3S技术在河北省唐山市地面形变监测和城市扩展中的应用研究
详细信息    本馆镜像全文|  推荐本文 |  |   获取CNKI官网全文
摘要
地面形变是在自然因素和人为因素作用下形成的地表垂直向变形现象。在我国有许多城市和地区都发生了不同程度的地面形变现象。随着国民经济的进步,城市建设的进度飞速进展,地面形变的危害也日趋显著,它具有分布广、变化过程不易觉察等特点。在我国北方大多数城市以及沿海大多数城市和地区都有不同程度的地面形变问题,其直接影响着社会经济、区域环境的可持续发展,威胁着当地人民的生命财产安全。因此,及时准确地监测地面形变及其发展过程具有重要的意义。
     本文基于雷达遥感和光学遥感技术,以河北省唐山市为研究区,研究了利用多传感器、多时相遥感数据对采煤塌陷区沉降信息提取的方法技术。在此过程中,充分利用研究区已有的资料和信息以及该领域的先验知识等参照信息,结合光学遥感与雷达遥感各自特性和优势,提取研究区较长时期内的地面形变信息,包括变化区域、变化速度、变化量等,并分析了地面形变灾害发生的原因及其对城市扩展的影响。初步形成了一套适合矿业城市地面形变遥感信息提取的有效方法组合和工作流程,达到了通过遥感技术对矿业城市的地面形变引起的灾害和城市扩展进行宏观、快速、准确监测的目的,从而为相关职能部门提供决策依据。
     本文取得的主要创新点和研究成果如下:
     1、将雷达遥感与光学遥感技术相结合来研究城市地面变形,有效地提高了城市地面形变的研究效果。利用雷达遥感技术提取高精度的地面沉降垂直信息,光学遥感技术结合积水现象间接提取沉降区域的空间展布,两者各取所长、相互补充、相互验证。此方法为研究矿业城市地面形变、矿区地面沉降预测和趋势分析,提供了一种科学、合理、有效的方法,并具有可行性和可操作性。
     2、利用ASTER的多波段数据,详细分析了塌陷区域地物的光谱特征。针对煤炭和污水水体的异物同谱现象,提出了一种基于ASTER数据的归一化差异水体指数的算法,即NDWIASTER1、4=(ASTER1-w×ASTER4)/(ASTER1 + w×ASTER4)。该方法是在前人研究基础上完善和发展得到的,经过应用与验证,效果良好。此方法不仅解决了研究区域的地物分类问题,也为遥感技术应用到城市地面变化监测方面提供有力参考。
     3、首次将研究数据和信息经过格式转换、投影变换整合到数字地球平台之上,利用数字地球平台的三维显示、图层交互操作等功能优势,将矿区分布、积水分布和沉降区域分布相结合进行分析和验证,提高了分析效率和准确性。
     4、系统阐述了地面形变的三种类型、采煤引起的灾害程度最大的塌陷的原因、塌陷的三种模式、影响塌陷的原因。在此基础上分析了塌陷是如何引起积水,然后得出利用积水来监测采煤塌陷的可行性结论。
     5、文章围绕遥感技术在采煤塌陷区地面沉降监测应用展开研究,详细分析和论述了雷达遥感、光学遥感相关核心技术和整个应用技术体系,并针对城市分布和采煤塌陷集中区的遥感信息提取技术做了深入讨论,对所提取信息的准确度和精确度做了系统分析和评价。
     6、基于论文所研究技术,利用TM、ETM、ASTER多源、多时相遥感数据,结合开滦煤矿的矿区分布,有效提取了研究区的6个时相的积水信息。同时,采用GIS技术进行了数据叠置和统计分析,得到了开滦煤矿10个矿区的积水变化图,包括10个矿区的积水动态变化面积、区域、速度等。依据积水的变化信息,分析了开滦煤矿塌陷10个矿区的塌陷状况。
     7、围绕城市扩展信息提取,论文采用多源、多时相的光学遥感数据,利用波段组合、图像增强、数据融合、地物分类等方法技术,提取了唐山市不同时期的轮廓图。在对唐山市的扩展面积、速率和方向进行全面分析的基础上,分析了采煤塌陷对唐山市城市扩展影响。发现唐山市东北的荆各庄也会在不久的将来阻挡唐山市往东北方向的发展,得出唐山市以后应该往西和西北两个方向发展的合理性结论。
     8、基于雷达遥感干涉测量技术,充分利用和参考以上研究成果和区域相关信息,提取了研究区5个时间段历时10年来的沉降量变化信息。在有效验证和结果数据分析的基础上,讨论了沉降变化的影响因素。自1999年唐山市被列入国家级采煤塌陷区综合治理示范区以来,在唐山市区全面禁止地下煤炭开采。雷达监测结果数据表明沉降速度变缓、面积变小,这和相关部门得出的唐山市地面沉降得到了有效控制的结论一致。
The ground deformation is the surface vertical deformation phenomenon caused by natural factors and human factors.In our country,the surface deformation phenomenon of different degree have taken place in many cities and regions.With the rapid development of urban construction,the ground deformation hazards are becoming increasingly important,and it has the characteristics of wide distribution and changing process difficult to detect.Most of the northern cities ,many coastal cities and regions are all facing the problem of ground deformation,which directly influences the regional environment and the sustainable development of social economy,and threatens people’s safety of life and property . Consequently,it is important to monitor accurately land subsidence and its development.
