扬州市城市绿地系统的遥感监测分析
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摘要
随着我国城市化进程的不断加快,城市所在区域的土地利用/土地覆盖发生了快速的变化。城市绿地是城市生态系统中的一个子系统,是城市建设的主要自然因素,城市绿地的监测和调控成为城市规划的一项重要课题。
将遥感技术应用到绿地系统提取中,可以动态掌握绿地覆盖面积,从而优化绿地空间结构、提高城市的可持续发展潜能。
本研究在收集、总结国内外同类研究成果的基础上,以正在高速发展的扬州市城区为例,利用不同时相的TM数据、CBERS-02的CCD数据和中国资源卫星二号星的全色数据,选用合适的方法对城市主要地物信息进行自动(半自动)提取,以对扬州市城区绿地系统的变化进行动态监测及分析。
1.在对遥感影像进行几何校正、裁减、增强和融合处理的基础上,研究了城市主要地物信息快速准确提取的原理和方法。利用多时相、多植被指数法提取城市绿地信息,利用非监督分类法提取城市建筑物信息,利用决策树分类法提取城市水体信息,利用多重滤波处理对线性地物提取方面的优势提取道路信息,然后跟踪分析扬州市不同绿地载体类型的动态变化和现状。结果显示:(1)扬州市城市化发展迅速,2002-2007年间城区建筑物面积年增长率为11.31%,比1989-2002年的年增长率增加了8.67个百分点; (2)扬州市2006年建成区绿地率为37.0%,远远超过国家园林城市32%的标准,比2003年增加了2.7%,年增长率为0.9%; (3)扬州市水域面积1989年占全市总面积的16.2%、2002年占全市总面积的13.9%,2002年比1989年减少了2.3%;(4)扬州市道路面积在1989年-2003年间增长了近3倍;
2.利用统计数据验证扬州市公共绿地、公园绿地、水网特色景观带、居民区绿地、城市道路绿地的现状和变化,分析扬州市如何发挥自身优势开展城市绿化建设、有效保护传统文化遗产、创建具有地方特色的国家园林城市。扬州市统计局数据显示,2006年底扬州城区绿地面积达2625.26ha、绿地率达37.5%,人均公用绿地面积达10.4m2。针对城市化发展迅速这一现状,扬州市积极推行立体绿化和屋顶绿化,在城市有限的土地内拓宽绿化空间:傍河植绿,建成数十万平方米的滨河园林绿带;依路植绿,主要交通要道道路两侧设置15-45m宽的绿化带,绿地率均达到40%以上。
With the faster development of urbanization,prodigious changes has occurred to land use/coverge in the city whereabouts.City greenland is a subsysterm of city ecosysterm,which is main nature element of city, the survey and control of city’s greenland become an important task of city planning.
Put the RS technology into the extraction of city greenbelt systerm,it can master greenland coverage area dynamicly,optimize greenland space configuration,heighten sustainable development potential of city.
Study area lies in YangZhou city which developing quickly now.On the basis of collecting and summarizing literatures,the RS data I used is some different times Landsat TM data、CCD data of CBERS-02 and high resolution data of CERS-02, Firstly,take the information extraction of land use types of the city by the use of appropriate methods,and then,monitoring and analysis the change of greenland systerm in YangZhou.
1. On the basis of geometry registration ,enhancement and subset for images,the paper studies the information extraction mechanism and approach on mostly object of the city.Extract city greenland information by the use of multitemporal and multi-vegetation index,Extract city building information by the use of unsupvised classification,Extract city water information by the use of decision tree classification, reveal the road information take the advantage of multi-filtering on linear object extraction,and then tracked and Analyze the dynamic change and status quo of different types of greenland in yangzhou.Study found:(1)The urbanization of YangZhou is fast,annual growth rate of building was 11.31% from 2002 to 2007,there was 8.67% more than which of 1989-2002;(2)The city greenland rate was 37.0% in 2006,it beyonded the standard of nation garden city (32.0%) much more,there was 2.7% more than which of 2003,the annual growth rate was 0.9%;(3)The proportion of water area in the whole area was 16.2% in 1989、13.9% in 2002,there was 2.3% less than 1989;(4)There had 3 times increase in road area during 1989 to 2003.
2. Using survey data validate the status in quo and change of commonality greenland、park greenland、water net characteristic sight belt、residential greenland、roadway greenland in YangZhou.Analyse YangZhou how to use self-advantage to develop it’s greenland building、protect it’s traditional civilization heritage in effect,establish nation garden city with district characteristic.The data of statistic bureau indicate that: The area of greenland was 2625.26ha、greenland rate was 37.5%,communal greenlan area per capita was 10.4 m2 .Aiming at the status in qua of faster urbanization , YangZhou put solid virescence and roof virescence in practice actively,develop virescence room in limited ground; YangZhou made virescence close the river, built hundreds of thousands of shore gardens greenbelts; YangZhou made virescence close the road,both sides of central roads lay 15-45meters greenbelt,the greenland rate all beyond 40%;
将遥感技术应用到绿地系统提取中,可以动态掌握绿地覆盖面积,从而优化绿地空间结构、提高城市的可持续发展潜能。
本研究在收集、总结国内外同类研究成果的基础上,以正在高速发展的扬州市城区为例,利用不同时相的TM数据、CBERS-02的CCD数据和中国资源卫星二号星的全色数据,选用合适的方法对城市主要地物信息进行自动(半自动)提取,以对扬州市城区绿地系统的变化进行动态监测及分析。
1.在对遥感影像进行几何校正、裁减、增强和融合处理的基础上,研究了城市主要地物信息快速准确提取的原理和方法。利用多时相、多植被指数法提取城市绿地信息,利用非监督分类法提取城市建筑物信息,利用决策树分类法提取城市水体信息,利用多重滤波处理对线性地物提取方面的优势提取道路信息,然后跟踪分析扬州市不同绿地载体类型的动态变化和现状。结果显示:(1)扬州市城市化发展迅速,2002-2007年间城区建筑物面积年增长率为11.31%,比1989-2002年的年增长率增加了8.67个百分点; (2)扬州市2006年建成区绿地率为37.0%,远远超过国家园林城市32%的标准,比2003年增加了2.7%,年增长率为0.9%; (3)扬州市水域面积1989年占全市总面积的16.2%、2002年占全市总面积的13.9%,2002年比1989年减少了2.3%;(4)扬州市道路面积在1989年-2003年间增长了近3倍;
2.利用统计数据验证扬州市公共绿地、公园绿地、水网特色景观带、居民区绿地、城市道路绿地的现状和变化,分析扬州市如何发挥自身优势开展城市绿化建设、有效保护传统文化遗产、创建具有地方特色的国家园林城市。扬州市统计局数据显示,2006年底扬州城区绿地面积达2625.26ha、绿地率达37.5%,人均公用绿地面积达10.4m2。针对城市化发展迅速这一现状,扬州市积极推行立体绿化和屋顶绿化,在城市有限的土地内拓宽绿化空间:傍河植绿,建成数十万平方米的滨河园林绿带;依路植绿,主要交通要道道路两侧设置15-45m宽的绿化带,绿地率均达到40%以上。
With the faster development of urbanization,prodigious changes has occurred to land use/coverge in the city whereabouts.City greenland is a subsysterm of city ecosysterm,which is main nature element of city, the survey and control of city’s greenland become an important task of city planning.
Put the RS technology into the extraction of city greenbelt systerm,it can master greenland coverage area dynamicly,optimize greenland space configuration,heighten sustainable development potential of city.
Study area lies in YangZhou city which developing quickly now.On the basis of collecting and summarizing literatures,the RS data I used is some different times Landsat TM data、CCD data of CBERS-02 and high resolution data of CERS-02, Firstly,take the information extraction of land use types of the city by the use of appropriate methods,and then,monitoring and analysis the change of greenland systerm in YangZhou.
