地球信息科学学报 ›› 2016, Vol. 18 ›› Issue (4): 544-552.doi: 10.3724/SP.J.1047.2016.00544

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一种基于移动窗口的城市绿度遥感度量方法

吴俊1(), 孟庆岩1,*(), 占玉林1, 顾行发1, 张佳晖1,2   

  1. 1. 中国科学院遥感与数字地球研究所,北京 100101
    2. 中国科学院大学资源与环境学院,北京 100049
  • 收稿日期:2015-07-15 修回日期:2015-09-14 出版日期:2016-04-20 发布日期:2016-04-19
  • 通讯作者: 孟庆岩 E-mail:wujun@radi.ac.cn;mengqy@radi.ac.cn
  • 作者简介:

    作者简介:吴 俊(1991-),男,硕士生,主要从事城市陆表环境遥感研究。E-mail: wujun@radi.ac.cn

  • 基金资助:
    国家自然科学基金项目(41471310、41371416);国土资源部城市土地资源监测与仿真重点实验室开放基金资助课题(2012B091100219);三亚市专项科研试制项目(2015KS114)

A Measure of Urban Green Index in Urban Areas Based on Moving Window Method

WU Jun1(), MENG Qingyan1,*(), ZHAN Yulin1, GU Xingfa1, ZHANG Jiahui1,2   

  1. 1. Institute of Remote Sensing and Digital Earth, Chinese Academy of science, Beijing 100101, China
    2. College of Resources and Environment, University of Chinese Academy of Science, Beijing 100049, China
  • Received:2015-07-15 Revised:2015-09-14 Online:2016-04-20 Published:2016-04-19
  • Contact: MENG Qingyan E-mail:wujun@radi.ac.cn;mengqy@radi.ac.cn

摘要:

针对城市绿度空间分布特征难以描述且合理性难以度量的问题,在基于多光谱遥感数据和激光雷达数据(LiDAR)获取高精度城市建筑物与绿地信息的基础上,本文提出一种基于移动窗口的城市绿度遥感度量方法。其通过遍历研究区像元,建立了移动窗口内的城市绿地面积与固定窗口面积之间的关系,计算了中心像元的绿度指数,并与传统的格网法、缓冲区法进行了比较。研究结果表明:该方法建立的绿度指数,能很好地反映城市居民在区域内接触城市绿地的概率及其空间分布特征,与格网法和缓冲区法相比,有效避免了格网法产生的边缘效应,并解决了缓冲区法空间不连续性的问题,实现了区域范围内任意点的城市绿度度量。该方法为城市绿地度量、城市规划、管理提供了一种新视角。

关键词: 移动窗口, 城市绿度, 遥感, 接触概率

Abstract:

Urban green space is an important element of ecological networks. Conservation policies urge the protection of urban green space in cities possessed by dense buildings and focus on the improvement of intercommunity relationships among the green space plots within different areas. Urban green space forms an indispensable part of urban ecosystems. Quantifying the urban green space is of substantial importance for urban planning and development. In order to solve the problem of measuring the proximity of residents to green space (PRG), this paper proposed a method of urban green index (UGI) based on multi-spectral remote sensing data and Lidar data (LiDAR), which provide the accurate information of urban buildings and green spaces. In this study, the urban green index of the central pixel is developed based on calculating the area of urban green space and a fixed window area. The results show that the urban green index can be an effective method to measure the proximity of residents to green space and its spatial distribution characteristics. It avoids the edge effects generated by grid method, overcomes the discontinuity problem occurred in the buffer space, and could obtain the urban green index of any point in the region. At the same time, the newly constructed model can be used to identify the key protection regions that will have typical demonstration effects. The input parameters of the model can be obtained from the remote sensing images, which are easier to obtain than from the field measurements. Therefore, it could be considered to be a new method for studying the urban green space and could offer effective technical assistances to urban planning and management. The quantitative evaluation of the urban green space will provide the scientific support to urban greening and urban environmental protection. This study exploits the advantages of multi-source remote sensing data with high ground resolution in extracting building and vegetation information.

Key words: moving window, urban green index, remote sensing, proximity of residents to green space (PRG)