地理科学 ›› 2018, Vol. 38 ›› Issue (11): 1741-1749.doi: 10.13249/j.cnki.sgs.2018.11.001

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一种新的城市景观扩张过程测度方法:多阶邻接度指数

刘稼丰(), 焦利民, 董婷, 许刚, 张博恩, 杨璐迪   

  1. 武汉大学资源与环境科学学院, 湖北 武汉 430079
  • 收稿日期:2017-12-08 修回日期:2018-03-08 出版日期:2018-11-20 发布日期:2018-11-20
  • 作者简介:

    作者简介:刘稼丰(1992-),男,河南平顶山人,博士研究生,主要从事城市扩张研究。E-mail:liujiafeng@whu.edu.cn

  • 基金资助:
    国家自然科学基金项目(41571385)资助

A Novel Measure Approach of Expansion Process of Urban Landscape: Multi-order Adjacency Index

Jiafeng Liu(), Limin Jiao, Ting Dong, Gang Xu, Bo’en Zhang, Ludi Yang   

  1. School of Resource and Environment Science, Wuhan University, Wuhan 430079, Hubei, China
  • Received:2017-12-08 Revised:2018-03-08 Online:2018-11-20 Published:2018-11-20
  • Supported by:
    National Natural Science Foundation of China (41571385)

摘要:

提出多阶邻接度指数(Multi-order Adjacency Index, MAI),应用多阶缓冲区完善对新旧斑块间空间关系的识别,从而更为详细地揭示城市扩张过程特征。MAI的延伸公式可供自下而上从宏观分析城市整体的扩张程度及空间变化过程。选取武汉市作为研究区,基于4期遥感影像(1995、2000、2005和2010年)划分3个时段应用MAI分析武汉市城市景观格局的演变特征。结果表明,MAI能够详细地反映出新增城市斑块在空间上有更加离散的分布趋势,新增斑块的扩张程度逐渐加深,建成区的边界不断向外延展。比较MAI与LEI(Landscape Expansion Index, LEI)的特征差异,指出MAI能够更加详尽地反映新旧斑块间的空间位置关系。

关键词: 多阶邻接度指数, 景观扩张指数, 城市扩张, 多阶缓冲区

Abstract:

Landscape index is an effective approach to capture the information for landscape pattern. In urban expansion, the spatial relationship of newly grown urban patches to existing urban areas reflects the properties of urban expansion evolution. However, existing metrics cannot comprehensively express the spatial distributions of all new patches relative to old patches, lacking quantitative reflection of spatial relationship gradient of outlying new patches to old patches. We propose a new landscape metric, multi-order adjacency Index (MAI), to depict urban expansion degree by adjacency degree based on distance between new and old patches and boundary-sharing rate. The two characteristics of MAI are shown as follows: 1) The value of MAI is continuous for reflecting the gradient of expansion degree of new patches. 2) MAI has clear physical meaning for representing actual distance between new and old patches, and the landscape expansion types are then redefined by MAI. Meanwhile, the two variants of MAI, mean multi-order adjacency Index (MMAI) and area-weighted mean multi-order adjacency Index (AWMMAI), are designed to capture information for the dynamic process of urban expansion from a bottom-up view. Based on four period’s remote sensing images (1995, 2000, 2005 and 2010) of Wuhan, we applied MAI for characterizing the change of landscape pattern. The following results were obtained: 1) The variation trend of the number for each expansion type show a tendency to decrease first and then increase except distant leap type that present a dramatic increasing trend; 2) The spatial pattern of Wuhan was more compact in the beginning, and became more and more dispersed along with urban expansion; 3) The result of MMAI indicate average expansion degree increased in the dynamic process of urban expansion, and the change trend of AWMMAI shows that the global spatial pattern of Wuhan city is dispersed in a general trend, but has a direction towards the compact development during 2005-2010. By comparing MAI and other dynamic metrics of urban expansion, we found that MAI can provide information more precisely than others in reflecting the gradient spatial relationship. At the same time, MAI improved the recognition of landscape expansion type and made up for the lack of quantitatively distinguishing the urban patches with larger urban expansion degree by the existing measurement methods. MAI also inquired into the spatial pattern change characteristics of urban landscape expansion in a deeper level. MAI provides a better perspective to understand the hidden mechanism of the spatial characteristics of urban expansion. Future research will include analysis and verification of the growth of the outlying seed regions. The simulation model of urban expansion by using MAI could be discussed for predicting the farther urban expansion. MAI is also expected to be a practical measurement to generalize in other cities or scales for better understanding urban expansion dynamics and analyzing problems of urban spatial pattern.

Key words: Multi-order Adjacency Index, MAI, landscape expansion index, urban expansion, multi-order buffers

中图分类号: 

  • K909