1. On the basis of geometry registration ,enhancement and subset for images,the paper studies the information extraction mechanism and approach on mostly object of the city.Extract city greenland information by the use of multitemporal and multi-vegetation index,Extract city building information by the use of unsupvised classification,Extract city water information by the use of decision tree classification, reveal the road information take the advantage of multi-filtering on linear object extraction,and then tracked and Analyze the dynamic change and status quo of different types of greenland in yangzhou.Study found:(1)The urbanization of YangZhou is fast,annual growth rate of building was 11.31% from 2002 to 2007,there was 8.67% more than which of 1989-2002;(2)The city greenland rate was 37.0% in 2006,it beyonded the standard of nation garden city (32.0%) much more,there was 2.7% more than which of 2003,the annual growth rate was 0.9%;(3)The proportion of water area in the whole area was 16.2% in 1989、13.9% in 2002,there was 2.3% less than 1989;(4)There had 3 times increase in road area during 1989 to 2003.
2. Using survey data validate the status in quo and change of commonality greenland、park greenland、water net characteristic sight belt、residential greenland、roadway greenland in YangZhou.Analyse YangZhou how to use self-advantage to develop it’s greenland building、protect it’s traditional civilization heritage in effect,establish nation garden city with district characteristic.The data of statistic bureau indicate that: The area of greenland was 2625.26ha、greenland rate was 37.5%,communal greenlan area per capita was 10.4 m2 .Aiming at the status in qua of faster urbanization , YangZhou put solid virescence and roof virescence in practice actively,develop virescence room in limited ground; YangZhou made virescence close the river, built hundreds of thousands of shore gardens greenbelts; YangZhou made virescence close the road,both sides of central roads lay 15-45meters greenbelt,the greenland rate all beyond 40%;
引文
【1】李敏.现代城市绿地系统规划[M]北京:中国建筑工业出版社,2002.
【2】王浩.城市生态园林绿地系统规划[M].北京:中国林业出版社,2003.
【3】林业部环境保护工作,www.sdinfo.net.cn/hjinfo/hjinfol bmhy/bmhy9-7/林业部环境保护工作.html .
【4】赵英时等.遥感应用分析原理与方法[M].北京:科学出版社,2003.
【5】彭望琭,余先川,周涛等译.数字图像处理[M],北京:电子工业出版社,2003.
【6】戴昌达,姜小光,唐伶俐等.遥感图像应用处理与分析[M],清华大学出版社,2004.
【7】黎夏,叶嘉安.利用遥感监测和分析珠江三角洲的城市扩展过程-以东莞市为例[J].地理研究,1997.12.16(4):56~61.
【8】吴秋华.城市扩展的航天遥感初步动态监测实验研究[M].北京:中科院遥感应用研究所,1991.10.
【9】江涛,张传霞.城市扩展动态变化的遥感研究[J].遥感信息,1999,4:50~53.
【10】汪小钦,徐涵秋,陈崇成.福清市城市时空扩展的遥感监测及其动力机制.福州大学学报(自然科学版) [J],2000,vol.28(2):111~115.
【11】T.W.Owen,T.N.Carlson and R.T.Gillies.Assessment of satellite remotely-sensed land Cover parameters in quantitatively describing the climate effect of urbanization[J].International Journal of Remote sensing,1998,vol.19(9):1663~1681.
【12】Kondoh A,Nishiyama J.Changes in hydrological cycle due to urbanization in the suburb of Toky Metropolitan Area,Japan[J].Remote Sensing for Land Surface Characterization, Editors:Gupta RK.Advances inpaceresearch,2000,vol.26(7):1173~1176.
【13】Khan NI.The effects of urbanization on urban storm water runoff:A case study on greater Dhaka metropolitan city.Operational Remote Sensing for Sustainable Development[J], Editors: Nieuwenhuis GJA, Vaughan RA, Molenear M,1999:285~294.
【14】Mark L.Imhoff etal.The Use of Multisource Satellite and Geo-spatial Data to Study the Effect of Urbanisation on Primary Productivity in the United States[J].IEEETransactions on Geoscience and Remote Sensing,2000,vol.38(6):2549~2556.
【15】赵元洪,田粮虎,何侃.利用多平台遥感数据复合研究城市扩展的动态监测[J].环境遥感,1992.8,vol.7(3):196-200.
【16】J.G.Masek, F.ELindsay and S.N.Goward.Dynamics of urban growth in the Washington DC metropolitan area,1973-1996,fromlandsat observation[J].International Journal of Remotesensing,2000,vol.21(18):3473~3486.
【17】陈述彭.地球信息科学[M],科学出版社,地学的探索,第六卷, 2003:150~152.
【18】李树楷.全球环境、资源遥感分析[M],测绘出版社. 1992.
【19】阎守琶.国家空间信息基础设施建设的理论与方法[M],海洋出版社. 2003.
【20】林宗坚.摄影测量与遥感当前发展中面临的图像图形学问题[J],科学技术与工程.2002,1:23~25.
【21】李德仁,李清泉.地球空间信息学与数字地球[J],电子科技导报. 1999,5:33～36.
【22】Core A, The Digital EarCh: Understanding Our Planet in the 21st Century. 1998.
【23】李树楷,新型空间信息集成型技术, http://www.digitalearth.net.cn/readingroom/specialityarticlellskw.htm.
【24】徐冠华,“遥感应用与地理信息系统”,走向21世纪的中国地球科学调研组:《走向21世纪的中国地球科学》[M],河南科学出版社. 1995.
【25】QuickBird遥感数据在土地整理工作中的应用,国土资源遥感.2007,4:74~75.
【26】遥感技术的发展现状和趋势,http://www.chinadci.com/gb/szcs/3s/rs develop.htm.
【27】David J. Coven and John R. Jensen, Extraction and Modeling of Urban Attributes Using Remote Sensing Technology, "People and Pixels: Linking Remote Sensing and Social Science", National research Council, National Academy Press, 1998.164~188.
【28】Jensen, J. R., Introductory Digital Image Processing: A remote sensing perspective,2nd Edition. NJ: Prentice-Hall. 1996.
【29】梅安新,彭望碌,秦其明等.遥感导论[M],高等教育出版社. 2001.
【30】李伯衡.国土信息系统与国土利用制图[M],中国大地出版社. 2003.
【31】杨晓梅.遥感影像的地学理解与分析,[博士论文],中国科学院地理所. 1999.
【32】陈述彭.遥感大辞典[M],科学出版社. 1990.
【33】周成虎,骆剑承等.遥感影像地学理解与分析[M],北京:科学出版社. 1999.
【34】(日)遥感研究会,刘勇卫译.遥感精解[M],测绘出版社. 1993.
【35】淮静娟主编.遥感图像目视判读的原理与方法[M],北京:中国科学技术出版社. 1999.
【36】余旭初,刘智.遥感图像面状目标识别的智能可视化模型[J],解放军测绘学院学报, 1996,Vo1.13(3), 209~214.
【37】王世新,魏成阶,刘亚岚等.气象卫星洪涝灾害监测与评估系统,'98遥感进展”论文集,大连:环境遥感分会年会论文集. 1998.
【38】王世新,魏成阶,阎守琶等. 98全国洪涝灾害遥感监测评估的主要成果一基于网络的洪涝灾情遥感速报系统的应用,自然灾害学报[J], 2000,Vo1.9 ( 2 ),5～16.
【39】魏成阶,刘亚岚,王世新等.台湾南投“9.21”地震灾害卫星遥感监测评估,《遥感在中国》[M],地震出版社, 2000,124~128.
【40】王杰生.遥感图像应用处理中的一个分类新算法一模拟目视分辨法[J],环境遥感, 1992,Vol.7 (2):125~130.
【41】刘亚岚,阎守邑,王涛,肖春生.遥感图像分区自动分类方法研究[J],遥感学报, 2002,Vo1.6 (5):357~363.
【42】马祖陆,茹锦文,刘光慧,遥感图像屏幕判读识别法在贵州岩溶山区土地调查种的应用[J],中国岩溶1995,Vo1.14 (3), 217~222.
