鄯善县土地利用变化检测研究
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摘要
自1972年美国发射第一颗陆地资源卫星以来,对地观测卫星发展迅速,应用领域不断扩大,应用成效也得到不断提高。由于遥感技术可以提供最佳的信息获取方式,并且不受地形阻隔等限制,具有实时、快速、覆盖范围广、高空间分辨率、高光谱分辨率、高时相分辨率等特点。经过近30多年的发展,遥感技术已经成为采集地球数据及其变化信息的重要技术手段,并广泛渗透到国民经济的各个领域。
上世纪80年代,美国、日本和欧洲空间局相继提出了对地观测计划(EOS),从此利用遥感影像进行土地利用变化检测就越来越多的为研究者们所关注,但是传统土地利用检测方法主要通过野外土地清查,或根据像片进行解译分析得来。这类方法存在的问题是检测结果在时间上不一致,且工作量大,现时性低,更新困难(史培军,1996)。土地利用状态的数据和信息的快速更新已成为困扰遥感、地理信息系统等领域的一个技术难题,研究如何准确快速地从己获取的地理数据中发现变化如何自动地从影像中提取所需地物的变化等理论和技术对于土地利用/覆盖图件快速更新具有十分重要的意义(睦海刚,2002) ,本论文则是基于此展开的。
本文从近年来基于遥感影像的土地利用变化检测发展出发,总结出较为常用的变化检测方法,经过对比分析,采用遥感检测方法中的分类后比较法进行检测,以鄯善县1990年、1999年及2008年三期遥感影像和鄯善县91年和2005年土地利用现状图为研究数据,探讨了遥感变化检测三大流程:图像预处理、变化信息获取以及后处理的具体实施过程,在得到变化信息的基础上结合土地利用动态模型分析了研究区土地利用的时空变化情况,并进行了模拟预测。
Since 1972, the United States launched the first Land Resource Satellites, Earth observation satellite developed rapidly, its application field and application effect is expanding constantly improving. Due to the remote sensing technique can provide the best information acquisition modes, and not block etc, terrain, rapid, real-time bestrew scope, high spatial resolution ,high resolution and high resolution phase, etc. After nearly 30 years of development, use the remote sensing data collecting earth changes has become a the important information and technology, and has been widely permeates every field of national economy.
In the 1980s, the United States, Japan and the European space agency have proposed to the earth observation plan (EOS), remote sensing image of land use change detection, has had more and more concern of researchers, but traditional land use/covering mainly through the field detection method based on field measurement or check Pictures for linear-ring .This kind of method is obtained in time inconsistency, big workload, time-consuming, the difficult to update (Shi Peijun, 1996). Updating the LUCC state data and information rapidly has become a technical problem in fields such as Remote Sensing and Geographic Information System. The research on how to accurately and rapidly discover the change of geographic data we have had, and how to automatically extract the needed change-information from the image. The theory and technology for LUCC maps’updating, covering has important significance (Hanging Mu2002) this paper is sincerity based on these topics.
This article, in view of the development of the land use change detection which based on remote sensing image, raise the change detection methods which are used regularly, through comparison and analysis, using remote sensing detection methods of classification comparison. used the Shanshan county region’remote sensing images in 1990, 1999 and 2008 and phase land use status in 91 and 2005, the study of remote sensing data, and discusses the three process change detection: image preprocessing, change information acquisition and the concrete implementation process, later, article used the result of land use based on information dynamic model is analyzed and studied area of land use changes, and simulated forecast.
上世纪80年代,美国、日本和欧洲空间局相继提出了对地观测计划(EOS),从此利用遥感影像进行土地利用变化检测就越来越多的为研究者们所关注,但是传统土地利用检测方法主要通过野外土地清查,或根据像片进行解译分析得来。这类方法存在的问题是检测结果在时间上不一致,且工作量大,现时性低,更新困难(史培军,1996)。土地利用状态的数据和信息的快速更新已成为困扰遥感、地理信息系统等领域的一个技术难题,研究如何准确快速地从己获取的地理数据中发现变化如何自动地从影像中提取所需地物的变化等理论和技术对于土地利用/覆盖图件快速更新具有十分重要的意义(睦海刚,2002) ,本论文则是基于此展开的。
本文从近年来基于遥感影像的土地利用变化检测发展出发,总结出较为常用的变化检测方法,经过对比分析,采用遥感检测方法中的分类后比较法进行检测,以鄯善县1990年、1999年及2008年三期遥感影像和鄯善县91年和2005年土地利用现状图为研究数据,探讨了遥感变化检测三大流程:图像预处理、变化信息获取以及后处理的具体实施过程,在得到变化信息的基础上结合土地利用动态模型分析了研究区土地利用的时空变化情况,并进行了模拟预测。
Since 1972, the United States launched the first Land Resource Satellites, Earth observation satellite developed rapidly, its application field and application effect is expanding constantly improving. Due to the remote sensing technique can provide the best information acquisition modes, and not block etc, terrain, rapid, real-time bestrew scope, high spatial resolution ,high resolution and high resolution phase, etc. After nearly 30 years of development, use the remote sensing data collecting earth changes has become a the important information and technology, and has been widely permeates every field of national economy.
