武汉市主城区用地结构遥感监测及动态变化
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摘要
城市内部用地结构及其时空演变特征不仅能一定程度上反映出城市社会经济发展水平、预示城市未来发展空间和发展潜力,而且还会直接影响城市人居环境的适宜性,不同地区和不同发展阶段城市内部用地结构存在明显差异。本文基于武汉市1990、2000、2010和2018年4期Landsat TM/OLI遥感影像,采用面向对象多尺度分割算法对武汉市主城区内部用地结构进行了长时间序列遥感监测研究,并在此基础上分析了城市用地结构的时空演变特征。研究表明:1990-2018年武汉市主城区用地结构类型以不透水层、植被和水体为主,用地结构演变模式主要表现为植被和水体向不透水层的转化。主城区内部不透水层面积由1990年的329.73 km~2增加至2018年466.69 km~2,增加了136.96 km~2;植被和水体面积则由1990年的332.74 km~2、318.26 km~2减少到2018年的320.46 km~2、196.39 km~2,分别减少了12.28 km~2、121.87 km~2;裸土地面积较小,整体变化不如前3种用地类型显著。本研究可为城市功能用地制图、城市用地效率分析以及城市生态环境质量综合评价提供参考。
The land use structure and its spatio-temporal evolution characteristics within cities can not only reflect the level of urban economic development, but also predict the future development space and development potential of the city and even directly affect the suitability of the urban human settlement environment. There are significant differences in the internal land use structure of cities in different stages of development and different regions. In this paper, we used object-oriented multi-scale segmentation algorithm to carry out long-term remote sensing monitoring on the internal land cover structure of Wuhan main urban area based on the Landsat TM/OLI remote sensing images of 1990, 2000, 2010 and 2018. Then, the land use patterns in Wuhan were monitored,and the characteristics of land use structure changes during the 1990, 2000, 2010 and 2018 were further discussed. The research shows that: the internal land-use structure in the main urban area of Wuhan city is dominated by impervious surface, vegetation, and waterbody during the recent 28 years. The land use change pattern mainly reflects the transformation of vegetation and waterbody into impervious surface. From 1990 to2018, impervious surface is the main type of land use in the study area, which increased from 329.73 km~2 in1990 to 466.69 km~2 in 2018, which increased by 136.96 km~2. The vegetation and waterbody area decreased from332.74 km~2, 318.26 km~2 in 1990 to 320.46 km~2, 196.39 km~2 in 2018 respectively, which decreased by 12.28 km~2 and 121.87 km~2 respectively; bare land area is too small, and it's change is not as significant as the first three types of land changes. This study can provide reference for urban functional land mapping, urban land efficiency analysis and comprehensive evaluation of urban ecological environment quality.
The land use structure and its spatio-temporal evolution characteristics within cities can not only reflect the level of urban economic development, but also predict the future development space and development potential of the city and even directly affect the suitability of the urban human settlement environment. There are significant differences in the internal land use structure of cities in different stages of development and different regions. In this paper, we used object-oriented multi-scale segmentation algorithm to carry out long-term remote sensing monitoring on the internal land cover structure of Wuhan main urban area based on the Landsat TM/OLI remote sensing images of 1990, 2000, 2010 and 2018. Then, the land use patterns in Wuhan were monitored,and the characteristics of land use structure changes during the 1990, 2000, 2010 and 2018 were further discussed. The research shows that: the internal land-use structure in the main urban area of Wuhan city is dominated by impervious surface, vegetation, and waterbody during the recent 28 years. The land use change pattern mainly reflects the transformation of vegetation and waterbody into impervious surface. From 1990 to2018, impervious surface is the main type of land use in the study area, which increased from 329.73 km~2 in1990 to 466.69 km~2 in 2018, which increased by 136.96 km~2. The vegetation and waterbody area decreased from332.74 km~2, 318.26 km~2 in 1990 to 320.46 km~2, 196.39 km~2 in 2018 respectively, which decreased by 12.28 km~2 and 121.87 km~2 respectively; bare land area is too small, and it's change is not as significant as the first three types of land changes. This study can provide reference for urban functional land mapping, urban land efficiency analysis and comprehensive evaluation of urban ecological environment quality.
引文
[1]刘纪远,宁佳,匡文慧,等.2010-2015年中国土地利用变化的时空格局与新特征[J].地理学报,2018,73(5):789-802.[Liu J Y,Ning J,Kuang W H,et al.Spatio-temporal patterns and characteristics of land-use change in China during 2010-2015[J].Acta Geographica Sinica,2018,73(5):789-802.]
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[4]Mooney H A,Duraiappah A,Larigauderie A.Evolution of natural and social science interactions in global change research programs[J].Proceedings of the National Academy of Sciences,2013,110(1):3665-3672.