【43】余旭初.遥感影像分析中的智能与可视化技术的联合研究, [博士论文],中国人民解放军测绘学院. 1997.
【44】刘纪远.中国资源环境遥感宏观调查与动态研究[M],中国科学技术出版社. 1996.
【45】林业部环境保护工作,www.sdinfo.net.cn/hjinfo/hjinfol bmhy/bmhy9-7/林业部环境保护工作.html .
【46】数字城市,http://www.sinowatch. com/07/default.htm .
【47】郭树桂.卫星遥感与制图[M],中国人民解放军测绘学院. 1984.
【48】Trolier, L.J. and W.R. Philipson. Visual analysis of Landsat Thematic Mapper images for hydrologic land use cover[J]. Photogrammetry Engineering. and RemoteSensing. 1986, vol.52(9):1531~1538.
【49】傅肃性.遥感专题分析与地学图谱[M],北京:科学出版社. 2002.
【50】李小文,高峰,王锦地,朱启僵.遥感反演中参数的不确定性与敏感性分析[J],遥感学报, 1997,Vol. 1(1) 5~14 .
【51】刘贵忠,邸双亮.小波分析及其应用[M],西安:西安电子科技大学出版社. 1992.
【52】催新春,裘季冰,张文龙.基于小波变换和数学形态学的人造景物提取[J],上海师范大学学报(自然科学版), 2002,Vo1.31(1), 42~46.
【53】陶洪久,柳健,田金文.基于小波变换和数学形态学的遥感图像边缘检测,红外与激光工程. 2002,vol.31(2),152~157.
【54】Multi-level Thresholding: Fuzzy Maximum Entropy Criterion Using ICM Proceedings of The First International Conference on Image And Graphics[J] ,Tianjin,China, 2000,Vo1.5, 293~298,
【55】Wang F., Improving Remote Sensing Image Analysis through Fuzzy Information Representation[J], PE&RS, 1990,Vol. 56(8), 1163~1169.
【56】孙丹峰,汲长远,林培.自组织网络与模糊规则结合在遥感土地覆盖分类中应用研究,中国土地科学. 1999,vol.12(5),42~44.
【57】骆剑承,周成虎,杨艳.具有部分监督的遥感影像模糊聚类方法研究及应用[J],遥感技术与应用, 1999,Vol. 14(4), 37~43.
【58】曹燕,宁书年,王四龙,刘玉荣.分形分维在遥感图像纹理分析中的应用[J],遥感技术与应用, 1997,Vo1. 12(4), 31~35 .
【59】Priebe, C. E,Solka, J. L., and Rogers, G. W. (1993), "Discriminant analysis in aerial images using fractal based features," Adaptive and Learning Systems, F. A. Sadjadi, Ed.,proc. SPIE 1962, 196~208.
【60】D.L.Civco. Artificial Neural Networks for land-cover Classification and Mapping[J],International Journal of Geographical Information System, 1993,Vol. 7(2), 173~186.
【61】Development of Improved Image Classification Algorithms to Extract Quantitative Urban/Suburban Landuse/Land Cover Information from High Spatial Resolution DigitalImagery, NASA Affiliate Research Center, 1998.
【62】H.Murai and S.Omatu. Remote Sensing Image Analysis Using a Neural Network and Knowledge-Based Processing[J], Int. J. Remote Sensing, 1997,vol.18(4): 811~828.
【63】李厚强,王宜主,刘政凯.一种适用于多类别遥感图像分类的新方法一符合神经网络分类方法[J],遥感学报, 1997,1, 257~261.
【64】庄镇泉,章劲松,神经网络与智能信息处理,http://www.ahetc.gov.cn/cid199910/07.htm.
【65】莫源富,周立新.分区分类法一针对山区遥感图像的一种全新的分类方法,中国岩溶,2000,vol.19(4),360～365.
【66】师庆东,吕光辉,潘晓玲.在NOAA遥感影像中根据植被区域特点分区分类及应用, http://www.xjb.ac.cnlxjlhs/kexie/articles/environment/environment42.htm.
【67】刘亚岚,阎守邑,王涛,肖春生.遥感图像分区自动分类方法研究[J],遥感学报, 2002,Vo1.6 (5), 327~363.
【68】Running SW, L.TR, etc. A remote sensing based vegetation classification logic for global land cover analysis[J],Remote Sensing of Environment, 1995, 51, 39~48.
【69】Apisit Eiumnoh, Rajendra P. Shrestha, Can DEM Enhance The Digital Image Classification. 1997.http://www.gisdevelopment.nebaars/acrsl/ts9/ts9007.shtml.
【70】吴炳方,黄绚,田志刚.应用遥感及地理信息系统进行植被制图[J],环境遥感, 1995,Vo1.10(1), 30~36.
【71】Apisit Eiumnoh, Rajendra P. Shrestha, Can DEM Enhance The Digital Image Classification. 1997. http://www.gisdevelopment.nebaars/acrsl/ts9/ts9007.shtml.
【72】吴信才,地理信息系统的基本技术与发展动态,http://159.226.117.32/body/article/gis- move.htm.
【73】余旭初,方勇, RS和GIS集成环境下的遥感图像分析技术[J],解放军测绘学报, 1997 ,Vo1.14(3), 176~181.
【74】P.V. Narasimha Rao, K.D. Reddy, T.S. Kumar, B.R.M.Rao, Mufti-resolution Segmentation and Classification of Remote Sensing Data[J], IAPRA &SIS, 2002 ,Vo1.34(7),150~154, "Resource and Environmental Monitoring", Hyderabad, India.
【75】党安荣王晓栋陈晓峰张建宝,ERDAS IMAGINE遥感图像处理方法[M],北京,清华大学出版社.2003.4
【76】刘俊平,黄华.城市绿地景观格局及其生态建设对策的探讨[J].内蒙古科技与经济.2000,vol.4:9~11.
【77】C.Y Jim a, Sophia S. Chen Comprehensive greenspace planning based on landscape ecology principles in compact Nanjing city, China. Landscape and Urban Planning . 2003,65:95~116.
【78】曹勇宏.城市绿地系统建设的生态对策以长春市为例[J].城市环境与城市生态. 2001,vol.14(5): 9~10.
【79】李锋,王如松.城市绿地系统的生态服务功能评价、规划与预测研究——以扬州市为例[J].生态学报.2003,vol.23(9):1929～1936.
【80】杨士弘.城市绿化树木碳氧平衡效应研究[J].城市环境与城市生态.1996,vol.9(1):37～39.
【81】周志翔,邵天一等.城市绿地空间格局及其环境效应——以宜昌市中心城区为例[J].生态学报.2004,vol.24(2):186～192.
【82】Graetz R D, Pech R R, Davis A W. The assessment and monitoring of sparsely vegetated rangelands using calibrated Landsat data[J]. International Journal of Remote Sensing,1988, vol.9(7):1 201~1 222.
【83】Peter R.J. North Estimation of AR, LAI, and vegetation fractional cover from ATSR-2 imagery[J].Remote Sensing of Environment, 2002, vol.80(1):114~121.
【84】Bannari A, Morin D, Bonn F. A review of vegetation indices[J]. Remote Sensing Reviews, 1995,13:.95~120.
【85】Baret E Guyot G. Potentials and limits of vegetation indices for LAI and APAR assessment[J]. Remote Sensing of Environment, 1991,vol.35 (2): 161~173.
【86】Duncan Stow D. Franklin Hope A. Assessing the relationship between spectral vegetation indices and shrub cover in the Jornada Basin New Mexico[J]. International Journal of Remote Sensing 1993,vol.14(18 ): 3395~3416.
【87】陈述彭,童庆禧,郭华东等.遥感信息机理研究[M].北京,科学出版社,1998: 139.
【88】胡良军,邵明安.论水土流失研究中的植被覆盖度量指标[J].西北林学院学报,2001, vol.16 (1):40~43.
