基于夜晚灯光数据和Google Earth的城市建成区提取分析

doi:10.3724/SP.J.1047.2015.00750

地球信息科学学报 ›› 2015, Vol. 17 ›› Issue (6): 750-756.doi: 10.3724/SP.J.1047.2015.00750

• 遥感科学与应用技术 • 上一篇

基于夜晚灯光数据和Google Earth的城市建成区提取分析

宋金超, 李新虎^*(), 吝涛, 张国钦, 叶红, 何晓燕, 葛汝冰

中国科学院城市环境研究所, 厦门 361021

收稿日期:2014-08-11 修回日期:2014-11-06 出版日期:2015-06-10 发布日期:2015-06-10
通讯作者: 李新虎 E-mail:xhli@iue.ac.cn
作者简介:
作者简介：宋金超（1990-）,女,山东潍坊人,硕士生,研究方向为城市形态、城市功能。E-mail：jcsong@iue.ac.cn
基金资助:
国家自然科学基金项目（41371540、41201155）;宁波市软科学研究计划项目（2013A10096）

A Method of Extracting Urban Built-up Area Based on DMSP/OLS Nighttime Data and Google Earth

SONG Jinchao, LI Xinhu^*(), LIN Tao, ZHANG Guoqin, YE Hong, HE Xiaoyan, GE Rubing

Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China

Received:2014-08-11 Revised:2014-11-06 Online:2015-06-10 Published:2015-06-10
Contact: LI Xinhu E-mail:xhli@iue.ac.cn
About author:
*The author: SHEN Jingwei, E-mail:jingweigis@163.com

摘要/Abstract

摘要：

夜晚灯光数据已被广泛应用于提取城市建成区的研究,由于灯光具有溢出特性,因此确定最佳灯光阈值成为研究热点。本研究中总结4种常用最佳阈值确定方法的特点,并使用Google Earth影像空间比较法,确定夜晚灯光数据提取城市建成区的最佳阈值。由于地形、交通等因素影响城市形态,城市形态影响夜晚灯光数据提取城市建成区的最佳阈值大小,因此,根据城市形态将阈值结果分为2类,并得到块状城市和带状城市建成区的最佳灯光阈值分别为43和 47。Google Earth影像空间比较法与其他方法相比具有不受统计数据限制,以及简易操作等优势,且从形态上对城市建成区提取结果进行空间比较;其次,根据城市形态对最佳阈值结果分类,使不同类型的城市建成区提取结果更准确。该方法适用于在地形复杂、形态多样的大尺度空间中提取城市建成区。

关键词: 夜晚灯光数据, Google Earth, 城市建成区, 城市形态, 地形坡度

Abstract:

DMSP-OLS nighttime data has been widely used for extracting urban built-up area since the 1970s. It has also been used to estimate the economic level, density of population, changes in spatial patterns of urban landscapes, spatial dynamics of fishery, and the relationships between urbanization, human health and energy consumption. Due to the light’s characteristic of overflowing, the range of city extracted by DMSP-OLS nighttime data surpasses its real boundary in urban area extraction. Therefore, an accurate light threshold determination has become a research hotspot in recent years. In this paper, we sum up the features of four commonly used methods from other dissertations. Then, a spatial comparison method based on Google Earth is adopted to determine the optimum value of light threshold for urban built-up area extraction. Because factors such as terrain and traffic have significant impacts on the urban form, and the urban form influences the value of light threshold, the results of threshold for urban built-up area extraction are divided into two categories according to the urban form. The optimum thresholds for crumb city and strip city are 43 and 47 respectively. Compared to other methods, the spatial comparison method based on Google Earth has two advantages in innovation. Firstly, the classification of threshold result is based on the urban form; meanwhile, it not only breaks the limit of statistical data, but also improves the accuracy of urban built-up area extraction. Secondly, the data sources such as DMSP-OLS nighttime data and Google Earth image used in this method are free and easy to acquire. The method picks a series of sampling points around the whole city on Google Earth as the reference data, which displays not only the results of traditional statistics, but also the spatial differences between the real boundary and the urban area extracted by DMSP-OLS nighttime data. In a word, this method is suitable for extracting urban built-up area in regions with complicated terrains and diverse urban forms.

Key words: DMSP/OLS nighttime data, Google Earth, urban built-up area, urban form, slope

宋金超, 李新虎, 吝涛, 张国钦, 叶红, 何晓燕, 葛汝冰. 基于夜晚灯光数据和Google Earth的城市建成区提取分析[J]. 地球信息科学学报, 2015, 17(6): 750-756.DOI:10.3724/SP.J.1047.2015.00750

SONG Jinchao,LI Xinhu,LIN Tao,ZHANG Guoqin,YE Hong,HE Xiaoyan,GE Rubing. A Method of Extracting Urban Built-up Area Based on DMSP/OLS Nighttime Data and Google Earth[J]. Journal of Geo-information Science, 2015, 17(6): 750-756.DOI:10.3724/SP.J.1047.2015.00750

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城市分类	周围坡度	形状率
块状城市	<17°	>0.5
带状城市	>17°	<0.5

		统计数据面积（km²）	提取面积（km²）	相对误差（%）
块状城市	宁波	285	293	3
	厦门	246	261	6
	沈阳	430	438	2
	长春	418	445	6
	长沙	306	324	5
带状城市	三明	29	28	-3
	贵阳	162	174	7
	兰州	197	201	2
	拉萨	62	66	6
	西宁	75	71	-5

基于夜晚灯光数据和Google Earth的城市建成区提取分析

A Method of Extracting Urban Built-up Area Based on DMSP/OLS Nighttime Data and Google Earth

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