     Based on radar remote sensing and optical remote sensing technology,this dissertation takes Tangshan City in Hebei Province as the study area, and using the multi-sensor and multi-temporal remote sensing data ,studies the methods and techniques of the subsidence information extraction in coal mining collapse area.In this process,making full use of the existing data ,information and priori knowledge in this field ,etc.of the study area,and combining the respective characteristics and advantages of radar remote sensing and optical remote sensing,the longer-period ground deformation data of the study area is extracted ,including change area,change speed and change quantity,etc.as well as analyzes the occurrence cause of ground deformation hazards and its influences on urban expansion.It has preliminarily formed a set of effective method combination and work flow suitable to ground deformation remote sensing information extraction of the mining cities,and achieves the goal of the macroscopic,fast and accurate monitoring of the urban expansion and hazards caused by ground deformation in mining cities by remote sensing tenology,then provides decision basis for the relevant functional departments.
     The maincreative contributions and research results of this dissertation are listed as follows:
     1.Combining radar remote sensing with optical remote sensing, high precision land subsidence vertical information is extracted by radar remote sensing technology,and the spatial distribution of subsidence regions is extracted indirectly by combining optical remote sensing technology with hydrops phenomenon,each taking its director, and achieving the mutual complementation as well as the mutual verification.This method provides a scientific,reasonable and effective way for studying ground deformation of mining cities,land subsidence prediction and trend analysis of the mining regions, also having feasibility and maneuverability.
     2.Based on ASTER multi-band remote sensing data, analyzing in detail spectral characteristics of ground objects located in subsidence regions,and aiming at the fact that different objects have the same spectrum,the method of normalized difference water index based on ASTER data is presented,namely NDWIASTER1、4=(ASTER1 - w×ASTER4)/(ASTER1 + w×ASTER4). The method is obtained from the improvement and development of the previous research, The application and verification of this method shows good effect.This method not only solves the problems of terrain classification in study area,but also provides the powerful reference for applying the remote sensing technology into the ground surface deformation monitoring in urban areas.
     3.First time integrating the research data and information into the Digital Earth Platform(DEP) by format conversion and projection transformation,and taking functional advantage of DEP,such as the three-dimensional display, interactive operation on layer,etc.the combination of the mining area distribution, hydrops distribution and subsidence area distribution is analyzed and verified,then improving the analysis efficiency and accuracy.
     4.It is systematically expounded that the three types of ground deformation,the reasons of subsidence caused by the coal mining which has the maximum hazard degree,three models of subsidence,and influencing factors of subsidence.On the basis,analyzing how subsidence causes hydrops,then the feasible conclusion of monitoring coal-mining subsidence by hydrops is drawed
     5.The dissertation carries out research on the application of remote sensing technology in monitoring ground subsidence of coal-mining collapse area,analyzing and discussing in detail the core technology related to radar remote sensing and optical remote sensing, and the whole application technique system.It maks deep discussion on remote sensing information extraction technology of cities distribution and coal mining subsidence concentration area,and maks systematic analysis and evaluation for the accuracy and precision of the information extracted.
     6.Based on the technology studied of this dissertation,six phases hydrops information in study area is extracted by TM、ETM、ASTER multi-source and multi-temporal remote sensing data,combining with the mining area distribution of Kailuan Coal Mine.Meanwhile,data overlay and statistical analysis are made by GIS technology,producing the hydrops change maps of ten mining areas of Kailuan Coal Mine,which included the area,region and speed of hydrops dynamic change of the ten mining areas.In terms of hydrops change information,the subsidence status of ten collapse mining areas of Kailuan Coal Mine is analyzed.
