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广州市绿地景观空间特征评价与规划对策
引用本文:刘柏静,叶长青.广州市绿地景观空间特征评价与规划对策[J].黑龙江农业科学,2014(10):95-99.
作者姓名:刘柏静  叶长青
作者单位:海南大学环境与植物保护学院,海南海口,570228
基金项目:海南省中西部高校提升综合实力工作资金资助项目,国家自然科学基金资助项目,“十一五”国家科技支撑计划资助项目,广东省建设厅科研课题资助项目
摘    要:绿地空间结构极大影响绿地功能,而传统的城市绿地评价过多注重绿地数量,忽视了其空间分布。运用景观生态学理论和GIS、RS技术,以广州市区为研究对象,选取绿地覆盖率、斑块面积等11项指标,通过主成分分析对6个行政区绿地进行比较评价,将评价指标综合为绿地空间格局、绿地形状和绿化覆盖率3个方面。结果表明:越秀区由于绿地分布结构合理,覆盖率较高,综合状况最佳,其次为荔湾区,白云区综合评价最差。评价方法从绿地空间结构的角度完善了传统城市绿地评估体系,为城市绿地规划管理与生态建设提供科学依据。

关 键 词:景观生态  主成分分析  城市规划  遥感  地理信息系统

Comprehensive Assessment of Spatial Characteristics of Urban Greenbelt Landscapes and Planning Strategies in Guangzhou City
LIU Bai-jing,YE Chang-qing.Comprehensive Assessment of Spatial Characteristics of Urban Greenbelt Landscapes and Planning Strategies in Guangzhou City[J].Heilongjiang Agricultural Science,2014(10):95-99.
Authors:LIU Bai-jing  YE Chang-qing
Institution:(Environment and Plant Protection College of Hainan University, Haikou, Hainan 570228)
Abstract:Spatial structures of urban green spaces have great impacts on their functions, but the traditional eval- uation took too much emphasis on the number of green spaces, ignoring their spatial distribution. Using land- scape ecology theory,GIS and RS technology, 11 indexes such as the green coverage,patch area index and so on were selected to evaluate green spaces in Guangzhou. Principal component analysis was conducted and 11 inde- xes were grouped into three types, the first was landscape pattern index, the second was shape index and the third was the green coverage index. The comprehensive evaluation results showed that Yuexiu district was the best because of the reasonable structure and higher green coverage. Liwan district was better and Baiyun dis- trict was the worst. This evaluation method for green spaces system improved the traditional one from the per- spective of the structure of green space,and provided a scientific basis for the planning and ecological construc- tion of urban green spaces.
Keywords:landscape ecology  principal component analysis  urban planning  remote sensing  GIS
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