In the 1980s, the United States, Japan and the European space agency have proposed to the earth observation plan (EOS), remote sensing image of land use change detection, has had more and more concern of researchers, but traditional land use/covering mainly through the field detection method based on field measurement or check Pictures for linear-ring .This kind of method is obtained in time inconsistency, big workload, time-consuming, the difficult to update (Shi Peijun, 1996). Updating the LUCC state data and information rapidly has become a technical problem in fields such as Remote Sensing and Geographic Information System. The research on how to accurately and rapidly discover the change of geographic data we have had, and how to automatically extract the needed change-information from the image. The theory and technology for LUCC maps’updating, covering has important significance (Hanging Mu2002) this paper is sincerity based on these topics.
This article, in view of the development of the land use change detection which based on remote sensing image, raise the change detection methods which are used regularly, through comparison and analysis, using remote sensing detection methods of classification comparison. used the Shanshan county region’remote sensing images in 1990, 1999 and 2008 and phase land use status in 91 and 2005, the study of remote sensing data, and discusses the three process change detection: image preprocessing, change information acquisition and the concrete implementation process, later, article used the result of land use based on information dynamic model is analyzed and studied area of land use changes, and simulated forecast.
引文
[1]房自立.基于结构信息的多时相遥感图像变化检测方法研究措施[D].国防科技大学,2006(6).
[2]《全国土地利用总体规划纲要(2005-2020)》.
[3]刘纪远,布和敖斯尔.中国土地利用变化现代化过程时空特征的研究一基于卫星遥感数据[J].第四纪研究.2000,20(3):229-239.
[4]布和敖斯尔,刘纪远,王长耀.遥感在我国资源与环境变化研究中的作用[J].科技导报.1997,110(8):14-18.
[5]史培军,宫鹏,李晓兵等.土地利用/覆盖变化研究的方法与实践[M].科学出版社.1996.
[6]睦海刚.基于特征的道路网自动变化检测方法研究[D].武汉大学博士论文:武汉大学,2002.
[7] Li L and Leung M K H .Integrating intensity and texture difference for robust change detection .IEEE Transaction On Image Processing,2002,11 (2):105-112.
[8]方圣辉,佃袁勇,李微.基于边缘特征的变化检测方法研究[J].武汉大学学报信息科学版.2005,20(5):135一138.
[9] Bruzzone L and Prieto D F.Unsupervised change detectiong in multisource and multisensory remote sensing images.IEEE Trans on Geoscience and Remote Sensing.2000,6:2441-2443.
[10] Cao G Z,Chen J and Jiang J P.A nocel local invariant descriptor adapted to mobole robot vision.Proceeding of the American Control Conference.2004.vol.3:2196-2201.
[11] Cavallaro A and Ebrahimi T.Change detection based on color edges.Proc.of IEEE Intermational Symposium on Circuits and Systems,Sydney,Australia.2001.
[12] Cavallaro A and Ebrahimi T.Classification of Change detection algorithms for object-based applications.Proc.Of workshop on Image Analysis for Multimedian Interactive Services.2003.
[13] Chen T,Yu W X,Jiang Y M and Su Y.Struture change detection of images based in biological vision principle.MIPPR 2005:Image Analysis Techniques.Proc.of SPIE,2005,Vol.604405-1.
[14] Petit,C.C.,and Lambin,E.F.,Intergration of multi-source remote sensing data for land cover chang detection.International Journal of Geographical Informationa Science,2001,15:785-803.