【89】Anderson G L, Hanson J D, Haas R H. Evaluating landsat thematic mapper derived vegetation indices for estimating above-ground biomass on semiarid rangelands[J]. Remote Sensing of Environment 1993,vol.45 (2): 165~175.
【90】Muneni R B, Nemani Running S W Estimation of global leaf area index and absorbed parusing radiative transfer models[J]. IEEE Transactions on Geoscience and Remote Sensing. 1997,35:1 380~1 393.
【91】Myneni R B, Hall F q Sellers P S, Marshak A L. The interpretation of spectral vegetation indexes[J].IEEE Transactions on Geoscience and Remote Sensing,1995, 33:481~486.
【92】Myneni R B", Keeling C D, Tucker C J, Asrar Cz, Nemani R R. Increased plant growth in the northern high latitudes from 1981 to 1991[J]. Nature,1997, 386: 698~702.
【93】Bradley C Rundquist. The influence of canopy green vegetation fraction on spectral measurements over native tallgrass prairie[J]. Remote Sensing of Environment,2002. vol.81(1):129~135.
【94】Kaufman Y J.The Atmospheric Effect on Remote Sensing and Its Correction[A].Theory and Applications of Optical Remote Sensing[C], New York:Wiley. 1989, 336~428.
【95】Dymond J R, Shepherd J D, Qi J. A simple physical model of vegetation reflectance for standardizing optical satellite imagery[J]. Remote Sensing of Environment, 2001,vol.77 (2): 230~239.
【96】方红亮,田庆久.高光谱遥感在植被监测中的研究综述[J].遥感技术与应用,1998 ,vol.13 (1):62~69.
【97】Toby N, Carlson, David A Ripley. On the Relation between NDVI Fractional Vegetation Cover and Leaf Area Index[J]. Remote Sensing of Environment,1997, 62: 241~252.
【98】Dymond J R, Stephens P R, Newsome P F et al. Percent vegetation cover of a degrading Range land from SPOT[J]. International Journal of Remote Sensing, 1992 ,vol.13(11):1999~2007.
【99】Wittich K P, Hansing O. Area-averaged vegetative cover fraction estimated from satellite data[J]. International Journal of Biometerology, 1995, vol.38 (3):209-215.
【100】Purevdor J T S, Tateishi Ishiyama T, et al. Relationships between percent vegetation cover and vegetation indices[J]. International Journal of Remote Sensing, 1998, vol.19(18): 3 519~3 535.
【101】Leprieur C. Kerr Y H. Mastorchio S. et al. Monitoring vegetation cover across semi-arid regions:Comparison of remote observations from various scales[J]. International Journal of Remote Sensing, 2000,vol.21 (2): 281~300.
【102】Bradley C Rundquist. The influence of canopy green vegetation fraction on spectral measurements over native tallgrass prairie[J]. Remote Sensing of Environment,2002. vol.81(1):129~135.
【103】Qi J, Marsett R C, Moran M. S., Goodrich D. C, P. Heilman, Y. H. Kerr, G. Dedieu, A. Chehbouni and X. X. Zhang. Spatial and temporal dynamics of vegetation in the San Pedro River basin area[J].Agricultural and Forest Meteorology,2000,(105 ): 55~68.
【104】Zeng XuBin, Robert E, Dickinson Alison Walker, et al. Derivation and evaluation of global 1-km fractional vegetation cover data for land modeling[J]. Journal of Applied Meterology,2000,vol.39 (6):826~839.
【105】罗修岳,郑柯.脆弱生态环境植被指数和植被盖度数字图像的编制及其应用研究—以晋陕蒙地区为例.晋陕蒙接壤地区脆弱生态系统遥感监测与管理研究[M].北京:宇航出版1994,24~35.
【106】Goward S N, Haemmrich K F, blaring R H. Visible-near infrared spectral reflectance of landscape components in western Oregon[J]. Remote Sensing ofEnvironment, 1994, vol.47 (2):190~203.
【107】文贡坚,王润生.从航空遥感图像中自动提取主要道路[J].软件学报,2000,(11):17~20.
【108】Leprieur C, Kerr Y H, Pichon 3 M. Critical assessment of vegetation indices from AVHRR in asemi-arid environment[J]. International Journal of Remote Sensing, 1996,(17): 2 549~2 563.
【109】Leprieur C, Verstraete M M, Pinty B. Evaluation of the performance of various vegetation indices to retrieve vegetation cover from AVHRR data[J]. Remote Sensing Review, 1994,(10 ): 265~284.
【110】Qi J, Chenbouni A, Huete A R, et al. Modified soil adjusted vegetation index (MSAVI) [J]. Remote sensing of environment, 1994, vol.48 (2): 119~126.
【111】Kanemasu E T, Demetriades-Shah T H, Su H, Lang A R G. Estimating grassland biomass using remotely sensed data[J]. Applications of remote sensing in agriculture, Cambridge, Cambridge University Press, Clark M D S(Ed.), 1990, 185~199.
【112】Li Y, Demetriades-Shah T H, Kanemasu E T, Shultis J K, Kirkham M B. Use of second derivatives of canopy reflectance for monitoring prairie vegetation over different soil backgrounds[J].Remote Sensing of Environment,1993,vol.44(1):81~87.
【113】Major D J, Baret F, Guyot G.. A ratio vegetation index adjusted for soil brightness[J]. International Journal of Remote Sensing, 1990,(11):720~727.
【114】Clevers J G P W. The application of a vegetation index in correcting the infrared reflectance for soil background[J]. Proceedings of Symposium on Remote Sensing for Resources Development and Environmental Management, Enschede, 1986, 25-29.
【115】Huete A RJackson R D, Post, D F. Spectral response of plant canopy with different soil background[J]. Remote Sensing of Enivronment. 1985,vol.17(1):37~53.
【116】Qi J, Kerr Y., Chehbouni, A. External factor consideration in vegetation index development[J]. In:6th International Symposium on Physical Measurements and Signatures in Remote Sensing, Vald'Isere, France, January 17-21, 1994(Toulouse, France: CNES), 723~730.
【117】Anatoly A Gitelson, Yoram J Kaufman, Robert Stark, Don Rundquist. Novel algorithms for remote estimation of vegetation fraction[J]. Remote Sensing of Environment 2002,vol.80(1):76~87.
【118】Fernandez S, Vidal D, Simon E, Sole-Sugranes L. Radiometric characteristics of triticum aestivum cv. astral under water and nitrogen stress[J]. International Journal of Remote Sensing 1994,(15):1867~1884.
【119】Gitelson A, Merzlyak M.. Remote estimation of chlorophyll content in higher plant leaves[J].International Journal of Remote Sensing, 1997,(18 ): 291~298.
【120】Pinty B,Verstraete M M. GEMI: A non-linear index to monitor global vegetation from satellites[J].Vegetatio, 1992,101:15~20.
【121】Carlson T N, Ripley D A. On the relation between NDVI, fractional vegetation cover, and leaf area index[J]. Remote Sensing of Environment,1997 ,vol.62 ( 3):241~252.
【122】Liu Q, Huete A. A feedback based modification of the NDVI to minimize canopy background and atmospheric noise. IEEE Transactions on Geoscience and Remote Sensing, 1995, ( 33):457~465.
【123】Gillies R R, Kustas W P, Humes K S. A verification of the `triangle' method for obtaining surface soil water content and energy fluxes from remote measurements of the Normalized difference vegetation Index(NDVI) and surface [J]. International Journal of Remote Sensing, 1997,(18):3145~3166.
【124】Gitelson A, Kogan F, Zakarin E, Spivak L, Lebed L. Using AVHRR data for quantitive estimation of vegetation conditions: calibration and validation[J]. Advances in Space Research 1998 ,( 22):673~676.
【125】McDaniel K C, Haas R H. Assessing mesquite-grass vegetation condition from Landsat[J]. Photogrammetric Engineering and Remote Sensing,1982,( 48):441~450.
