杭州城市生活质量的定量评价

以乡镇、街道为基本空间统计单元,选取人口密度、住宅基准地价、大专以上学历人口比重为社会经济指标,建设用地比重、NDVI、地表温度为生物物理指标,采用主成分分析和GIS叠加法,定量评价了杭州城市生活质量的空间分布状况。结果表明：NDVI和地表温度 (相关系数r = -0.63)、城镇用地比重 (相关系数r = -0.83) 呈明显的负相关,地表温度和城镇建设用地是影响杭州“绿色环境”两个的最重要因素。NDVI和住宅基准地价 (r = -0.66)、大学毕业生比例 (相关系数r = -0.59)、人口密度 (相关系数r = -0.29) 也呈较明显的负相关,“绿色环境”并未成为高学历人群和高收入家庭的主要决定因素,较繁华或较便利地段仍是高学历人群和高收入家庭选择居住环境的首要选择。高生活质量值 (前20%) 区域主要位于分布于城市中心区,即杭州上城区、下城区及西湖区的部分单元,而郊区的生活质量相对较低。

A Quantitative Assessment on the Quality of Life in Hangzhou Based on Landsat/TM and Socioeconomic Data

By taking streets and towns as basic spatial analysis units, the quality of life (QOL) in Hangzhou is quantitatively evaluated by integrating principal component analysis and geographic information system overlay of ranked data layers. The socioeconomic variables such as population density, basic residential land price and percentage of college graduate are selected from socioeconomic data and the biophysical variables including percentage of built-up area, surface temperature (in oC) and NDVI value are extracted from Landsat/TM data. The results show that NDVI displays a strong negative correlation with percentage of built-up area (correlation coefficient r = -0.83) and surface temperature (correlation coefficient r = -0.63), so they are regarded as two main influencing factors of "green environment" quality. At the same time, there is also obvious negative correlation between NDVI and basic residential land price (correlation coefficient r = -0.66), percentage of college graduate (correlation coefficient r = -0.59) and population density (correlation coefficient r = -0.29). It means that "green environment" is still not the most important factor for high educated and high income families to choose living environment in Hangzhou, on the contrary, they would like to choose densely populated areas with convenient traffic conditions as their residence. Downtown of Hangzhou, that is, Shangcheng district, Xiacheng district and some units of Xihu district still belongs to higher QOL region (the first 20% of the evaluation value) and suburb appears lower QOL.