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基于MSPA与混淆矩阵的绿地系统格局 演化及其驱动因子研究——以伦敦为例
戴菲,毕世波,陈明,郭晓华*
0
作者简介:
摘要:
绿地系统的类型、景观组分及驱动力分析和评价能够为绿地系统的未来规划起到指导作用。伦敦是推动世界建设城市环城绿带的最成功典范。以其为例,首先依据相关政策研究了1975—2018年6个时间点的绿地变化情况。而后借助ENVI5.3、ArcMap10.5、混淆矩阵和MSPA等技术方法从时间、空间维度与绿地格局的类型层面对其1975年来的绿地系统进行了深入探究,提出从时空变化到驱动力分析的绿地系统研究思路。结果表明:1)伦敦1975年来的绿地系统发展可分为3个阶段:1975—1990年的缓慢减少期、1990—2011年的迅速恶化期、2011年至今的迅速恢复与完善期,绿地面积占比从1975年的39.83%下降至1990年的38.57%、2011年的30.71%,最后迅速上升至2018年的44.45%;2)核心区景观类型从占该年绿地系统比例39.83%的253.16km2增长至2018年的310.7km2,但边缘仅增加了3.08km2,绿地与周边非绿地系统用地的过渡地带有待于进一步完善;3)研究时间段总体变化的kappa系数为0.68。土地利用类型的变化程度依次为33%、29%、34%、22%、37%,总体变化程度为32%;植被用地的平均变化率依次为21.73%、18.70%、21.63%、15.55%、21.66%,总体变化率为19.39%;主要的驱动力,建设用地>裸地>水域;基于MSPA与混淆矩阵的绿地研究方法具有可行性。
关键词:  风景园林  MSPA  混淆矩阵  绿地系统  格局演化  驱动因子
DOI:
基金项目:
Research on Green Space System Pattern Evolution and Its Driving Factors Based on MSPA and Confusion Matrix—Taking London as an Example
DAI Fei,BI Shibo,CHEN Ming,GUO Xiaohua
Abstract:
The type, landscape composition and driving force analysis and evaluation of green space system can guide the future planning of green space system. London is the most successful example of promoting the world's green belt around city. Taking this as an example, this paper studies the changes of green space at six time points from 1975 to 2018 according to relevant policies. Then, with the help of ENVI5.3, ArcMap10.5, confusion matrix and MSPA, the green space system from 1975 has been deeply explored from the time and space dimensions and the type of green space pattern, and from time-space perspective, green space system research ideas is proposed. The results show that: 1) The development of green space system in London in 1975 can be divided into three stages: the slow reduction period from 1975 to 1990, the rapid deterioration period from 1990 to 2011, and the rapid recovery and improvement period from 2011 to the present. The proportion of green area decreased from 39.83% in 1975 to 38.57% in 1990 and 30.71% in 2011, and quickly rose to 44.45% in 2018; 2) The landscape type in the core area increased from 253.16km2, which accounted for 39.83% of the green space system in the year, To 310.7km2 in 2018, but the edge only increased by 3.08km2, and the transitional zone between green space and surrounding non-green space system land needs further improvement; 3) The Kappa coefficient of the overall change of the study time period is 0.68. The degree of land use change was 33%, 29%, 34%, 22%, 37% and the overall change degree was 32%; while the average change rate of vegetation land was 21.73%, 18.70%, 21.63%, 15.55%, 21.66%, and the overall rate of change is 19.39%; the main driving force is construction land > bare land > waters; and the greenfield research method based on MSPA and confusion matrix is feasible.
Key words:  landscape architecture  MSPA  confusion matrix  green space system  pattern evolution  driving factor

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