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[8]匡文慧,刘纪远,陆灯盛.京津唐城市群不透水地表增长格局以及水环境效应[J].地理学报,2011,66(11):1486-1496.[Kuang W H,Liu J Y,Lu D S.Pattern of impervious surface change and its effect on water environment in the Beijing-Tianjin-Tangshan metropolitan area[J].Acta Geographica Sinica,2011,66(11):1486-1496.]
[9]侯西勇,邸向红,侯婉,等.中国海岸带土地利用遥感制图及精度评价[J].地球信息科学学报,2018,20(10):1478-1488.[Hou X Y,Di X H,Hou W,et al.Accuracy evaluation of land use mapping using remotesensing techniques in Coastal Zone of China[J].Journal of Geo-information Science,2018,20(10):1478-1488.]
[10]宋明明,都金康,郑文龙,等.秦淮河流域近30年不透水面景观格局时空演变研究[J].地球信息科学学报,2017,19(2):238-247.[Song M M,Du J K,Zheng W L,et al.Quantifying the spatial-temporal changes of impervious surface landscape pattern from 1988 to 2015 in Qinhuai River Basin[J].Journal of Geo-information Science,2017,19(2):238-247.]
[11]金晶,王斌,张立明.基于线性光谱混合分析的城市不透水层分布估算[J].复旦学报(自然科学版),2010,49(2):197-208,273-274.[Jin J,Wang B,Zhang L M.Estimating urban impervious surface distribution by linear spectral mixture analysis[J].Journal of Fudan University(Natural Science),2010,49(2):197-208,273-274.]
[12]常变蓉,李仁东.武汉市建设用地扩张遥感监测及空间分异分析[J].国土资源遥感,2017,29(3):118-123.[Chan B R,Li R D.A study of remote sensing monitoring and spatial variation of construction land expansion in Wuhan[J].Remote Sensing for Land&Resources,2017,29(3):118-123.]
[13]张扬,刘艳芳,刘以.武汉市不透水地表时空格局分析[J].地理科学,2017,37(12):1917-1924.[Zhang Y,Liu Y F,Liu Y.Spatial and temporal patterns analysis of impervious surface in Wuhan City[J].Scientia Geographica Sinica,2017,37(12):1917-1924.]
[14]黄靖,夏智宏.基于MODIS遥感数据的武汉市植被覆盖变化监测分析[J].气象与环境科学,2009,32(2):16-20.[Huang J,Xia Z H.Analysis for monitoring vegetation coverage change of Wuhan based on remote sensing data of MODIS[J].Meteorological and Environmental Science,2009,32(2):16-20.]
[15]淡永利,王宏志,张欢,等.2000-2010年武汉市中心城区湖泊景观变化[J].生态学报,2014,34(5):1311-1317.[Dan Y L,Wang H Z,Zhang H,et al.Lakes evolution of central Wuhan during 2000 to 2010[J].Acta Ecologica Sinica,2014,34(5):1311-1317.]
[16]李忠锋,王一谋,冯毓荪,等.基于RS与GIS的榆林地区土地利用变化分析[J].水土保持学报,2003,17(2):97-99,140.[Li Z F,Wang Y M,Feng Y S,et al.Analysis of land use change in Yulin prefecture based on RS and GIS[J].Journal of Soil and Water Conservation,2003,17(2):97-99,140.]
[17]赵健,魏成阶,黄丽芳,等.土地利用动态变化的研究方法及其在海南岛的应用[J].地理研究,2001,20(6):723-730,774.[Zhao J,Wei C J,Huang L F.Research methods of land use changes and their applications in Hainan Island[J].Geographical Research,2001,20(6):723-730,774.]
[18]李丽娟,杨俊伟,姜德娟,等.20世纪90年代无定河流域土地利用的时空变化[J].地理研究,2005,24(4):527-534,656.[Li L J,Yang J W,Jiang D J,et al.GIS based study on spatial temporal changes of land use in Wuding River Basin in the 1990s[J].Geographical Research,2005,24(4):527-534,656.]
[19]冯昕,杜世宏,张方利,等.基于多尺度融合的高分辨率影像城市用地分类[J].地理与地理信息科学,2013,29(3):43-47,127.[Feng X,Du S H,Zhang F L.Urban land classification of high resolution images based on multiscale fusion[J].Geography and Geo-Information Science,2013,29(3):43-47,127.]
[20]Benz U C,Hofmann P,Willhauck G,et al.Multi-resolution,object-oriented fuzzy analysis of remote sensing data for GIS-ready information[J].ISPRS Journal of Photogrammetry and Remote Sensing,2003,58(3):239-258.
