城区边界遥感提取研究进展
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摘要
针对当前城乡统计口径和城区边界提取标准不统一的问题,该文梳理了当前国内外城区边界相关概念及界定标准、不同分辨率影像下的城区边界遥感提取方法,以及城区边界提取中"连接"的判断方法。结果表明,当前城区边界遥感提取主要面临3个问题:选用的标准、城区中的"连接"判断标准缺乏、自动化程度有待加强。提出了上述3个问题的解决思路:构建综合空间特征和人口特征,符合中国国情和特色的指标体系;探讨不同"连接"判断方法对城区边界提取结果的影响;将城区边界提取标准转化为机器学习算法,引入人工智能技术提升城区边界自动化提取程度。
Aiming at the problems that the current urban-rural statistical caliber and urban boundary extraction standards are not uniform,this paper systematically combed the relevant concepts and defining standards of urban boundary at home and abroad,urban boundary extraction methods with remote sensing images of different resolution,and the judgment method of"connection"to main urban areas.Results showed that there were three main problems in remote Sensing extraction of urban boundary at present:the criteria adopted to extract urban boundary need to be further discussed;the judgment of"connection"to main urban areas lacked objective,quantitative and unified criteria;and the degree of automation should be strengthened.The solutions to the above three problems were put forward as follows:construct an indicators system which integrated spatial and demographic characteristics and conformed to Chinese national conditions;explored the impact of different"connection"judgment methods on the results of urban boundary extraction;transform the urban boundary extraction criteria into machine learning algorithm,and introduce artificial intelligence technology to enhance the degree of automatic extraction of urban boundary.This paper can provide practical ideas for relevant scholars to carry out research on remote sensing extraction of urban boundary and unify the standards of urban boundary extraction.
Aiming at the problems that the current urban-rural statistical caliber and urban boundary extraction standards are not uniform,this paper systematically combed the relevant concepts and defining standards of urban boundary at home and abroad,urban boundary extraction methods with remote sensing images of different resolution,and the judgment method of"connection"to main urban areas.Results showed that there were three main problems in remote Sensing extraction of urban boundary at present:the criteria adopted to extract urban boundary need to be further discussed;the judgment of"connection"to main urban areas lacked objective,quantitative and unified criteria;and the degree of automation should be strengthened.The solutions to the above three problems were put forward as follows:construct an indicators system which integrated spatial and demographic characteristics and conformed to Chinese national conditions;explored the impact of different"connection"judgment methods on the results of urban boundary extraction;transform the urban boundary extraction criteria into machine learning algorithm,and introduce artificial intelligence technology to enhance the degree of automatic extraction of urban boundary.This paper can provide practical ideas for relevant scholars to carry out research on remote sensing extraction of urban boundary and unify the standards of urban boundary extraction.
引文
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[10]沈洁,罗翔.英国城乡地域的划分:标准、方法与历程[J].规划师,2015,31(8):139-144.(SHEN Jie,LUOXiang.British urban and rural areas division:standard,approach,and process[J].Planners,2015,31(8):139-144.)
[11]王智勇.中国的城乡划分与城镇化评估:基于国际比较的视角[J].人口与经济,2018(2):1-15.(WANGZhiyong.China’s rural-urban classification and urbanization evaluation:from the perspective of international comparison[J].Population&Economics,2018(2):1-15.)
[12]惠彦,金志丰,陈雯.城乡地域划分和城镇人口核定研究:以常熟市为例[J].地域研究与开发,2009,28(1):42-46.(HUI Yan,JIN Zhifeng,CHEN Wen.Study on urban rural area division and urban population counting:the case of Changshu city[J].Areal Research and Development,2009,28(1):42-46.)
[13]宁晓刚,王浩,林祥国,等.京津冀城市群1990-2015年城区时空扩展监测与分析[J].测绘学报,2018,47(9):1207-1215.(NING Xiaogang,WANG Hao,LINXiangguo,et al.Spatio-temporal urban sprawl monitoring and analysis over Beijing-Tianjin-Hebei Urban Agglomeration during 1990-2015[J].Acta Geodaetica et Cartographica Sinica,2018,47(9):1207-1215.)