[15] Petit,C.,Scudder,T.,and Lambin E.,Quantifying processes of land-cover change by sensing:reserrlement and rapid land-cover change in southeastern Zambia InternationalJournal of Remote Sensong,2001,22:3435-3456.
[16] Robinson,J.W.,A critical review of the change detection and urban classification literature.TechnicalmemorandumCSC/TM-79/6235,ComputerSciencesCorporation,Silver Spring,Maryland,U.S.A.1979.
[17] Weng,Q.,Land use change analysis in the Zhujiang Delta of China using satellitr remote sensing,GIS and stochastic modeling.Journal of Envirinmental Management,2002,64:273-284.
[18]赵英时.遥感应用分析原理与方法.北京:科学出版社,2003.
[19]钟家强.基于多时相遥感图像的变化检测:博士学位论文.长沙:国防科学技术大学,2005.
[20] Radke R J,Andra S,IA一Kofahi O and Roysam B.Image chage detection algorithms :A systemtic survey.1EEE Transaction On Image processing,2005,14(3):294一307.
[21] Dia X and Khorram S.The effects of image misregistretion on the accuracy of remotely sensed chang detection.IEEE Trans on Geoscience and Remote Sensing,1998,36(5):1566-1577.
[22]张路,基于多元统计分析的遥感影像变化检测方法研究:博士论文.武汉:武汉大学,2004
[23] Elvidge CD,Yuan D and Ridgeway D W.Relative radiometric normalization of Landsat Multispectral Scanner(MSS) data using automatic scattergram-Controlled regression.Photogrammetric Engineering and Remote Sensing,1995,61(10):1255一1260.
[24] LuiSC,FuCW and change S.Statistical change detection with momets under Time-varying illumination.IEEE Transaction on Image Processing 1998,(7)9:1258-1268.
[25] Costantini R.Counter illumination variations in a video surveillance environment, Electronic Imaging Conference,San Jose,USA.Proc.of SPIE,2001.
[26] Miller L,Nualchawee k,Tom C.Analysis of the Dynamics of-Shifting Cultivation in the Tropical Forests of Northern Thailand Using Landscape Modeling and Class frication of Landsat Imager[R].Greenbel,Maryland,U.S.A.:NASA Technical Memorandum ,Goddard Space Flight Centre,1978.
[27]李月臣,杨华,刘春霞.土地覆盖变化遥感检测方法[J].水土保持研究.2006,2(1):210-213.
[28]党安荣,王晓栋,陈晓峰.遥感图像处理方法[M].北京:清华大学出版社,2004.
[29]冯春,郭建宁,闵祥军.土地利用/土地覆盖遥感变化检测方法新进展[J].遥感信息.2006,3:81 84.
[30]吴芳,刘荣,田维春等.遥感变化检测技术及其应用综述[J].地理空间信息.2007(5).
[31]冯春,郭建宁,李杏朝等.土地利用/覆盖变化检测方法新进展[J]遥感信息,2006(3).
[32] J.Morisette,S.Khorram,and T.Mace.Land-cover change detection enhanced with generalized linear model[J].Int.J.Remote Sensing.1999(20):2703-2721.
[33] Macleod R.D.A quantitative comparison of change detection algorithms for monitoring eelgrass from remotely sensed data[J].PE & RS.1998,64(3): 207~216.
[34]新疆统计年年鉴[M].中国统计出版社.1999-2007.
[35]鄯善总体规划设计书.鄯善县国土资源局.2005.
[36]马蔼乃等.遥感信息模型[M].北京:北京大学出版社,1997.13～21.
[37]戴昌达,胡得永.TM数据的信息特征[J].遥感信息,1987(2):5-8.
[38]戴昌达,雷莉萍.TM图像的光谱信息特征与最佳波段组合[J].环境遥感.1989,4(4):282-292.
[39]Towsherd Y.R.et al.Preliminary analysis of Landsat-4 Thermatic Mapperproducts[J].International journal of remote sensing.1983,(4):817～823.
[40]Charvez P.Set. A Statistic method for selecting Landsat MSS ratio [J].Journal applied. photographic engineering.1982,8(1):23～30.
[41]Pat S.Chavez, Jr Digital processing techniques for image mapping withLandsat TM and SPOT simulator data[C].Eighteenth international symposiumon remote sensing of enviorment.Paris,France,1984.
[43]陈德超.TM与SPOT影像融合算法比较研究[J].遥感技术与应用.2001,16(2):110-115.
