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昆明冶金高等专科学校学报 ›› 2023, Vol. 39 ›› Issue (4): 42-.DOI: 10.3969/j.issn.1009-0479.2023.04.006

• 资源开发与测绘 • 上一篇    下一篇

基于多阶邻接度指数的城市景观扩张格局演变分析一以昆明市呈贡区为例

易俊华1,王 霄2,许泉立2   

  1. (1.昆明冶金高等专科学校测绘学院,云南 昆明 650033; 2.云南师范大学地理学部,云南 昆明 650500)
  • 收稿日期:2023-05-15 出版日期:2023-08-27 发布日期:2023-12-28
  • 作者简介:易俊华 (1976-),女,云南昆明人,正高级工程师,工学硕士,主要从事空间分析与资源环境遥感研究。
  • 基金资助:
    云南省教育厅科学研究基金:基于多阶邻接度指数的滇池流域城市扩张时空异质性及其驱动机制研究(2023J1524);国家自然科学基金:基于土地自然演化单元的土地利用变化元胞自动机模型研究 (42161065)。

Analysis of the Evolution of Urban Landscape Expansion Pattern Based on Multi-Order Adjacency Index: A Case Study of Chenggong District, Kunming City

YI Junhua1 ,WANG Xiao2, XU Quanli2   

  1. ( 1. Faculty of Surveying and Mapping, Kunming Metallurgy College , Kunming 650033 , China;2. Department of Geography , Yunnan Normal University , Kunming 650500, China)
  • Received:2023-05-15 Online:2023-08-27 Published:2023-12-28

摘要: 城市景观既是城市扩张的典型特征,又是评判城市化水平的重要指标。度量城市景观扩张特征并分析其时空演化格局有助于人们了解城市发展的态势,进而为城市合理规划提供依据。以云南省昆明市呈贡区为例,基于多阶邻接度指数 (Multi-order Adjacency ndex,MAI) 和空间自相关分析方法测度并分析了该区域2005-2020 年 (每5年为1个计算周期,共3 个时段) 的城市景观扩张特征及其时空格局演化态势。首先,运用 MAI值度量了研究区的城市景观扩张特征:然后,基于 MAI值,运用空间自相关分析方法探测了城市扩张的空间聚集特征与趋势。结果表明:1) 蔓延式和边缘式是研究区主要的城市景观扩张类型,其他类型较为平均且与上述两种类型比较有明显差距: 2) 城市发展早期(前 10年),蔓延式占绝对优势,后期这种趋势明显下降;3)MAI值的高-高聚集区域呈现由中间向四周扩散的趋势,城市化步伐正朝“紧凑”方向发展。上述结果表明:结合 MAI 和空间自相关是度量和探测城市景观扩张特征及其时空演化过程的有效途径。

关键词: 城市景观扩张, 景观格局; 空间自相关;多阶邻接度指数; 驱动分析

Abstract: Urban landscape is not only a typical characteristic of urban expansion , but also an importantindicator to evaluate the level of urbanization. Measuring landscape characteristic and analyzing its spa-tio-temporal evolution pattem is helpful to reveal the trend of urban expansion and provide a support forrational urban planning. Taking Chenggong district of Kunming of Yunnan province of China as the casestudy, this issue measured the characteristics of urban landscape expansion with Multi-order AdjacencIndex ( MAl) and analyzed its geographic cluster pattern using spatial autocorrelation analysis methodfrom 2005 to 2020 (every 5 years is a calculation period, and there are three periods in total). Firstly.we measured the characteristic of urban landscape according to the MAl values, and then , based on theMAl value , the spatial autocorrelation analysis method was adopted to detect the geographic cluster patterns and the urbanization trend. The results showed that: l) Sprawl type and edge type were the maintypes of urban landscape expansion in the study area, while the other types were more average and haveobvious gap compared with the above two types; 2) In the early stage of urban development ( the first 10years) , the sprawl type dominated , and then the trend was obviously declining in the later stage; 3 )The high-high cluster areas of MAl showed the trend of urban expansion from the center to the surround-ing areas, and the pace of urbanization was developing towards the direction of “ compact". These re-sults indicated that the combination of MAl and spatial autocorrelation is an effective way to measure anddetect the characteristics of urban landscape expansion and its spatio-temporal evolution process.

Key words: urban landscape expansion, landscape pattem, spatial autocorrelation, multi-order adjacency index: drive analysis

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