     7.Around the urban expansion information extraction, the dissertation adopts the multi-source and multi-temporal optical remote sensing data. Making use of methods and technologies named band combination,image enhancement,data fusion and terrain classification,etc.the outline drawing during different periods in Tangshan is extracted.On the basis of the comprehensive analysis on the expansion area,rate and direction of Tangshan City,it analyzes the influence which is caused by coal-mining subsidence on Tangshan city expansion.Founding that Jing Ge Zhuang located in the north-east of Tangshan City will hinder the development along the north-east direction of Tangshan City in the near future, the reasonable conclusion which shows Tangshan ought to develop towards the west and north-west direction is drawed.
     8.Based on the radar remote sensing interferometry technology,making full use of the above research results and information related to the region,the subsidence quantity change information of the five time segments during the decade is extracted.On foundation of the effective validation and result data analysis,it discusses influencing factors of subsidence change.Since Tangshan City was listed in the comprehensive treatment demonstration zone of the national coal-mining subsidence region in 1999,underground coal mining is totally banned in Tangshan urban area.The radar satellite monitoring results shows the velocity of subsidence is becoming slower,and the area of subsidence is becomig smaller,which is consistent with the conclusion drawed by the related departments that is the ground subsidence of Tangshan City has been controlled effectively.
引文
[1]承继成,郭华东,史文中等.遥感数据的不确定性问题[M].北京:科学出版社,2004.
    [2]陈基炜.利用GPS-InSAR合成方法进行地面沉降研究与展望[J].测绘科学,2003, 28(4):69-71.
    [3]陈俊勇.对SRTM和GTOPO30地形数据质量的评估[J].武汉大学学报,2005, 30(11):941-943.
    [4]陈敏,刘秉瀚,杨靛青. TM遥感图像中居民点的自动提取[J].福州大学学报(自然科学版). 2004,12(4):95-98.
    [5]陈述彭.地球信息科学与区域持续发展[M].北京:测绘出版社,1995.
    [6]陈述彭.遥感地学分析的时空维[J].遥感学报,1997, 1(3):161-171.
    [7]陈述彭,童庆喜,郭华东.遥感信息机理研究[M].北京:科学出版社,1998.
    [8]戴昌达,姜小光,唐伶俐.遥感图像应用处理与分析[M].北京:清华大学出版社,2004.
    [9]邓辉,黄润秋. InSAR技术在地形测量和地质灾害研究中的应用[J].山地学报,2003,21(3):373-377.
    [10]邓文胜,关泽群,王昌佐.从TM图像中提取城镇建筑覆盖区专题信息的改进方法.遥感信息[J],2004(4):43-46.
    [11]地面沉降——第六届地面沉降国际讨论会论文选.地质出版社,2001.
    [12]丁德亮,郑汝海,邵斌.关于机场选址的思考[J].山西建筑. 2007,33(22)27-28.
    [13]杜培军,郭达志.遥感图像与DTM的复合及其在矿山的应用[J].煤田地质,2000, 9(30):5-7.
    [14]杜培军.高分辨率卫星遥感的发展及其在矿山的应用[J].煤田地质,2000, 10(1):5-7.
    [15]杜培军.工矿区陆面演变与空间信息技术应用的研究[D].中国矿业大学(徐州).2003,32(1):94.
    [16]杜培军,郭达志. GIS支持下遥感图像中采矿塌陷地提取方法研究[J].中国图像图形学报,2003, 8(2):231-235.
    [17]杜培军,陈云浩.向工矿区陆面演变分析的多源遥感信息融合[J].辽宁工程技术大学学报,2005,24(2):172-174.
    [18]杜培军,郑辉,张海荣.矿业/矿区发展空间信息技术保障体系研究进展与若干关键技术. 2007,25(9):52-58.
    [19]杜兴明,郉忠信.唐山是岩溶塌陷地质灾害治理勘查工作研究[J].华东地质矿产杂志, 1999,14(2):273-276.
    [20]郭华东等.雷达对地观测理论与应用[M].北京:科学出版社,2000.
    [21]郭华东.感知天地——信息获取与处理技术[M].北京:科学出版社,2000.
    [22]郭泺,夏北成,余世孝.森林景观格局研究中的尺度效应[J].应用与环境生物学报. 2006, 12(3):304-307.
    [23]果巧真.采煤塌陷区遥感动态监测系统的研究[D].河北理工大学,2004.
    [24]韩明正.采煤塌陷矿区土地整理模式研究[D].北京:中国农业大学,2004.