[21]Walker J,Blaschke T.Object-based land-cover classification for the Phoenix metropolitan area:optimization vs.transportability[J].International Journal of Remote Sensing,2008,29(7):2021-2040.
[22]王蕾,杨武年,任金铜,等.GF-2影像面向对象典型城区地物提取方法[J].测绘通报,2018(1):138-142.[Wang L,Yang W N,Ren J T,et al.Object-oriented extraction method of typical urban features based on GF-2 images[J].Bulletin of Surveying and Mapping,2018(1):138-142.]
[23]Tian J,Chen D M.Optimization in multi-scale segmentation of high-resolution satellite images for artificial feature recognition[J].International Journal of Remote Sensing,2007,28(20):4625-4644.
[24]陈斌,王宏志,李仁东.不同等级土壤遥感分类的尺度匹配性探讨[J].湖北大学学报(自然科学版),2018,40(4):429-436.[Chen B,Wang H Z,Li R D.The discussion of scale matching of different types of soil remote sensing classification[J].Journal of Hubei University(Natural Science),2018,40(4):429-436.]
[25]姚国红,张锦,王励.面向对象的高分辨率遥感影像地理要素提取[J].测绘科学,2012,37(6):53-55,61.[Yao G H,Zhang J,Wang L.Object-oriented feature extraction utilizing high resolution remote sensing imagery[J].Science of Surveying and Mapping,2012,37(6):53-55,61.]
[26]Zhao Q M,Molenaar M,Tempfli K,et al.Quality assessment for geo-spatial objects derived from remotely sensed data[J].International Journal of Remote Sensing,2005,26(14):2953-2974.
[2]Wulder M A,White J C,Goward S N,et al.Landsat continuity:Issues and opportunities for land cover monitoring[J].Remote Sensing of Environment,2008,112:955-969.
[3]陆大道,陈明星.关于“国家新型城镇化规划(2014-2020)”编制大背景的几点认识[J].地理学报,2015,70(2):179-185.[Lu D D,Chen M X.Several viewpoints on the background of compiling the"National New Urbanization Planning(2014-2020)"[J].Acta Geographica Sinica,2015,70(2):179-185.]
[4]Mooney H A,Duraiappah A,Larigauderie A.Evolution of natural and social science interactions in global change research programs[J].Proceedings of the National Academy of Sciences,2013,110(1):3665-3672.
[5]Lawler J J,Lewis J D,Nelson E,et al.Projected land-use change impacts on ecosystem services in the United States[J].Proceedings of the National Academy of Sciences,2014,111(20):7492-7497.
[6]匡文慧.区域尺度城市增长时空动态模型及其在京津唐都市圈应用[J].地理学报,2011,66(2):317-330.[Kuang W H.Simulating dynamic urban expansion at regional scale in Beijing-Tianjin-Tangshan Metropolitan Area[J].Acta Geographica Sinica,2011,66(2):317-330.]
[7]匡文慧,迟文峰,史文娇.中国与美国大都市区城市内部土地覆盖结构时空差异[J].地理学报,2014,69(7):883-895.[Kuang W H,Chi W F,Shi W J.Spatial-temporal characteristics of intra-urban land cover in the cities of China and USA from 1978 and 2010[J].Acta Geographica Sinica,2014,69(7):883-895.]
[8]匡文慧,刘纪远,陆灯盛.京津唐城市群不透水地表增长格局以及水环境效应[J].地理学报,2011,66(11):1486-1496.[Kuang W H,Liu J Y,Lu D S.Pattern of impervious surface change and its effect on water environment in the Beijing-Tianjin-Tangshan metropolitan area[J].Acta Geographica Sinica,2011,66(11):1486-1496.]
[9]侯西勇,邸向红,侯婉,等.中国海岸带土地利用遥感制图及精度评价[J].地球信息科学学报,2018,20(10):1478-1488.[Hou X Y,Di X H,Hou W,et al.Accuracy evaluation of land use mapping using remotesensing techniques in Coastal Zone of China[J].Journal of Geo-information Science,2018,20(10):1478-1488.]
[10]宋明明,都金康,郑文龙,等.秦淮河流域近30年不透水面景观格局时空演变研究[J].地球信息科学学报,2017,19(2):238-247.[Song M M,Du J K,Zheng W L,et al.Quantifying the spatial-temporal changes of impervious surface landscape pattern from 1988 to 2015 in Qinhuai River Basin[J].Journal of Geo-information Science,2017,19(2):238-247.]
[11]金晶,王斌,张立明.基于线性光谱混合分析的城市不透水层分布估算[J].复旦学报(自然科学版),2010,49(2):197-208,273-274.[Jin J,Wang B,Zhang L M.Estimating urban impervious surface distribution by linear spectral mixture analysis[J].Journal of Fudan University(Natural Science),2010,49(2):197-208,273-274.]
