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基于细粒度人口数据的深圳公园绿地可达性评价
引用本文:李浪姣,刘江涛,任福.基于细粒度人口数据的深圳公园绿地可达性评价[J].测绘与空间地理信息,2017,40(9).
作者姓名:李浪姣  刘江涛  任福
作者单位:1. 武汉大学资源与环境科学学院,湖北武汉,430079;2. 深圳市空间地理信息中心,广东深圳,518034
基金项目:国家自然科学基金资助项目
摘    要:公园绿地是城市公共基础设施的重要组成部分,公园合理的空间布局有助于城市居民便捷和公平地享用其服务功能。根据深圳市建筑普查数据和细粒度的人口数据提取住房信息,结合公园绿地数据和土地利用情况,针对不同类型公园的服务能力分别采用合适的可达性计算方法,从住房、社区和街道三个尺度评价深圳公园绿地可达性,结果表明:社区公园可达性一般,仅57.62%的社区的居民步行500 m以内能到达最近的社区公园;城市公园可达性总体较好,95.87%的社区市民步行前往最近城市公园所需时间在20 min以内。然而,大鹏半岛无城市公园,且多为自然生态保护区,市民到达城市公园所需时间长。社区公园可达性好的区域呈带状分布于深圳南部各区,城市公园高可达性区域呈多核围绕在各区行政中心。

关 键 词:公园绿地  可达性  住房信息  深圳

Using House Level Data to Evaluating Accessibility for Public Parks in Shenzhen
LI Lang-jiao,LIU Jiang-tao,REN Fu.Using House Level Data to Evaluating Accessibility for Public Parks in Shenzhen[J].Geomatics & Spatial Information Technology,2017,40(9).
Authors:LI Lang-jiao  LIU Jiang-tao  REN Fu
Abstract:Public parks are regarded as a crucial part of urban infrastructure and amenities.Rational spatial distribution of them is the key to offering convenient and equitable service for citizens.Using Shenzhen's building survey data and housing level demographic data,this study applied Euclidean distance and minimum cost distance to assess spatial accessibility of neighborhood parks and urban parks.The results indicated that neighborhood parks' accessibility level is ordinary,and that only 57.62% of citizens walk less than 500 m to the nearest neighborhood park.Meanwhile,the urban parks' accessibility is high,it takes below 20 min about 95.87% of nearly residents to go to an urban park by walking.However,residents who live in Dapeng Peninsula have to walk longer to go to a park than those in other sub-districts.Dapeng Peninsula is currently the largest and best biological reserve in Shenzhen.There are no urban parks except suburban forest parks or natural parks.In general,high level spatial access to neighborhood park area is banded in the south of Shenzhen,while these in good accessibility to urban park area concentrate on district administrative center.
Keywords:park  accessibility  house-level data  Shenzhen
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