    [25]何庆成,方志雷,李志明等. InSAR技术及其在沧州地面沉降监测中的应用[J].地学前缘, 2006,13(1):179-184.
    [26]黄小雪,罗麟,程香菊.遥感技术在灾害监测中的应用[J].四川环境,2004,23(6):102-106.
    [27]姜春玲,吴泉源,杨胜军等.基于RS技术的土地覆被变化区位效应分析——以龙口煤矿塌陷区为例[J].国土资源遥感,2007,(1):73-77.
    [28]李成尊,聂洪峰,汪劲等.矿山地质灾害特征遥感研究[J].国土资源遥感,2005, 63(1):45-48.
    [29]李连济.煤炭城市采空塌陷及经济转型[J].经济学研究,2006, (5):56-60.
    [30]李远华,姜琦刚.基于遥感调查与GIS分析的林芝地区地质灾害评价[J].国土资源遥感,2006,57(2):57-60.
    [31]李远华.遥感与GIS技术支持下藏东林芝地区地质灾害预警研究[D].硕士论文.吉林:吉林大学,2004.
    [32]梁家琳.欧空局干涉合成孔径雷达差分测量与相关特性的应用[J].测绘通报,1998,(1):5-6.
    [33]廖明生,林珲.雷达干涉测量:原理与信号处理基础[M].北京:测绘出版社.2003.
    [34]刘国祥,丁晓利,陈永奇等.极具潜力的空间对地观测新技术—合成孔径雷达干涉[J].地球科学进展, 2000,15(6):734-739.
    [35]刘国祥,刘文熙,黄丁发. InSAR技术及其应用中的若干问题[J].测绘通报,2001,(8): 10-12.
    [36]刘国祥,丁晓利,陈永奇等.使用卫星雷达差分干涉技术测量香港赤腊角机场沉降场[J].科学通报, 2001,46(14):1224-1228.
    [37]刘国祥,丁晓利,等.星载SAR复数图像的配准[J].测绘学报. 2001, 30(1):60-66.
    [38]刘国祥. InSAR基本原理[J].四川测绘. 2004, 27(4):187-190.
    [39]刘国祥.利用雷达干涉技术监测区域地表形变[M].北京:测绘出版社,2006.
    [40]刘廷权,朱庆杰,苏幼坡,张秀彦.唐山市基岩破裂对地震动的影响分析[J].岩石力学与工程学报. 2004,23,(10):1765-1769.
    [41]刘建国.陆地卫星MSS图像地表水域信息的机助识别提取[J].环境遥感,1989,4(1):19-27.
    [42]刘瑞,苗放,叶成名.基于数字地球平台的油气工程技术应用[J].成都理工大学学报(自然科学版),2009,36(2):118-121.
    [43]陆建华,周锦华.开滦矿区开采塌陷特征分析及综合防治对策[J].土地复垦,2000,(1):42-43.
    [44]鹿献章,杨义忠,喻根等.淮北市北区地表水体及采空塌陷遥感调查[J].安徽地质,1997,7(1):79-87.
    [45]路旭,匡绍君,贾有良等.用InSAR作地面沉降监测的试验研究[J].大地测量与地球动力学,2002, 22(4):66-70.
    [46]马蔼乃.遥感信息模型[M].北京:北京大学出版社,1996.
    [47]毛建旭,王耀南,夏耶.合成孔径雷达干涉成像技术及其应用[J].系统工程与电子技术,2003, 25(1):7-10.
    [48]梅安新,彭望绿,秦其明.遥感导论[M].北京:高等教育出版社,2001.
    [49]苗放,叶成名,刘瑞,等.新一代数字地球平台与“数字中国”技术体系架构探讨[J].测绘科学,2007,32(6): 157-158.
    [50]牟凤云,张增祥,迟耀斌等.基于多源遥感数据的北京市1973—2005年间城市建成区的动态监测与驱动力分析[J].遥感学报,2007,11(2):257-268.
    [51]彭苏萍,王磊,孟召平等.遥感技术在煤矿区积水塌陷动态监测中的应用——以淮南矿区为例[J].煤炭学报,2002,27(4):374-378.
    [52]舒宁.微波遥感原理[M].武汉:武汉测绘科技大学出版社,2000.
    [53]舒宁.雷达图像干涉测量原理[M].武汉:武汉大学出版社,2003.
    [54]镡志伟.煤层群开采的地面沉陷评价研究[D].北京:中国地质大学(北京),2007.
    [55]汤国安,张友顺,刘咏梅等.遥感数字图像处理[M].北京:科学出版社,2003.