【126】Pickup G., Chewings V H, Nelson D J. Estimating changes in vegetation cover over time in arid rangelands using Landsat MSS data[J]. Remote Sensing of Environment, 1993 , vol.43 ( 3):243~263.
【127】张云柏.ASAR影像应用于水稻识别和面积测算研究-以江苏宝应县为例[D].南京:南京农业大学农学院,2004.
【128】Hansen, M. Dubayah, R. and DeFries.R. Classification Trees: An Alternative to Traditional Land Cover Classifiers [J], International Journal of Remote Sensing, 1996,vol.17(5):1075~1082.
【129】Winlinson G G and Megier J.Evidential Reasoning in a Pixel Classification Hierarchy—A Potential Method for integrating lmage Classifiers and Expect Systerm Rules Based on Geographic Context[J] . International Journal of Remote sencing.1990,vol.11(10).1963～1968
【130】Kontoes C,Wilkinson G G,Burril1 A,Goffredo S and Megier J.An Experimental System for the Integration of GIS Data in Knowledge—based Analysis for Remote Sensing of Agriculture[J] . International Journal of Geographic Information System,1993,vol.7(3):247～262
【131】M.A.Friedl and C.E.Brodley.Decision Tree Classification of Land Cover from Remotely Sensed Data [J].Remote Sensing Environment, 1997,vol.61(3):399~409.
【132】Rick L.Lawrence and Andrea Wright. Rule-Based Classification Systems Using Classification and Regression Tree (CART) Analysis [J], PE&RS 2001,67(10):1137~1142.
【133】Yoshikawa Masanobu, Shindo Hisakazu and Nishii, Ryuei. Fully automated design of binary decision tree for land cover classification, Proceedings of the 1995 International Geoscience and Remote Sensing Symposium. Part 3 (of 3), 1995,Jul 10~14.
【134】Tadjudin Saldju and Landgrebe David A.(1996). Decision tree classifier design for high-dimensional data with limited training samples. Proceedings of the 1996 International Geoscience and Remote Sensing Symposium, IGARSS'96. Part 1 (of 4), 1996,May 28~31.
【135】Franklin S.E., Stenhouse, G.B., Hansen, M.J., Popplewell, C.C., Dechka, J.A.and Peddle,D.R.(2001).An Integrated Decision Tree Approach (IDTA) to mapping landcover using satellite remote sensing in support of grizzly bear habitat analysis in the Alberta yellow head ecosystem [J].Canadian Journal of Remote Sensing, 2001,27:579~592.
【136】De Colstoun, Story Michael H. and Thompson Craig. (2002). Vegetation mapping using multitemporal ETM+ data and a decision tree classifier. 2002 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2002), 2002, Jun 24~28 2890~2892.
【137】Simard Marc, Saatchi, Sasan S. and De Grandi, Gianfranco. (2000). Use of decision tree and multiscale texture for classification of JERS-1 SAR data over tropical forest [J]. IEEE Transactions on Geoscience and Remote Sensing, 2000, 38:2310~2321.
【138】Palaniappan, Zhu Feng, Zhuang Xinhua and Zhao, Yunxin (2000). Enhanced Binary Tree Genetic Algorithm for automatic land cover classification. 2000 International Geoscience and Remote Sensing Symposium (IGARSS 2000), 2000, Jul24~Jul 28, 2:688~692.
【139】Ding Qiang, Ding Qin and Perrizo (2002). Decision tree classification of spatial data streams using peano count trees. Applied Computing 2002: Proceeedings of the 2002 ACM Symposium on Applied Computing, 2002,Mar11-14 ,413~417.
【140】Pal Mahesh and Mather Paul M. (2002). A comparison of decision tree and backpropagation neural network classifiers for land use classification. 2002 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2002), 2002, Jun 24~28 ,503~505.
【141】Saglam, Ersoy Okan and Yazgan, Bingul (2003). Self organizing map and linear support vector machine decision tree with optimized class separability. Smart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Complex Systems and Artificia Life-Proceedings of the Artificial Neural Networks in Engineering Conference,Nov 2~5 2003, 13:193~198.
【142】周春平,尹连旺.遥感影象制图综合的智能化研究[J] .遥感学报,1998,2(1).72～77.
【143】Barzoha M R,Cooper D B.Automatic Finding of Main Road in Aerial Images by Using CJeometricstochastic Models and Estimation.IEEE CVPR.1993.
【144】Sylvain A.From Manual to Automatlc Stereo Plotting:Evaluation of Different Road Network Capture Processes.IAPRS XXXI Part t33,Viena,1996.
【145】Trinder C.Wang Yandong.Automatic Road Extraction from Aerial Images[J].Digital Signal Processing, 1998, 8 (4): 215～224.
【146】邵振峰,影像线状地物与房屋的自动提取:[博士论文].武汉:武汉大学,2001.
【147】Eaumgarmer A.Extraction of Roads from Aerial Imagery Based on Grouping and Local Context.ISPRS Comm.ⅢWorkshop,1998.
【2】王浩.城市生态园林绿地系统规划[M].北京:中国林业出版社,2003.
【3】林业部环境保护工作,www.sdinfo.net.cn/hjinfo/hjinfol bmhy/bmhy9-7/林业部环境保护工作.html .
【4】赵英时等.遥感应用分析原理与方法[M].北京:科学出版社,2003.
【5】彭望琭,余先川,周涛等译.数字图像处理[M],北京:电子工业出版社,2003.
【6】戴昌达,姜小光,唐伶俐等.遥感图像应用处理与分析[M],清华大学出版社,2004.
【7】黎夏,叶嘉安.利用遥感监测和分析珠江三角洲的城市扩展过程-以东莞市为例[J].地理研究,1997.12.16(4):56~61.
【8】吴秋华.城市扩展的航天遥感初步动态监测实验研究[M].北京:中科院遥感应用研究所,1991.10.
【9】江涛,张传霞.城市扩展动态变化的遥感研究[J].遥感信息,1999,4:50~53.
【10】汪小钦,徐涵秋,陈崇成.福清市城市时空扩展的遥感监测及其动力机制.福州大学学报(自然科学版) [J],2000,vol.28(2):111~115.
【11】T.W.Owen,T.N.Carlson and R.T.Gillies.Assessment of satellite remotely-sensed land Cover parameters in quantitatively describing the climate effect of urbanization[J].International Journal of Remote sensing,1998,vol.19(9):1663~1681.
【12】Kondoh A,Nishiyama J.Changes in hydrological cycle due to urbanization in the suburb of Toky Metropolitan Area,Japan[J].Remote Sensing for Land Surface Characterization, Editors:Gupta RK.Advances inpaceresearch,2000,vol.26(7):1173~1176.
【13】Khan NI.The effects of urbanization on urban storm water runoff:A case study on greater Dhaka metropolitan city.Operational Remote Sensing for Sustainable Development[J], Editors: Nieuwenhuis GJA, Vaughan RA, Molenear M,1999:285~294.
【14】Mark L.Imhoff etal.The Use of Multisource Satellite and Geo-spatial Data to Study the Effect of Urbanisation on Primary Productivity in the United States[J].IEEETransactions on Geoscience and Remote Sensing,2000,vol.38(6):2549~2556.
【15】赵元洪,田粮虎,何侃.利用多平台遥感数据复合研究城市扩展的动态监测[J].环境遥感,1992.8,vol.7(3):196-200.
【16】J.G.Masek, F.ELindsay and S.N.Goward.Dynamics of urban growth in the Washington DC metropolitan area,1973-1996,fromlandsat observation[J].International Journal of Remotesensing,2000,vol.21(18):3473~3486.
【17】陈述彭.地球信息科学[M],科学出版社,地学的探索,第六卷, 2003:150~152.
【18】李树楷.全球环境、资源遥感分析[M],测绘出版社. 1992.
【19】阎守琶.国家空间信息基础设施建设的理论与方法[M],海洋出版社. 2003.
【20】林宗坚.摄影测量与遥感当前发展中面临的图像图形学问题[J],科学技术与工程.2002,1:23~25.