[44]詹才保.基于GIS技术的大城市边缘区土地利用变化及驱动力研究[R].中国科学院地理科学与资源研究所硕士研究报告,2001,6.
[45]王建.图像融合在引大灌区土地覆盖调查中的应用[J].遥感技术与应用.2001,16(3):173-177.
[46]王萍,张继贤,林宗坚,李春霞.基于多源遥感数据融合的土地利用/土地覆盖变化信息提取试验[J].测绘通报.2003.4:14～17.
[47]周前祥,敬忠良,姜世忠.不同光谱与空间分辨率遥感图像融合方法的理论研究[J].遥感技术与应用.2003.18(1):41～46.
[49]肖桂荣.基于遥感与GIS的县级土地利用动态监测与更新研究——以长乐市为例[D].福州大学硕士研究生论文,2002.12.
[50]冉有华,李文君,陈贤章.TM图像土地利用分类精度验证与评估——以定西县为例[J].遥感技术与应用.2003,18(2):81-86.
[51]陈本清.利用多时相卫星遥感影像对厦门市城市化进程及环境变化进行动态监测与分析[D].福州大学硕士研究生毕业论文,2002.3.
[52]赵英时.遥感应用分析原理与方法[M].科学出版社,2003.6.
[53]郭笃发.利用马尔科夫过程预测黄河三角洲新生湿地土地利用/覆被格局的变化[M].土壤38(1):42-47.
[54]李大平,丁建丽,何祺胜.基于马氏链首达时间的干旱区LUCC过程研究[J].国土资源科技馆理.2006,05
[55]张滢,丁建丽.绿洲土地利用变化未来趋势预测及其调控研究[J].干旱区资源与环境.2006,11(6).
[56]塔西甫拉提·特依拜,赵睿,丁建丽等.干旱区绿洲LUCC马尔可夫过程分析—以新疆和田绿洲为例[J].干旱区地理,2006,8(4).
[57]李东,苏小红等.基于新灰色马尔科夫模型的股价预测方法[J].哈尔滨工业大学学报.2003,35(2):244-249.
[58]高玉进.干旱区土地利用与土地覆盖变化对绿洲稳定性的影响研究[D].新疆大学硕士学位论文,2004.
[59]颜亮.基于RS和地学信息图谱的石河子市土地利用/覆被变化研究及预测分析[D].新疆大学硕士学位论文,2008.
[60]丁建丽,张滢,塔西甫拉提·特依拜.绿洲—荒漠交错带土地利用/覆盖时空变化研究[J].环境科学研究,2006,19(6).
[61]张雷.矿产资源开发与国家工业化[M].北京:商务印书馆,2004 [ ZHANG Lei: Mineral Resources Exploitation and National Industrialization[M] ] . Beijing : The Commercial /rests,2004(1).
[62]吴传钧.人地关系与经济布局(吴传钧文集)[M].北京:学苑出版社,2008.
[63]李进笃.自然能模型——人与自然和谐的数理证译[J].济南大学学报,2004,(2).
[64] Munasinghe M and Mcmeely J, Key Concepts and Terminology of Sustainable development[M].Defin- ing and Measuring Sustainability,The Bio-geophysical Foundation, New York,1996.
[65]张雷.中国区域发展的资源环境基础[M].北京:科学出版社,2006.
[2]《全国土地利用总体规划纲要(2005-2020)》.
[3]刘纪远,布和敖斯尔.中国土地利用变化现代化过程时空特征的研究一基于卫星遥感数据[J].第四纪研究.2000,20(3):229-239.
[4]布和敖斯尔,刘纪远,王长耀.遥感在我国资源与环境变化研究中的作用[J].科技导报.1997,110(8):14-18.
[5]史培军,宫鹏,李晓兵等.土地利用/覆盖变化研究的方法与实践[M].科学出版社.1996.
[6]睦海刚.基于特征的道路网自动变化检测方法研究[D].武汉大学博士论文:武汉大学,2002.
[7] Li L and Leung M K H .Integrating intensity and texture difference for robust change detection .IEEE Transaction On Image Processing,2002,11 (2):105-112.
[8]方圣辉,佃袁勇,李微.基于边缘特征的变化检测方法研究[J].武汉大学学报信息科学版.2005,20(5):135一138.
[9] Bruzzone L and Prieto D F.Unsupervised change detectiong in multisource and multisensory remote sensing images.IEEE Trans on Geoscience and Remote Sensing.2000,6:2441-2443.