    [56]汪宝存,苗放,晏明星,赖得军,陈建华.基于遥感技术的开滦煤矿地面塌陷积水动态监测.国土资源遥感,2007,73(3):94-97.
    [57]王超,张红,刘智.星载合成孔径雷达干涉测量[M].北京:科学出版社,2002.
    [58]王超,张红,刘智等.苏州地区地面沉降的星载合成孔径雷达差分干涉测量监测[J].自然科学进展,2002,12(6):621-624.
    [59]王洪涛,王恩志,李士雄.唐山市岩溶地面塌陷成因机制与迭置分析方法[J].中国岩溶,1996(5):311-318.
    [60]魏风华.唐山市岩溶塌陷机制分析.地质与勘探[J],2006,2(42):86-89.
    [61]吴立新,高均海,葛大庆等.基于D-InSAR的煤矿区开采沉降遥感监测技术分析[J].地理与地理信息科学. 2004, 20(2):22-25.
    [62]吴立新,高均海,葛大庆等.工矿区地表沉陷D-InSAR监测试验研究[J].东北大学学报(自然科学版),2005, 26 (8):778-782.
    [63]肖平,万剑华.合成孔径雷达干涉测量技术及其在生成DEM和监测地层变化中的应用[J].测绘通报,1998,(6):2-4.
    [64]熊春宝,唐立刚,匡绍君等.大范围地面沉降的差分GPS监测法[J].岩土力学. 2003, 24(6):931-934.
    [65]徐涵秋.基于压缩数据维的城市建筑用地遥感信息提取[J].中国图象图形学报. 2005,10(2):223-229.
    [66]徐涵秋.利用改进的归一化差异水体指数(MNDWI)提取水体信息的研究[J].遥感学报, 2005,9(5):589-595.
    [67]杨存建,周成虎. TM图像的居民地信息提取方法研究[J].遥感学报, 2000(2):146-150.
    [68]杨武年,濮国梁,CAUNEAU F等.长江三峡库区地质灾害遥感图像信息处理及其监测和评估[J].地质学报,2005,79(3):423-428.
    [69]殷作如,邓智毅,董荣泉.开滦矿区采煤塌陷地生态环境综合治理途径[J].矿山测量, 2003 (3):21-24.
    [70]尤惠川,徐锡伟,吴建平,何正勤.唐山地震深浅构造关系研究[J].地震地质,2002(24):571-582.
    [71]查勇,倪绍祥,杨山.一种利用TM图像自动提取城镇用地信息的有效方法[J].遥感学报,2003(1):37-41.
    [72]张文华,赵安文.地面塌陷的模式及特殊危害[J].地质灾害与环境保护,2003,14(1):7-10.
    [73]张晓玲,王建国,黄顺吉.干涉SAR成像中地形高度估计及基线估计方法的研究[J].信号处理,1999,15(4):316-320.
    [74]赵英时.遥感应用分析原理与方法[M].北京:科学出版社,2002.
    [75]赵宗壮,杜兴明,刘志刚.唐山市区岩溶地面塌陷及其防治[J].中国地质灾害与防治学报,1998(9):222-227.
    [76]张梁,张业成,罗元华等.地质灾害灾情评估理论与实践[M].北京:地质出版社,1998.
    [77]张艳梅.基于雷达差分干涉技术的地震形变场测量研究[D].武汉大学, 2005.
    [78]中华人民共和国地质矿产部,中华人民共和国国家科学技术委员会,中华人民共和国国家计划委员会.中国地质灾害与防治[M].北京:地质出版社,1991.
    [79]周成虎,骆剑承,杨晓梅等.遥感图像地学理解与分析[M].北京:科学出版社,1999.
    [80]周群.采煤塌陷地致灾机理及恢复治理研究-以肥城市为例[D].山东农业大学, 2005.
    [81]周宇鹏,苗放,叶成名,等.基于Google Earth的GIS开发模式探讨[C].中国地球物理年会22届年会,2006.
    [82]朱彩英,蓝朝桢,靳国旺.纹理图象亮度阈值法提取SAR图象居民地.中国图象图形学报. 2003, 8(6):611-620.
    [83]朱庆杰,苏幼坡,刘廷全.唐山市岩溶塌陷安全评价[J].中国安全科学学报,2004(12):91-95.
    [84]朱庆杰,苏幼坡.唐山市地质灾害综合防灾研究.防灾减灾工程学报[J],2005(25):309-314.
