地球信息科学学报 ›› 2021, Vol. 23 ›› Issue (6): 1017-1027.doi: 10.12082/dqxxkx.2021.200346

• 地理空间分析综合应用 • 上一篇    下一篇

基于栅格的安徽省人居环境人文适宜性评价

李大伟1(), 黄薇薇1,*(), 沈非1,2, 程煜1, 陈铭杨1   

  1. 1.安徽师范大学地理与旅游学院,芜湖 241003
    2.资源环境与地理信息工程安徽省工程技术研究中心,芜湖 241003
  • 收稿日期:2020-07-04 修回日期:2020-10-29 出版日期:2021-06-25 发布日期:2021-08-25
  • 通讯作者: 黄薇薇
  • 作者简介:李大伟(1993— ),男,安徽合肥人,硕士生,主要从事资源环境与GIS应用研究。E-mail: lidawei2020@126.com
  • 基金资助:
    安徽省高校自然科学研究项目(KJ2019A0496)

Evaluation of Human Suitability of Human Settlement Environment in Anhui Province based on Grid

LI Dawei1(), HUANG Weiwei1,*(), SHEN Fei1,2, CHENG Yu1, CHEN Mingyang1   

  1. 1. School of Geography and Tourism, Anhui Normal University, Wuhu 241003, China
    2. Engineering Technology Research Center of Resources Environment and GIS, Anhui Province, Wuhu 241003, China
  • Received:2020-07-04 Revised:2020-10-29 Online:2021-06-25 Published:2021-08-25
  • Contact: HUANG Weiwei
  • Supported by:
    University Natural Science Research Project of Anhui Province(KJ2019A0496)

摘要:

新时期新型城镇化建设对适宜的人居人文环境提出了切实要求。运用GIS技术,基于夜间灯光遥感影像、交通矢量、兴趣点(POI)、统计年鉴等多源数据,以500 m×500 m栅格为基础单元,选取经济水平、交通通达、历史文化、公共服务等因子(权重分别为0.36、0.27、0.17、0.20),采用综合指数法构建人居环境人文适宜性评价模型,定量评价2017年安徽省人居环境人文适宜性。结果表明:① 安徽省人居环境人文适宜性指数介于0.83~87.10之间,划分为高度适宜区、较高适宜区、中度适宜区、一般适宜区及临界适宜区5种类型区,以中度适宜区面积最大,占全省总面积68.72%,高度适宜区面积最小,仅占总面积的1.24%,整体呈现“多核心”、“条带式”空间分异格局;② 交通通达和公共服务是造成全省人居环境人文适宜性分异的主要因子,其指数均值在中度适宜区皆达到了94.18,且贡献率均值在各类型区均在34.00%以上;历史文化对较高及临界适宜区影响明显,贡献率均值分别为10.51%和11.93%;经济水平对高度适宜区的作用最显著,其贡献率均值高达22.02%;③ 全省近90.86%的人口集中分布在人居环境人文适宜性指数43.00~66.00之间,属于中度至较高适宜区的范围,人居环境人文质量与人口分布较为匹配。测评结果较为客观地反映了安徽省人居环境的人文本底。

关键词: 人居环境, 人文适宜性, 空间分异, 经济, 交通, 历史文化, 公共服务, 栅格数据

Abstract:

The construction of new urbanization puts forward practical requirements for a suitable human settlement environment in the new period. By using GIS technology, based on multi-source data such as Nighttime Light (NTL) data, traffic network vectors data, Points of Interest (POI) data, and statistical yearbooks, we selected the economic level, transportation accessibility, historical culture, and public service as impact factors of the suitability of human settlement environment (weights were 0.36, 0.27, 0.17, 0.20, respectively) on the basis of 500 m × 500 m grid unit. We quantitatively evaluated the human suitability of human settlement environment in Anhui Province in 2017 using a synthetical index method to construct the human suitability evaluation model. The results show that: (1) the human suitability index of human settlements in Anhui Province ranged from 0.83 to 87.10. The human settlement environment could be divided into five types: highly suitable areas, relatively suitable areas, moderately suitable areas, general suitable areas, and critical suitable areas. The area of moderately suitable areas was the largest, accounting for 68.72% of the whole province, while the area of highly suitable areas was the smallest, accounting for only 1.24% of the whole province. The spatial heterogeneity of human settlement suitability was characterized by "Multi-core" and "striped" patterns; (2) the transport accessibility and public service were the main factors that led to difference in human suitability of human settlements in the province, with an average index of 94.18 in the moderate suitable areas, and an average contribution rate of 34% in all types of regions. Besides, the historical culture had a significant impact on higher and critically suitable areas, with an average contribution rates of 10.51% and 10.53%, respectively, while the economic level had the most significant contribution to the highly suitable areas, with an average contribution rate of 22.02%; and (3) nearly 90.86% of the population in the province was concentrated in the regions with human suitability index of 43.00~66.00 (i.e., moderate to the high suitable areas), which implied that the human quality of human settlements matches the population distribution. In conclusion, our evaluation results objectively reflect the baseline of the human settlements in Anhui Province.

Key words: human settlement, human suitability, spatial differentiation, economy, transportation traffic, historical culture, public service, raster data