[10] Cao G Z,Chen J and Jiang J P.A nocel local invariant descriptor adapted to mobole robot vision.Proceeding of the American Control Conference.2004.vol.3:2196-2201.
[11] Cavallaro A and Ebrahimi T.Change detection based on color edges.Proc.of IEEE Intermational Symposium on Circuits and Systems,Sydney,Australia.2001.
[12] Cavallaro A and Ebrahimi T.Classification of Change detection algorithms for object-based applications.Proc.Of workshop on Image Analysis for Multimedian Interactive Services.2003.
[13] Chen T,Yu W X,Jiang Y M and Su Y.Struture change detection of images based in biological vision principle.MIPPR 2005:Image Analysis Techniques.Proc.of SPIE,2005,Vol.604405-1.
[14] Petit,C.C.,and Lambin,E.F.,Intergration of multi-source remote sensing data for land cover chang detection.International Journal of Geographical Informationa Science,2001,15:785-803.
[15] Petit,C.,Scudder,T.,and Lambin E.,Quantifying processes of land-cover change by sensing:reserrlement and rapid land-cover change in southeastern Zambia InternationalJournal of Remote Sensong,2001,22:3435-3456.
[16] Robinson,J.W.,A critical review of the change detection and urban classification literature.TechnicalmemorandumCSC/TM-79/6235,ComputerSciencesCorporation,Silver Spring,Maryland,U.S.A.1979.
[17] Weng,Q.,Land use change analysis in the Zhujiang Delta of China using satellitr remote sensing,GIS and stochastic modeling.Journal of Envirinmental Management,2002,64:273-284.
[18]赵英时.遥感应用分析原理与方法.北京:科学出版社,2003.
[19]钟家强.基于多时相遥感图像的变化检测:博士学位论文.长沙:国防科学技术大学,2005.
[20] Radke R J,Andra S,IA一Kofahi O and Roysam B.Image chage detection algorithms :A systemtic survey.1EEE Transaction On Image processing,2005,14(3):294一307.
[21] Dia X and Khorram S.The effects of image misregistretion on the accuracy of remotely sensed chang detection.IEEE Trans on Geoscience and Remote Sensing,1998,36(5):1566-1577.
[22]张路,基于多元统计分析的遥感影像变化检测方法研究:博士论文.武汉:武汉大学,2004
[23] Elvidge CD,Yuan D and Ridgeway D W.Relative radiometric normalization of Landsat Multispectral Scanner(MSS) data using automatic scattergram-Controlled regression.Photogrammetric Engineering and Remote Sensing,1995,61(10):1255一1260.
[24] LuiSC,FuCW and change S.Statistical change detection with momets under Time-varying illumination.IEEE Transaction on Image Processing 1998,(7)9:1258-1268.
[25] Costantini R.Counter illumination variations in a video surveillance environment, Electronic Imaging Conference,San Jose,USA.Proc.of SPIE,2001.
[26] Miller L,Nualchawee k,Tom C.Analysis of the Dynamics of-Shifting Cultivation in the Tropical Forests of Northern Thailand Using Landscape Modeling and Class frication of Landsat Imager[R].Greenbel,Maryland,U.S.A.:NASA Technical Memorandum ,Goddard Space Flight Centre,1978.
[27]李月臣,杨华,刘春霞.土地覆盖变化遥感检测方法[J].水土保持研究.2006,2(1):210-213.
[28]党安荣,王晓栋,陈晓峰.遥感图像处理方法[M].北京:清华大学出版社,2004.
[29]冯春,郭建宁,闵祥军.土地利用/土地覆盖遥感变化检测方法新进展[J].遥感信息.2006,3:81 84.
[30]吴芳,刘荣,田维春等.遥感变化检测技术及其应用综述[J].地理空间信息.2007(5).
[31]冯春,郭建宁,李杏朝等.土地利用/覆盖变化检测方法新进展[J]遥感信息,2006(3).
[32] J.Morisette,S.Khorram,and T.Mace.Land-cover change detection enhanced with generalized linear model[J].Int.J.Remote Sensing.1999(20):2703-2721.
[33] Macleod R.D.A quantitative comparison of change detection algorithms for monitoring eelgrass from remotely sensed data[J].PE & RS.1998,64(3): 207~216.
[34]新疆统计年年鉴[M].中国统计出版社.1999-2007.