    [85] Andrew Jarosz and Dieter Wanke Use of InSAR for Monitoring of Mining Deformations. FRING 2003 Workshop, Frascati, Italy.
    [86] Antonello q Casagli N, Farina P, et al. Ground Based SAR Interferometry for Monitoring Mass Movements [J].Landslides, 2004, 1(1):21-28.
    [87] A. S. M. Maksud Kamal, Saburoh Midorikawa. 2004. GIS-based geomorphological mapping using remote sensing data and supplementary geoinformation a case study of the Dhaka city area, Bangladesh.International Journal of Applied Earth Observation and Geoinformation, 2004, (6):111–125.
    [88] A. Volcani, A. Karnieli, T. Svoray. The use of remote sensing and GIS for spatio-temporal analysis of the physiological state of a semi-arid forest with respect to drought years. Forest Ecology and Management, 2005, 215:239–250.
    [89] Beaudueel F. and Biole P., Voleano wide fringes in the ERS SAR interferograms of Etna (1992-1998): Deformation or troposphere effete. Journal of Geophysical Research, Vol105, NoB7, Pages16, 391-16, 402, July2000.
    [90] BulmerMH, PetleyDN, MurphyW. SAR in landslide monitoring[J]. Ceo-physieal Researeh Abstraets, 2003, 5(3):37-43.
    [91] Carnec C, Massonnet D, King C. Two Examples of the Use of SAR Interferometry on Displacement Fields of Small Spatial Extent [J]. Geophysical Research Letters, 1996, 23(24) 3579-3582
    [92] Carnec C, et al. Monitoring and modeling land subsidence at the Cerro Prieto geothermal field, Baja California, Mexico, using SAR interferometry. Geophysical Research Letters,1999, 26(6):1211
    [93] Carnec C, Delacourt C. Three Years of Mining Subsidence Monitored by SAR Interferometry, Near Gardanne, France [J]. Journal of Applied Geophysics, 2000, 43(1): 43-54.
    [94] Chen C.W. Statistical-cost Network-flow approaches to Two-dimensional phase unwrapping for radar interferometry[D].USA: Stanford University,2001.
    [95] Cheng S Y, Huang G H, ChakmaA, et al. Estimation of atmospheric mixing height using data from airport meteoro logical stations [J]. Journal of Environmental Science and Health-Part A, 2001,36(4):521-536.
    [96] Cheng S Y, Jing Y Q , Liu L , et al. Estimation of atmospheric mixing height over large area using data from airport meteoro-logical stations [J].Journal of Environmental Science and Health-Part A , 2002, 37(6):991-1007.
    [97] Dekker A G, Vos R J, Peters SMW. Comparison of Remote Sensing Data, Model Results and in Situ Data for Total Suspended Matter TSM in the Southern Frisian Lakes [J].The Science of the Total Environment, 2001,(268):197-214.
    [98] Ding X.L. G.X.LIU Z.W.LI Ground Subsidence Monitoring in Hong Kong with Satellite SAR interferometry Advanced Workshop on InSAR for Measuring Topography and Deformation of Earth Surface [J].Dec.16-17, 2002, Hong Kong
    [99] Eric J F, et al. Rapid subsidence over oil fields measured by SAR interferometry. Geophysical Research Letters, 1998, 25(17):3215
    [100] Fielding E J, Blom R G Goldstein M R. Rapid Subsidence over Oil Fields Measured by SAR Interferometry [J]. Geophysical Research Letters, 1998, 25 (17): 3215-3218.
    [101] Floyd M. Henderson , Zong-Guo Xia. SAR application in human settlement detection,population estimation and urban land use pattern analysis:a status report,IEEE Transaction On Geoscience And Remote Sensing,Vol.35,NO.1,pp79-85,January,1997.
    [102] Franceschetti G, Lanari R. Synthetic Aperture Radar Processing . Florida, CRC Press, 1999, pp188-195.
    [103] Gabtiel A K, Goldstein R M, Zebker H A. Mapping Small Elevation Changes Over Large Areas: Differential Radar Interferometry [J]. Journal of Geophysical Research, 1989, 94(B7):9183-9191.
    [104] Gatelli. F, Guarenieri. A. M, Parizzi. F. The Wavenumber Shift in SAR Interferometry[J]. IEEE Transactions on Geoscidence and Remoter Sensing, et 1994, 32(4):855-865.
    [105] Gini Ketelaar,Freek van Leijen,Petar Marinkovic ON THE USE OF POINT TARGET CHARACTERISTICS IN THE ESTIMATION OF LOW SUBSIDENCE RATES DUE TO GAS EXTRACTION IN GRONINGEN,THE NETHERLANDS. FRING 2005 Workshop.