[12]常变蓉,李仁东.武汉市建设用地扩张遥感监测及空间分异分析[J].国土资源遥感,2017,29(3):118-123.[Chan B R,Li R D.A study of remote sensing monitoring and spatial variation of construction land expansion in Wuhan[J].Remote Sensing for Land&Resources,2017,29(3):118-123.]
[13]张扬,刘艳芳,刘以.武汉市不透水地表时空格局分析[J].地理科学,2017,37(12):1917-1924.[Zhang Y,Liu Y F,Liu Y.Spatial and temporal patterns analysis of impervious surface in Wuhan City[J].Scientia Geographica Sinica,2017,37(12):1917-1924.]
[14]黄靖,夏智宏.基于MODIS遥感数据的武汉市植被覆盖变化监测分析[J].气象与环境科学,2009,32(2):16-20.[Huang J,Xia Z H.Analysis for monitoring vegetation coverage change of Wuhan based on remote sensing data of MODIS[J].Meteorological and Environmental Science,2009,32(2):16-20.]
[15]淡永利,王宏志,张欢,等.2000-2010年武汉市中心城区湖泊景观变化[J].生态学报,2014,34(5):1311-1317.[Dan Y L,Wang H Z,Zhang H,et al.Lakes evolution of central Wuhan during 2000 to 2010[J].Acta Ecologica Sinica,2014,34(5):1311-1317.]
[16]李忠锋,王一谋,冯毓荪,等.基于RS与GIS的榆林地区土地利用变化分析[J].水土保持学报,2003,17(2):97-99,140.[Li Z F,Wang Y M,Feng Y S,et al.Analysis of land use change in Yulin prefecture based on RS and GIS[J].Journal of Soil and Water Conservation,2003,17(2):97-99,140.]
[17]赵健,魏成阶,黄丽芳,等.土地利用动态变化的研究方法及其在海南岛的应用[J].地理研究,2001,20(6):723-730,774.[Zhao J,Wei C J,Huang L F.Research methods of land use changes and their applications in Hainan Island[J].Geographical Research,2001,20(6):723-730,774.]
[18]李丽娟,杨俊伟,姜德娟,等.20世纪90年代无定河流域土地利用的时空变化[J].地理研究,2005,24(4):527-534,656.[Li L J,Yang J W,Jiang D J,et al.GIS based study on spatial temporal changes of land use in Wuding River Basin in the 1990s[J].Geographical Research,2005,24(4):527-534,656.]
[19]冯昕,杜世宏,张方利,等.基于多尺度融合的高分辨率影像城市用地分类[J].地理与地理信息科学,2013,29(3):43-47,127.[Feng X,Du S H,Zhang F L.Urban land classification of high resolution images based on multiscale fusion[J].Geography and Geo-Information Science,2013,29(3):43-47,127.]
[20]Benz U C,Hofmann P,Willhauck G,et al.Multi-resolution,object-oriented fuzzy analysis of remote sensing data for GIS-ready information[J].ISPRS Journal of Photogrammetry and Remote Sensing,2003,58(3):239-258.
[21]Walker J,Blaschke T.Object-based land-cover classification for the Phoenix metropolitan area:optimization vs.transportability[J].International Journal of Remote Sensing,2008,29(7):2021-2040.
[22]王蕾,杨武年,任金铜,等.GF-2影像面向对象典型城区地物提取方法[J].测绘通报,2018(1):138-142.[Wang L,Yang W N,Ren J T,et al.Object-oriented extraction method of typical urban features based on GF-2 images[J].Bulletin of Surveying and Mapping,2018(1):138-142.]
[23]Tian J,Chen D M.Optimization in multi-scale segmentation of high-resolution satellite images for artificial feature recognition[J].International Journal of Remote Sensing,2007,28(20):4625-4644.
[24]陈斌,王宏志,李仁东.不同等级土壤遥感分类的尺度匹配性探讨[J].湖北大学学报(自然科学版),2018,40(4):429-436.[Chen B,Wang H Z,Li R D.The discussion of scale matching of different types of soil remote sensing classification[J].Journal of Hubei University(Natural Science),2018,40(4):429-436.]
[25]姚国红,张锦,王励.面向对象的高分辨率遥感影像地理要素提取[J].测绘科学,2012,37(6):53-55,61.[Yao G H,Zhang J,Wang L.Object-oriented feature extraction utilizing high resolution remote sensing imagery[J].Science of Surveying and Mapping,2012,37(6):53-55,61.]
[26]Zhao Q M,Molenaar M,Tempfli K,et al.Quality assessment for geo-spatial objects derived from remotely sensed data[J].International Journal of Remote Sensing,2005,26(14):2953-2974.