[14]MERTES C M,SCHNEIDER A,SULLA M D,et al.Detecting change in urban areas at continental scales with MODIS data[J].Remote Sensing of Environment,2015,158:331-347.
[15]SCHNEIDER A,FRIEDL M A,POTERE D.Mapping global urban areas using MODIS 500mdata:new methods and datasets based on‘urban ecoregions’[J].Remote Sensing of Environment,2010,114(8):1733-1746.
[16]SON N T,CHEN C F,CHANG L Y,et al.Urban growth mapping from Landsat data using linear mixture model in Ho Chi Minh City,Vietnam[J].Journal of Applied Remote Sensing,2012,6(1):063543.
[17]WANG L,LI C,YING Q,et al.China’s urban expansion from 1990 to 2010 determined with satellite remote sensing[J].Chinese Science Bulletin,2012,57(22):2802-2812.
[18]JAT M K,GARG P K,KHARE D.Monitoring and modelling of urban sprawl using remote sensing and GIS techniques[J].International Journal of Applied Earth Observation and Geoinformation,2008,10(1):26-43.
[19]GAO F,DE COLSTOUN E B,MA R,et al.Mapping impervious surface expansion using medium-resolution satellite image time series:a case study in the Yangtze River Delta,China[J].International Journal of Remote Sensing,2012,33(24):7609-7628.
[20]SUN Z,WANG C,GUO H,et al.A modified normalized difference impervious surface index(MNDISI)for automatic urban mapping from Landsat imagery[J].Remote Sensing,2017,9(9):942-959.
[21]刘纪远,匡文慧,张增祥,等.20世纪80年代末以来中国土地利用变化的基本特征与空间格局[J].地理学报,2014,69(1):3-14.(LIU Jiyuan,KUANG Wenhui,ZHANG Zengxiang,et al.Spatiotemporal characteristics,patterns,and causes of land-use changes in China since the late 1980s[J].Journal of Geographical Sciences,2014,69(1):3-14.)
[22]陈军,陈利军,李然,等.基于GlobeLand30的全球城乡建设用地空间分布与变化统计分析[J].测绘学报,2015,44(11):1181-1188.(CHEN Jun,CHEN Lijun,LI Ran,et al.Spatial distribution and ten years change of global built-up areas derived from GlobeLand30[J].Acta Geodaetica et Cartographica Sinica,2015,44(11):1181-1188.)
[23]黄季焜,朱莉芬,邓祥征.中国建设用地扩张的区域差异及其影响因素[J].中国科学:地球科学,2007(9):1235-1241.(HUANG Jikun,ZHU Lifen,DENG Xiangzheng.Regional differences of China’s construction land expansion and its influencing factors[J].Science in China:Earth Sciences,2007(9):1235-1241.)
[24]LIU X,HU G,CHEN Y,et al.High-resolution multitemporal mapping of global urban land using Landsat images based on the Google Earth Engine Platform[J].Remote Sensing of Environment,2018,209:227-239.
[25]WAN B,GUO Q,FANG F,et al.Mapping US urban extents from MODIS data using one-class classification method[J].Remote Sensing,2015,7(8):10143-10163.
[26]GUINDON B,ZHANG Y,DILLABAUGH C.Landsat urban mapping based on a combined spectral-spatial methodology[J].Remote Sensing of Environment,2004,92(2):218-232.
[27]AUTHOR E B C,BELWARD A S.GLC2000:a new approach to global land cover mapping from Earth observation data[J].International Journal of Remote Sensing,2005,26(9):1959-1977.
[28]COSTA J N D,BIELECKA E,CALKA B,et al.Uncertainty quantification of the global rural-urban mapping project over Polish census data[C]∥Environmental Engineering.[S.l.]:[s.n.],2016.
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