    [106] Goldstein R M. Atmospheric Limitations to Repeat Track Radar Interferometry[J].Geophysical Research Letters, 1995, 22(18):2517-2520.
    [107] Graham L C. Synthetic Aperture Radar for Topographic Mapping. Proc. IEEE, 1974, 62, 763-768.
    [108] Goldstein R M, Zebker H A, Werner C L. Satellite Radar Interferometry: Two Dimensional Phase Unwrapping [J]. Radio Science, 1988, 23:713-720.
    [109] Hanqiu Xu. Modification of normalized difference water index (NDWI) to enhance open water features in remotely sensed imagery [J]. International Journal of Remote Sensing,2006,27(14):3025-3033.
    [110] Hanssen R. F, Radar Interferometry一Data Interpretation and Error Analysis[M].Kluwer Academic Publishers, 2001
    [111] Jianguo Liu,Hoonyol Lee,Guandao Hu,Jianguo Chen. Land Subsidence in Guan-Zhong Basin, Shan-Xi, China–A Sar Interferometric Study,Towrads Digital Earth--Proceedings of the International Symposium On Digital Earth,Since Press,1999.
    [112] Kampes, B., (1999) Delft Object-oriented Radar Interferometric Software User’s manual, Delft University of Technology, Nederland.
    [113] Li, Z. W., X. L. Ding and G. X. Liu, Modeling atmospheric effects on InSAR with meteorological and continuous GPS observations: algorithms and some test results [J]. Journal of Atmospheric and Solar - Terrestrial Physics, Vol. 66, pp. 907 - 917, 2004.
    [114] Liu, Rui; Kong, Xiangsheng; Miao, Fang; Ye, Chengming. Earth science framework research based on the digital earth platform[C]. Proceedings of SPIE - The International Society for Optical Engineering, v 6753, n PART 2, Geoinformatics 2007: Geospatial Information Science, 2007, p 67531V.
    [115] Rui, LIU; Fang MIAO; Baocun WANG. Using the Information of Ground Sunk Seeper Monitoring the Mining Subsidence[C]. 8th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences. World academic press, pp 114-118, 2008.
    [116] Rui Liu, Fang Miao, and Baocun Wang. Dynamic Monitoring the Sunk Seeper of KaiLuan Coal Mine Based on the RS Technique[C]. 2008 International Workshop on Education Technology and Training and 2008 International Workshop on Geoscience and Remote Sensing. IEEE Computer Society Conference Publishing Services, pp 179-182, 2008.
    [117] Madsen S N, Zebker H A, Martin J. Topographic Mapping Using Radar Interferometry: Processing Techniques [J]. IEEE Transactions on Geoscience and Remote Sensing, 1993, 31(1):246-256.
    [118] Massonnet D, Rabaute F. Radar Interferometry: Limits and Potential [J]. IEEE Transactions on Geoscience and Remote Sensing, 1993, 31(2):455-464.
    [119] Massonnet D, Rossi M, Carmona C, et al. The Displacement Field of the Landers Earthquake Mapped by Radar Interferometry[J].Nature,1993,364(8):138-142
    [120] Massonnet D, Holzer T, Vadon H. Land Subsidence Caused by the East Mesa GeothermalField, Calfornia, Observed Using SAR Interferometry [J]. Geophysical Research Letters, 1997, 24(8):901一904.
    [121] McFeeters S K. The Use of Normalized Difference Water Index(NDW I) in the Delineation of Open Water Features [J].International Journal of Remote Sensing, 1996,17(7):1425—1432.
    [122] Miao Fang, Ye Chengming, Bi Xiaojia, Wu Zhenhan, Kong Xiangsheng, Liu Rui, Yan Mingxing[C]. D-InSAR to inspect the active fault of Kunlun mountains on Qinghai-Tibet plateau. Proceedings of SPIE - The International Society for Optical Engineering, v 6795, Second International Conference on Space Information Technology, 2007, p 679520.
    [123] Mora O, Broquetas A. Linear and Nonlinear Terrain Deformation Maps From a Reduced Set of Interfore-metric SAR Images [J]. IEEE Transactions on Geoscience and Remote Sensing, 2003, 41(10):2243-2253.
    [124] Nellis M D, John A, Harrington Jr, et al. Remote Sensing of Temporal and Spatial Variations in PoolSize, Suspended Sediment, Turbidity, and Secchi Depth in Tuttle Creek Reservoir, Kansas: 1993[J]. Geomorphology, 1998,21:281- 293.