【21】李德仁,李清泉.地球空间信息学与数字地球[J],电子科技导报. 1999,5:33～36.
【22】Core A, The Digital EarCh: Understanding Our Planet in the 21st Century. 1998.
【23】李树楷,新型空间信息集成型技术, http://www.digitalearth.net.cn/readingroom/specialityarticlellskw.htm.
【24】徐冠华,“遥感应用与地理信息系统”,走向21世纪的中国地球科学调研组:《走向21世纪的中国地球科学》[M],河南科学出版社. 1995.
【25】QuickBird遥感数据在土地整理工作中的应用,国土资源遥感.2007,4:74~75.
【26】遥感技术的发展现状和趋势,http://www.chinadci.com/gb/szcs/3s/rs develop.htm.
【27】David J. Coven and John R. Jensen, Extraction and Modeling of Urban Attributes Using Remote Sensing Technology, "People and Pixels: Linking Remote Sensing and Social Science", National research Council, National Academy Press, 1998.164~188.
【28】Jensen, J. R., Introductory Digital Image Processing: A remote sensing perspective,2nd Edition. NJ: Prentice-Hall. 1996.
【29】梅安新,彭望碌,秦其明等.遥感导论[M],高等教育出版社. 2001.
【30】李伯衡.国土信息系统与国土利用制图[M],中国大地出版社. 2003.
【31】杨晓梅.遥感影像的地学理解与分析,[博士论文],中国科学院地理所. 1999.
【32】陈述彭.遥感大辞典[M],科学出版社. 1990.
【33】周成虎,骆剑承等.遥感影像地学理解与分析[M],北京:科学出版社. 1999.
【34】(日)遥感研究会,刘勇卫译.遥感精解[M],测绘出版社. 1993.
【35】淮静娟主编.遥感图像目视判读的原理与方法[M],北京:中国科学技术出版社. 1999.
【36】余旭初,刘智.遥感图像面状目标识别的智能可视化模型[J],解放军测绘学院学报, 1996,Vo1.13(3), 209~214.
【37】王世新,魏成阶,刘亚岚等.气象卫星洪涝灾害监测与评估系统,'98遥感进展”论文集,大连:环境遥感分会年会论文集. 1998.
【38】王世新,魏成阶,阎守琶等. 98全国洪涝灾害遥感监测评估的主要成果一基于网络的洪涝灾情遥感速报系统的应用,自然灾害学报[J], 2000,Vo1.9 ( 2 ),5～16.
【39】魏成阶,刘亚岚,王世新等.台湾南投“9.21”地震灾害卫星遥感监测评估,《遥感在中国》[M],地震出版社, 2000,124~128.
【40】王杰生.遥感图像应用处理中的一个分类新算法一模拟目视分辨法[J],环境遥感, 1992,Vol.7 (2):125~130.
【41】刘亚岚,阎守邑,王涛,肖春生.遥感图像分区自动分类方法研究[J],遥感学报, 2002,Vo1.6 (5):357~363.
【42】马祖陆,茹锦文,刘光慧,遥感图像屏幕判读识别法在贵州岩溶山区土地调查种的应用[J],中国岩溶1995,Vo1.14 (3), 217~222.
【43】余旭初.遥感影像分析中的智能与可视化技术的联合研究, [博士论文],中国人民解放军测绘学院. 1997.
【44】刘纪远.中国资源环境遥感宏观调查与动态研究[M],中国科学技术出版社. 1996.
【45】林业部环境保护工作,www.sdinfo.net.cn/hjinfo/hjinfol bmhy/bmhy9-7/林业部环境保护工作.html .
【46】数字城市,http://www.sinowatch. com/07/default.htm .
【47】郭树桂.卫星遥感与制图[M],中国人民解放军测绘学院. 1984.
【48】Trolier, L.J. and W.R. Philipson. Visual analysis of Landsat Thematic Mapper images for hydrologic land use cover[J]. Photogrammetry Engineering. and RemoteSensing. 1986, vol.52(9):1531~1538.
【49】傅肃性.遥感专题分析与地学图谱[M],北京:科学出版社. 2002.
【50】李小文,高峰,王锦地,朱启僵.遥感反演中参数的不确定性与敏感性分析[J],遥感学报, 1997,Vol. 1(1) 5~14 .
【51】刘贵忠,邸双亮.小波分析及其应用[M],西安:西安电子科技大学出版社. 1992.
【52】催新春,裘季冰,张文龙.基于小波变换和数学形态学的人造景物提取[J],上海师范大学学报(自然科学版), 2002,Vo1.31(1), 42~46.
【53】陶洪久,柳健,田金文.基于小波变换和数学形态学的遥感图像边缘检测,红外与激光工程. 2002,vol.31(2),152~157.
【54】Multi-level Thresholding: Fuzzy Maximum Entropy Criterion Using ICM Proceedings of The First International Conference on Image And Graphics[J] ,Tianjin,China, 2000,Vo1.5, 293~298,
【55】Wang F., Improving Remote Sensing Image Analysis through Fuzzy Information Representation[J], PE&RS, 1990,Vol. 56(8), 1163~1169.
【56】孙丹峰,汲长远,林培.自组织网络与模糊规则结合在遥感土地覆盖分类中应用研究,中国土地科学. 1999,vol.12(5),42~44.
【57】骆剑承,周成虎,杨艳.具有部分监督的遥感影像模糊聚类方法研究及应用[J],遥感技术与应用, 1999,Vol. 14(4), 37~43.
【58】曹燕,宁书年,王四龙,刘玉荣.分形分维在遥感图像纹理分析中的应用[J],遥感技术与应用, 1997,Vo1. 12(4), 31~35 .
【59】Priebe, C. E,Solka, J. L., and Rogers, G. W. (1993), "Discriminant analysis in aerial images using fractal based features," Adaptive and Learning Systems, F. A. Sadjadi, Ed.,proc. SPIE 1962, 196~208.
【60】D.L.Civco. Artificial Neural Networks for land-cover Classification and Mapping[J],International Journal of Geographical Information System, 1993,Vol. 7(2), 173~186.
【61】Development of Improved Image Classification Algorithms to Extract Quantitative Urban/Suburban Landuse/Land Cover Information from High Spatial Resolution DigitalImagery, NASA Affiliate Research Center, 1998.
【62】H.Murai and S.Omatu. Remote Sensing Image Analysis Using a Neural Network and Knowledge-Based Processing[J], Int. J. Remote Sensing, 1997,vol.18(4): 811~828.
【63】李厚强,王宜主,刘政凯.一种适用于多类别遥感图像分类的新方法一符合神经网络分类方法[J],遥感学报, 1997,1, 257~261.
【64】庄镇泉,章劲松,神经网络与智能信息处理,http://www.ahetc.gov.cn/cid199910/07.htm.
【65】莫源富,周立新.分区分类法一针对山区遥感图像的一种全新的分类方法,中国岩溶,2000,vol.19(4),360～365.
【66】师庆东,吕光辉,潘晓玲.在NOAA遥感影像中根据植被区域特点分区分类及应用, http://www.xjb.ac.cnlxjlhs/kexie/articles/environment/environment42.htm.
【67】刘亚岚,阎守邑,王涛,肖春生.遥感图像分区自动分类方法研究[J],遥感学报, 2002,Vo1.6 (5), 327~363.
【68】Running SW, L.TR, etc. A remote sensing based vegetation classification logic for global land cover analysis[J],Remote Sensing of Environment, 1995, 51, 39~48.
【69】Apisit Eiumnoh, Rajendra P. Shrestha, Can DEM Enhance The Digital Image Classification. 1997.http://www.gisdevelopment.nebaars/acrsl/ts9/ts9007.shtml.
【70】吴炳方,黄绚,田志刚.应用遥感及地理信息系统进行植被制图[J],环境遥感, 1995,Vo1.10(1), 30~36.
【71】Apisit Eiumnoh, Rajendra P. Shrestha, Can DEM Enhance The Digital Image Classification. 1997. http://www.gisdevelopment.nebaars/acrsl/ts9/ts9007.shtml.
