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• 第八届全国景观生态学学术研讨会专栏 • 上一篇    下一篇

南京市绿色基础设施网络格局与连通性分析的尺度效应

于亚平1,尹海伟1*,孔繁花2,王晶晶1,徐文彬1#br#   

  1. 1南京大学城市规划与设计系, 南京 210093; 2南京大学国际地球系统科学研究所, 南京 210023)
  • 出版日期:2016-07-18

Scale effect of Nanjing urban green infrastructure network pattern and connectivity analysis.

YU Ya-ping1, YIN Hai-wei1*, KONG Fan-hua2, WANG Jing-jing1, XU Wen-bin1#br#   

  1. (1Department of Urban Planning and Design, Nanjing University, Nanjing 210093,China; 2International Institute for Earth System Sciences, Nanjing University, Nanjing 210023, China).
  • Online:2016-07-18

摘要: 以南京市为研究区,基于ArcGIS、Erdas、GuidosToolbox和Conefor等软件平台,采用形态学空间格局分析(MSPA)和景观连通性分析方法,通过在MSPA中设置不同的粒度、边缘宽度和在景观连通性分析中设置不同的扩散距离阈值,对2013年南京市绿色基础设施网络格局变化的尺度效应、边缘效应与距离效应进行评价.结果表明: 基于MSPA获取的景观类型构成存在明显的尺度效应和边缘效应,且边缘效应对MSPA景观类型的影响较尺度效应更为明显.不同扩散距离对景观连通性的影响很大,对于南京市来说,2 km或2.5 km是关键的扩散距离阈值.当输入数据选择粒度30 m、边缘宽度30 m时,可以得到南京市城市绿色基础设施(UGI)网络更为详尽的景观信息.基于MSPA与景观连通性方法,分析尺度效应、边缘效应、距离效应对研究区UGI网络景观类型的影响,有助于选择合适的粒度、边缘宽度及扩散距离,并更好地理解UGI网络的空间格局和与生态过程相关的尺度效应和距离效应,从而使得UGI网络时空格局变化分析时的参数设置更为科学合理.研究结果可为中尺度范围内UGI景观网络时空格局分析时的参数设置提供重要的参考和依据,对其他地区UGI景观网络的分析也具有一定的借鉴意义.

关键词: 景观连通性, 南京市, 城市绿色基础设施(UGI), 形态学空间格局分析(MSPA)

Abstract: Based on ArcGIS, Erdas, GuidosToolbox, Conefor and other software platforms, using morphological spatial pattern analysis (MSPA) and landscape connectivity analysis methods, this paper quantitatively analysed the scale effect, edge effect and distance effect of the Nanjing urban green infrastructure network pattern in 2013 by setting different pixel sizes (P) and edge widths in MSPA analysis, and setting different dispersal distance thresholds in landscape connectivity analysis. The results showed that the type of landscape acquired based on the MSPA had a clear scale effect and edge effect, and scale effects only slightly affected landscape types, whereas edge effects were more obvious. Different dispersal distances had a great impact on the landscape connectivity, 2 km or 2.5 km dispersal distance was a critical threshold for Nanjing. When selecting the pixel size 30 m of the input data and the edge wide 30 m used in the morphological model, we could get more detailed landscape information of Nanjing UGI network. Based on MSPA and landscape connectivity, analysis of the scale effect, edge effect, and distance effect on the landscape types of the urban green infrastructure (UGI) network was helpful for selecting the appropriate size, edge width, and dispersal distance when developing these networks, and for better understanding the spatial pattern of UGI networks and the effects of scale and distance on the ecology of a UGI network. This would facilitate a more scientifically valid set of design parameters for UGI network spatiotemporal pattern analysis. The results of this study provided an important reference for Nanjing UGI networks and a basis for the analysis of the spatial and temporal patterns of mediumscale UGI landscape networks in other regions.

Key words: urban green infrastructure (UGI), Nanjing City., morphological spatial pattern analysis (MSPA), landscape connectivity