    [125] Pathier, E.,Fruneau,B.,Deffontaines, B.Angelier, J.Chang, C.P., Yu,S.B., Coseismic displacements of the footwall of the ChelungPu fault caused by the1999,Taiwan,Chi-Chi earthquake from InSAR and GPS data.,Earth Planet. Sci. Lett., 212, 73-88, 2003.
    [126] Perski Z. Applicability of ERS-1 land ERS-2 InSAR for Land Subsidence Monitoring in the Silesian Coal Mining Region, Poland [J]. International Archives of Photogrammetry and Remote Sensing, 1998, 32(7): 555-558.
    [127] PRAKASH, GUPTA R P. Land use mapping change detection in coal mining area-a case study in the Tharia, Coalfield, India[J]. International Journal of Remote Sensing, 1998, 19(3):391-410.
    [128] Rashed T, Weeks J R, GadallaM S, et al. Revealing the Anatomy of cities through spectral mixture analysis of multispectral satellite imagery: a case study of the Greater Cairo, Egypt [J]. Geocarto International, 2001,16(4):5~16.
    [129] Ursula C. Benz, Peter Hofmann, Gregor Willhauck, Iris Lingenfelder, Markus Heynen. Multi-resolution, object-oriented fuzzy analysis ofremote sensing data for GIS-ready information. ISPRS Journal of Photogrammetry & Remote Sensing, 2004, 58:239-258.
    [130] Xia Ye, Kaufmamnn H, X F Guo. Landslide Monitoring in the Three Gorges Area Using D-INSAR and Corner Reflectors. Advanced Workshop on InSAR for Measuring Topography and Deformation of the Earth Surface[C], 2002, Dec 16-17,Hong Kong.
    [131] Yan Mingxing, Miao Fang, Wang Baocun. Application of D-InSAR and GIS for Underground Mine Subsidence Monitoring. "Mapping without the Sun". Techniques and Applications of Optical and SAR Imagery Fusion. 2007,ISPRS VOLUME:XXXVI,PART7/C54.
    [132] Yang L, Huang C, Homer C G, et al. An app roach for mapping large-area impervious surfaces: synergistic use of Landsat27 ETM+ and high spatial resolution imagery[J]. Canadian Journal of Remote Sensing, 2003, 29(2):230~240.
    [133] Yasushi Yamaguchi, Anne B. Kahle, HirojiTsu, et al. Overview of Advanced Spaceborne Thermal Emission and Reflection Radiometer ( ASTER ) [J].IEEE Transactions on Geoscience and Remote Sensing.1998,36(4):1062-1071.
    [134] Ye, Chengming, Miao, Fang, Kong, Xiangsheng, Bi, Xiaojia, Liu, Rui. The oil and gas engineering techniques based on Digital Earth Platform[C]. Proceedings of SPIE - The International Society for Optical Engineering, v 6795, Second International Conference on Space Information Technology, 2007, p 679579.
    [135] Yueqin Zhou, Roland Klees, J.L.van Gendren et al. Differential SAR interferometry: Principles and Application [J]. ISPRS 2000, Amsterdam, The Netherlands, 2000, 227-236.
    [136] Y. Yamaguchi, H. Fujisada, M. Kudoh. ASTER Instrument Characterization and Operation Scenario[J].Advances in Space Research.1999,23(8):1415-1424.
    [137] Zebker H A, Goldstein R M. Topographic Mapping from Interferometry Synthetic Aperture Radar Observation. Journal of Geophysical Research, 1986, 91, 4993 - 4999.
    [138] Zebker H A, Villasenor J. Decorrelation in Interferometric Radar Echoes [J]. IEEE Transactions on Geoscience and Remote Sensing, 1992, 30(5): 950-959.
    [139] Zebker H A, Rosen P A, Goldstein R M, et al. On the Derivation of Coseismic Displacement Fields Using Differential Radar Interferometry: The Landers Earthquake [J]. Journal of Geophysical Research, 1994, 99(B10):19617-19634.
    [140] Zha Y, Gao J, Ni S. Use of normalized difference built-up index in automatically mapp ing urban areas from TM imagery[J].International Journal of Remote Sensing, 2003,24(3):583~594.
    [141] Zhang Q, Wang J, Peng X, et al. Urban built2up land change detection with road density and spectral information from multi-temporal Landsat TM data [J].International Journal of Remote Sensing,2002,23(15):3057~3078.