【72】吴信才,地理信息系统的基本技术与发展动态,http://159.226.117.32/body/article/gis- move.htm.
【73】余旭初,方勇, RS和GIS集成环境下的遥感图像分析技术[J],解放军测绘学报, 1997 ,Vo1.14(3), 176~181.
【74】P.V. Narasimha Rao, K.D. Reddy, T.S. Kumar, B.R.M.Rao, Mufti-resolution Segmentation and Classification of Remote Sensing Data[J], IAPRA &SIS, 2002 ,Vo1.34(7),150~154, "Resource and Environmental Monitoring", Hyderabad, India.
【75】党安荣王晓栋陈晓峰张建宝,ERDAS IMAGINE遥感图像处理方法[M],北京,清华大学出版社.2003.4
【76】刘俊平,黄华.城市绿地景观格局及其生态建设对策的探讨[J].内蒙古科技与经济.2000,vol.4:9~11.
【77】C.Y Jim a, Sophia S. Chen Comprehensive greenspace planning based on landscape ecology principles in compact Nanjing city, China. Landscape and Urban Planning . 2003,65:95~116.
【78】曹勇宏.城市绿地系统建设的生态对策以长春市为例[J].城市环境与城市生态. 2001,vol.14(5): 9~10.
【79】李锋,王如松.城市绿地系统的生态服务功能评价、规划与预测研究——以扬州市为例[J].生态学报.2003,vol.23(9):1929～1936.
【80】杨士弘.城市绿化树木碳氧平衡效应研究[J].城市环境与城市生态.1996,vol.9(1):37～39.
【81】周志翔,邵天一等.城市绿地空间格局及其环境效应——以宜昌市中心城区为例[J].生态学报.2004,vol.24(2):186～192.
【82】Graetz R D, Pech R R, Davis A W. The assessment and monitoring of sparsely vegetated rangelands using calibrated Landsat data[J]. International Journal of Remote Sensing,1988, vol.9(7):1 201~1 222.
【83】Peter R.J. North Estimation of AR, LAI, and vegetation fractional cover from ATSR-2 imagery[J].Remote Sensing of Environment, 2002, vol.80(1):114~121.
【84】Bannari A, Morin D, Bonn F. A review of vegetation indices[J]. Remote Sensing Reviews, 1995,13:.95~120.
【85】Baret E Guyot G. Potentials and limits of vegetation indices for LAI and APAR assessment[J]. Remote Sensing of Environment, 1991,vol.35 (2): 161~173.
【86】Duncan Stow D. Franklin Hope A. Assessing the relationship between spectral vegetation indices and shrub cover in the Jornada Basin New Mexico[J]. International Journal of Remote Sensing 1993,vol.14(18 ): 3395~3416.
【87】陈述彭,童庆禧,郭华东等.遥感信息机理研究[M].北京,科学出版社,1998: 139.
【88】胡良军,邵明安.论水土流失研究中的植被覆盖度量指标[J].西北林学院学报,2001, vol.16 (1):40~43.
【89】Anderson G L, Hanson J D, Haas R H. Evaluating landsat thematic mapper derived vegetation indices for estimating above-ground biomass on semiarid rangelands[J]. Remote Sensing of Environment 1993,vol.45 (2): 165~175.
【90】Muneni R B, Nemani Running S W Estimation of global leaf area index and absorbed parusing radiative transfer models[J]. IEEE Transactions on Geoscience and Remote Sensing. 1997,35:1 380~1 393.
【91】Myneni R B, Hall F q Sellers P S, Marshak A L. The interpretation of spectral vegetation indexes[J].IEEE Transactions on Geoscience and Remote Sensing,1995, 33:481~486.
【92】Myneni R B", Keeling C D, Tucker C J, Asrar Cz, Nemani R R. Increased plant growth in the northern high latitudes from 1981 to 1991[J]. Nature,1997, 386: 698~702.
【93】Bradley C Rundquist. The influence of canopy green vegetation fraction on spectral measurements over native tallgrass prairie[J]. Remote Sensing of Environment,2002. vol.81(1):129~135.
【94】Kaufman Y J.The Atmospheric Effect on Remote Sensing and Its Correction[A].Theory and Applications of Optical Remote Sensing[C], New York:Wiley. 1989, 336~428.
【95】Dymond J R, Shepherd J D, Qi J. A simple physical model of vegetation reflectance for standardizing optical satellite imagery[J]. Remote Sensing of Environment, 2001,vol.77 (2): 230~239.
【96】方红亮,田庆久.高光谱遥感在植被监测中的研究综述[J].遥感技术与应用,1998 ,vol.13 (1):62~69.
【97】Toby N, Carlson, David A Ripley. On the Relation between NDVI Fractional Vegetation Cover and Leaf Area Index[J]. Remote Sensing of Environment,1997, 62: 241~252.
【98】Dymond J R, Stephens P R, Newsome P F et al. Percent vegetation cover of a degrading Range land from SPOT[J]. International Journal of Remote Sensing, 1992 ,vol.13(11):1999~2007.
【99】Wittich K P, Hansing O. Area-averaged vegetative cover fraction estimated from satellite data[J]. International Journal of Biometerology, 1995, vol.38 (3):209-215.
【100】Purevdor J T S, Tateishi Ishiyama T, et al. Relationships between percent vegetation cover and vegetation indices[J]. International Journal of Remote Sensing, 1998, vol.19(18): 3 519~3 535.
【101】Leprieur C. Kerr Y H. Mastorchio S. et al. Monitoring vegetation cover across semi-arid regions:Comparison of remote observations from various scales[J]. International Journal of Remote Sensing, 2000,vol.21 (2): 281~300.
【102】Bradley C Rundquist. The influence of canopy green vegetation fraction on spectral measurements over native tallgrass prairie[J]. Remote Sensing of Environment,2002. vol.81(1):129~135.
【103】Qi J, Marsett R C, Moran M. S., Goodrich D. C, P. Heilman, Y. H. Kerr, G. Dedieu, A. Chehbouni and X. X. Zhang. Spatial and temporal dynamics of vegetation in the San Pedro River basin area[J].Agricultural and Forest Meteorology,2000,(105 ): 55~68.
【104】Zeng XuBin, Robert E, Dickinson Alison Walker, et al. Derivation and evaluation of global 1-km fractional vegetation cover data for land modeling[J]. Journal of Applied Meterology,2000,vol.39 (6):826~839.
【105】罗修岳,郑柯.脆弱生态环境植被指数和植被盖度数字图像的编制及其应用研究—以晋陕蒙地区为例.晋陕蒙接壤地区脆弱生态系统遥感监测与管理研究[M].北京:宇航出版1994,24~35.
【106】Goward S N, Haemmrich K F, blaring R H. Visible-near infrared spectral reflectance of landscape components in western Oregon[J]. Remote Sensing ofEnvironment, 1994, vol.47 (2):190~203.
【107】文贡坚,王润生.从航空遥感图像中自动提取主要道路[J].软件学报,2000,(11):17~20.
【108】Leprieur C, Kerr Y H, Pichon 3 M. Critical assessment of vegetation indices from AVHRR in asemi-arid environment[J]. International Journal of Remote Sensing, 1996,(17): 2 549~2 563.
【109】Leprieur C, Verstraete M M, Pinty B. Evaluation of the performance of various vegetation indices to retrieve vegetation cover from AVHRR data[J]. Remote Sensing Review, 1994,(10 ): 265~284.
【110】Qi J, Chenbouni A, Huete A R, et al. Modified soil adjusted vegetation index (MSAVI) [J]. Remote sensing of environment, 1994, vol.48 (2): 119~126.
【111】Kanemasu E T, Demetriades-Shah T H, Su H, Lang A R G. Estimating grassland biomass using remotely sensed data[J]. Applications of remote sensing in agriculture, Cambridge, Cambridge University Press, Clark M D S(Ed.), 1990, 185~199.
