2. 北京师范大学 水科学研究院,北京 100875
  • 收稿日期:2020-12-02 出版日期:2021-09-25 发布日期:2021-11-25
  • 通讯作者: *王 静(1966— ),女,浙江天台人,教授,博士生导师,主要从事土地资源与生态状况遥感监测与评价研究。 E-mail: wjing0162@126.com
  • 作者简介:黄隆杨(1995— ),男,重庆南川人,博士生,主要从事生态保护与国土空间规划研究。E-mail: hly@whu.edu.cn
  • 基金资助:
    国家自然科学基金项目(41871203)

Multi-functional Landscape Identification and Territorial Space Planning Zoning in Yantai City based on Big Data of Natural Resources

HUANG Longyang1(), WANG Jing1,2,*(), LI Zehui1, ZHAO Xiaodong1, LIU Jingjing1, FANG Ying1   

  1. 1. School of Resource and Environmental sciences, Wuhan University, Wuhan 430072, China
    2. College of Water Science, Beijing Normal University, Beijing 100875, China
  • Received:2020-12-02 Online:2021-09-25 Published:2021-11-25
  • Supported by:
    National Natural Science Foundation of China(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多方面的技术支撑。本文在广泛收集土地利用变更调查数据、自然资源调查评价数据、气象数据、多源遥感数据等自然资源大数据的基础上,结合社会经济数据和兴趣点数据,基于InVEST模型、CASA模型、通用土壤流失方程以及核密度分析等方法对烟台市6种景观功能进行了空间量化;再以村级管理单元为基本空间单元进行景观功能热点分析以识别多功能景观区;利用Spearman相关系数分析各种景观功能间的权衡与协调作用;最后基于二阶聚类法进行景观功能聚类以开展烟台市国土空间规划分区,并制定相应的保护与发展策略。研究表明:① 烟台市35.5%的村级管理单元为多功能景观区;② 自然景观功能间呈协同作用,而自然景观功能与居住和经济承载功能间存在显著的空间冲突和权衡作用;③ 根据景观功能聚类结果,烟台市被划分为生态保护区、农业农村发展区、城镇功能发展区和城镇核心区,面积占比分别为30%,55%,11%,4%。规划分区与现状管理边界在空间上具有较强的一致性和协调性,表明在自然资源大数据支撑下,基于景观功能聚类分析的国土空间规划分区具有相当的准确性和实用性。

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

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.

Key words: 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