[35]鄯善总体规划设计书.鄯善县国土资源局.2005.
[36]马蔼乃等.遥感信息模型[M].北京:北京大学出版社,1997.13～21.
[37]戴昌达,胡得永.TM数据的信息特征[J].遥感信息,1987(2):5-8.
[38]戴昌达,雷莉萍.TM图像的光谱信息特征与最佳波段组合[J].环境遥感.1989,4(4):282-292.
[39]Towsherd Y.R.et al.Preliminary analysis of Landsat-4 Thermatic Mapperproducts[J].International journal of remote sensing.1983,(4):817～823.
[40]Charvez P.Set. A Statistic method for selecting Landsat MSS ratio [J].Journal applied. photographic engineering.1982,8(1):23～30.
[41]Pat S.Chavez, Jr Digital processing techniques for image mapping withLandsat TM and SPOT simulator data[C].Eighteenth international symposiumon remote sensing of enviorment.Paris,France,1984.
[43]陈德超.TM与SPOT影像融合算法比较研究[J].遥感技术与应用.2001,16(2):110-115.
[44]詹才保.基于GIS技术的大城市边缘区土地利用变化及驱动力研究[R].中国科学院地理科学与资源研究所硕士研究报告,2001,6.
[45]王建.图像融合在引大灌区土地覆盖调查中的应用[J].遥感技术与应用.2001,16(3):173-177.
[46]王萍,张继贤,林宗坚,李春霞.基于多源遥感数据融合的土地利用/土地覆盖变化信息提取试验[J].测绘通报.2003.4:14～17.
[47]周前祥,敬忠良,姜世忠.不同光谱与空间分辨率遥感图像融合方法的理论研究[J].遥感技术与应用.2003.18(1):41～46.
[49]肖桂荣.基于遥感与GIS的县级土地利用动态监测与更新研究——以长乐市为例[D].福州大学硕士研究生论文,2002.12.
[50]冉有华,李文君,陈贤章.TM图像土地利用分类精度验证与评估——以定西县为例[J].遥感技术与应用.2003,18(2):81-86.
[51]陈本清.利用多时相卫星遥感影像对厦门市城市化进程及环境变化进行动态监测与分析[D].福州大学硕士研究生毕业论文,2002.3.
[52]赵英时.遥感应用分析原理与方法[M].科学出版社,2003.6.
[53]郭笃发.利用马尔科夫过程预测黄河三角洲新生湿地土地利用/覆被格局的变化[M].土壤38(1):42-47.
[54]李大平,丁建丽,何祺胜.基于马氏链首达时间的干旱区LUCC过程研究[J].国土资源科技馆理.2006,05
[55]张滢,丁建丽.绿洲土地利用变化未来趋势预测及其调控研究[J].干旱区资源与环境.2006,11(6).
[56]塔西甫拉提·特依拜,赵睿,丁建丽等.干旱区绿洲LUCC马尔可夫过程分析—以新疆和田绿洲为例[J].干旱区地理,2006,8(4).
[57]李东,苏小红等.基于新灰色马尔科夫模型的股价预测方法[J].哈尔滨工业大学学报.2003,35(2):244-249.
[58]高玉进.干旱区土地利用与土地覆盖变化对绿洲稳定性的影响研究[D].新疆大学硕士学位论文,2004.
[59]颜亮.基于RS和地学信息图谱的石河子市土地利用/覆被变化研究及预测分析[D].新疆大学硕士学位论文,2008.
[60]丁建丽,张滢,塔西甫拉提·特依拜.绿洲—荒漠交错带土地利用/覆盖时空变化研究[J].环境科学研究,2006,19(6).
[61]张雷.矿产资源开发与国家工业化[M].北京:商务印书馆,2004 [ ZHANG Lei: Mineral Resources Exploitation and National Industrialization[M] ] . Beijing : The Commercial /rests,2004(1).
[62]吴传钧.人地关系与经济布局(吴传钧文集)[M].北京:学苑出版社,2008.
[63]李进笃.自然能模型——人与自然和谐的数理证译[J].济南大学学报,2004,(2).
[64] Munasinghe M and Mcmeely J, Key Concepts and Terminology of Sustainable development[M].Defin- ing and Measuring Sustainability,The Bio-geophysical Foundation, New York,1996.
[65]张雷.中国区域发展的资源环境基础[M].北京:科学出版社,2006.