【112】Li Y, Demetriades-Shah T H, Kanemasu E T, Shultis J K, Kirkham M B. Use of second derivatives of canopy reflectance for monitoring prairie vegetation over different soil backgrounds[J].Remote Sensing of Environment,1993,vol.44(1):81~87.
【113】Major D J, Baret F, Guyot G.. A ratio vegetation index adjusted for soil brightness[J]. International Journal of Remote Sensing, 1990,(11):720~727.
【114】Clevers J G P W. The application of a vegetation index in correcting the infrared reflectance for soil background[J]. Proceedings of Symposium on Remote Sensing for Resources Development and Environmental Management, Enschede, 1986, 25-29.
【115】Huete A RJackson R D, Post, D F. Spectral response of plant canopy with different soil background[J]. Remote Sensing of Enivronment. 1985,vol.17(1):37~53.
【116】Qi J, Kerr Y., Chehbouni, A. External factor consideration in vegetation index development[J]. In:6th International Symposium on Physical Measurements and Signatures in Remote Sensing, Vald'Isere, France, January 17-21, 1994(Toulouse, France: CNES), 723~730.
【117】Anatoly A Gitelson, Yoram J Kaufman, Robert Stark, Don Rundquist. Novel algorithms for remote estimation of vegetation fraction[J]. Remote Sensing of Environment 2002,vol.80(1):76~87.
【118】Fernandez S, Vidal D, Simon E, Sole-Sugranes L. Radiometric characteristics of triticum aestivum cv. astral under water and nitrogen stress[J]. International Journal of Remote Sensing 1994,(15):1867~1884.
【119】Gitelson A, Merzlyak M.. Remote estimation of chlorophyll content in higher plant leaves[J].International Journal of Remote Sensing, 1997,(18 ): 291~298.
【120】Pinty B,Verstraete M M. GEMI: A non-linear index to monitor global vegetation from satellites[J].Vegetatio, 1992,101:15~20.
【121】Carlson T N, Ripley D A. On the relation between NDVI, fractional vegetation cover, and leaf area index[J]. Remote Sensing of Environment,1997 ,vol.62 ( 3):241~252.
【122】Liu Q, Huete A. A feedback based modification of the NDVI to minimize canopy background and atmospheric noise. IEEE Transactions on Geoscience and Remote Sensing, 1995, ( 33):457~465.
【123】Gillies R R, Kustas W P, Humes K S. A verification of the `triangle' method for obtaining surface soil water content and energy fluxes from remote measurements of the Normalized difference vegetation Index(NDVI) and surface [J]. International Journal of Remote Sensing, 1997,(18):3145~3166.
【124】Gitelson A, Kogan F, Zakarin E, Spivak L, Lebed L. Using AVHRR data for quantitive estimation of vegetation conditions: calibration and validation[J]. Advances in Space Research 1998 ,( 22):673~676.
【125】McDaniel K C, Haas R H. Assessing mesquite-grass vegetation condition from Landsat[J]. Photogrammetric Engineering and Remote Sensing,1982,( 48):441~450.
【126】Pickup G., Chewings V H, Nelson D J. Estimating changes in vegetation cover over time in arid rangelands using Landsat MSS data[J]. Remote Sensing of Environment, 1993 , vol.43 ( 3):243~263.
【127】张云柏.ASAR影像应用于水稻识别和面积测算研究-以江苏宝应县为例[D].南京:南京农业大学农学院,2004.
【128】Hansen, M. Dubayah, R. and DeFries.R. Classification Trees: An Alternative to Traditional Land Cover Classifiers [J], International Journal of Remote Sensing, 1996,vol.17(5):1075~1082.
【129】Winlinson G G and Megier J.Evidential Reasoning in a Pixel Classification Hierarchy—A Potential Method for integrating lmage Classifiers and Expect Systerm Rules Based on Geographic Context[J] . International Journal of Remote sencing.1990,vol.11(10).1963～1968
【130】Kontoes C,Wilkinson G G,Burril1 A,Goffredo S and Megier J.An Experimental System for the Integration of GIS Data in Knowledge—based Analysis for Remote Sensing of Agriculture[J] . International Journal of Geographic Information System,1993,vol.7(3):247～262
【131】M.A.Friedl and C.E.Brodley.Decision Tree Classification of Land Cover from Remotely Sensed Data [J].Remote Sensing Environment, 1997,vol.61(3):399~409.
【132】Rick L.Lawrence and Andrea Wright. Rule-Based Classification Systems Using Classification and Regression Tree (CART) Analysis [J], PE&RS 2001,67(10):1137~1142.
【133】Yoshikawa Masanobu, Shindo Hisakazu and Nishii, Ryuei. Fully automated design of binary decision tree for land cover classification, Proceedings of the 1995 International Geoscience and Remote Sensing Symposium. Part 3 (of 3), 1995,Jul 10~14.
【134】Tadjudin Saldju and Landgrebe David A.(1996). Decision tree classifier design for high-dimensional data with limited training samples. Proceedings of the 1996 International Geoscience and Remote Sensing Symposium, IGARSS'96. Part 1 (of 4), 1996,May 28~31.
【135】Franklin S.E., Stenhouse, G.B., Hansen, M.J., Popplewell, C.C., Dechka, J.A.and Peddle,D.R.(2001).An Integrated Decision Tree Approach (IDTA) to mapping landcover using satellite remote sensing in support of grizzly bear habitat analysis in the Alberta yellow head ecosystem [J].Canadian Journal of Remote Sensing, 2001,27:579~592.
【136】De Colstoun, Story Michael H. and Thompson Craig. (2002). Vegetation mapping using multitemporal ETM+ data and a decision tree classifier. 2002 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2002), 2002, Jun 24~28 2890~2892.
【137】Simard Marc, Saatchi, Sasan S. and De Grandi, Gianfranco. (2000). Use of decision tree and multiscale texture for classification of JERS-1 SAR data over tropical forest [J]. IEEE Transactions on Geoscience and Remote Sensing, 2000, 38:2310~2321.
【138】Palaniappan, Zhu Feng, Zhuang Xinhua and Zhao, Yunxin (2000). Enhanced Binary Tree Genetic Algorithm for automatic land cover classification. 2000 International Geoscience and Remote Sensing Symposium (IGARSS 2000), 2000, Jul24~Jul 28, 2:688~692.
【139】Ding Qiang, Ding Qin and Perrizo (2002). Decision tree classification of spatial data streams using peano count trees. Applied Computing 2002: Proceeedings of the 2002 ACM Symposium on Applied Computing, 2002,Mar11-14 ,413~417.
【140】Pal Mahesh and Mather Paul M. (2002). A comparison of decision tree and backpropagation neural network classifiers for land use classification. 2002 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2002), 2002, Jun 24~28 ,503~505.
【141】Saglam, Ersoy Okan and Yazgan, Bingul (2003). Self organizing map and linear support vector machine decision tree with optimized class separability. Smart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Complex Systems and Artificia Life-Proceedings of the Artificial Neural Networks in Engineering Conference,Nov 2~5 2003, 13:193~198.
【142】周春平,尹连旺.遥感影象制图综合的智能化研究[J] .遥感学报,1998,2(1).72～77.
【143】Barzoha M R,Cooper D B.Automatic Finding of Main Road in Aerial Images by Using CJeometricstochastic Models and Estimation.IEEE CVPR.1993.
【144】Sylvain A.From Manual to Automatlc Stereo Plotting:Evaluation of Different Road Network Capture Processes.IAPRS XXXI Part t33,Viena,1996.
【145】Trinder C.Wang Yandong.Automatic Road Extraction from Aerial Images[J].Digital Signal Processing, 1998, 8 (4): 215～224.
【146】邵振峰,影像线状地物与房屋的自动提取:[博士论文].武汉:武汉大学,2001.
【147】Eaumgarmer A.Extraction of Roads from Aerial Imagery Based on Grouping and Local Context.ISPRS Comm.ⅢWorkshop,1998.