用户名: 密码: 验证码:
土地开发整理工程的遥感评价方法研究与应用
详细信息    本馆镜像全文|  推荐本文 |  |   获取CNKI官网全文
摘要
土地整理是人类文明用地的产物,是人类利用自然和改造自然的措施,是社会经济发展到一定阶段解决土地利用问题的必然选择。从目前我国开展土地开发整理的实践看,较普遍的存在重数量、轻质量和生态,开发整理规划、可行性研究、整理工程量计算、整理后的土壤质量评价等事项主要以图纸、人工为主,较少采用遥感、地理信息系统等先进高效的技术方法。对土壤的质量验收鉴定及整理后的成果管理等方面缺乏先进有效的方法,而开发整理出的耕地质量较差很难形成一定的生产能力甚至造成丢荒,这不仅没有实现真正意义上的耕地整理开发,而且造成了资源的破坏和开发资金的浪费。
     随着土地整理实践的开展,目前已有大量项目竣工验收进入运行阶段,这些项目决策是否正确、预期目标和效益是否实现等尚不明确,急需进行后评价。
     遥感(RS,Remote Sense)用于大范围、高分辨率、快速信息获取,将“RS”技术应用于土地开发整理项目信息采集、处理和分析,可以进一步规范土地开发整理规划编制,对土地开发整理工程设计与实施动态监测、工程验收、特别是评价工程效果,可以极大提高技术含量,从而提高项目质量和效率。为此,我们以湖南省国土资源厅重点资助项目“基于遥感反演的土地开发整理评价”研究课题为带动,开启了国内用遥感这一当今先进手段评价土地开发整理之先河。
     综合运用多种研究方法,包括静态分析与发展动态预测相结合、政策规程与实际工程需要相结合的评价体系研究、遥感定性分析与定量计算相结合、传统技术与现代新技术方法相结合等科学的综合分析方法。通过较为系统的研究主要取得了如下成果:
     (1)依据《中华人民共和国土地管理法》及国土资源部《土地开发整理项目验收规程》等相关法律、法规,结合湖南省土地开发整理之省情和试验区实际情况,在研究高分辨率遥感信息特点和定量遥感解译理论的基础上,提出了用定量遥感方法,按土地平整工程、农田水利工程、田间道路工程、其他工程(防风林工程等)等四个方面的指标评价土地开发整理工程的工程量。项目区实验表明,该方法速度快、效率好、精度高、劳动强度极低、反应工程完成情况全面,分类提取的指标信息与实际情况情况很吻合。
     (2)在研究了土壤含水量、土壤有机质含量、地表温度、植被指数及其植被状态指数和条件温度植被指数等方面用遥感直接或间接评价了土壤质量,充分说明了其具有较好的、开创性的、发掘性的应用遥感技术能够评估或评价土壤质量和土壤农作潜力的基础上。指出,目前还没有建立土地开发整理工程及其土壤质量改善等方面有机结合系统评价土地开发整理工程的评价体系,更是没有建立用遥感方法评价土地开发整理工程评价体系。本研究在前人遥感应用的基础上,从多个遥感数据源预处理、分析入手,提出了用遥感方法评价开发整理工程的工程量,采用修正土壤调整植被指数、植被覆盖度、土壤含水量、土壤潜育化指标、LBV变换等比较关键性的指标对土地开发整理工程影响土壤质量情况进行较为科学客观的评价评价。
     (3)通过分析遥感信息物理机理、遥感图像处理解译原理及土壤遥感信息特征和提取特点之后,首先研究了对用于整理工程量评价的高分辨率Quickbird影像,在国产软件TITAN Image 6.5进行切割(根据评价的区域进行)和二维三次卷积内插法(4个单色波段及1个全色波段)融合;其次,为了保证精度,采用了GPS实测地面控制点,以多项式为几何纠正模型,对融合后的影像进行影像空间像元位置的变换,再用双三次插值法计算变换后各像元的亮度值,即像元亮度值的重采样。计算结果表明:点位误差均小于1m,,若换算成像元,点位误差在1个像元左右,完全满足整理工程量信息提取要求;其三,提出并采用ISODATA(自组织分类)方法,有效提取项目区内不同地块的面积值,沟渠和道路等线状物的长度值。面积提取精度在97%以上,线状物长度提取精度在98%以上。利用分类图及结合现场数据,还可以有效的进行灌排系统布局合理性分析、防护林分布合理性分忻、道路网布局合理性分析。
     (4)分析研究了土壤含水量与土壤质量的相关关系、土壤水分的光谱特征、土壤湿度与相对反射率,探讨了作物缺水指数法、距平植被指数法、微波遥感监测土壤水分、热惯量法、数据同化法等遥感方法提取土壤含水量的适应性,提出用光学植被盖度遥感分析土壤水分,利用样本统计和相关分析相结合的方法,建立了光学植被盖度的TM模型及不同深度土壤水分与遥感植被绿度指数之间的回归模型,对试验区各个时像的TM影像进行了土壤三个不同层次的含水量信息提取和分析。同时用其模型提取了项目区IKONOS影像、中巴资源一号卫星影像三个层次的土壤含水量信息。依据提取的信息分析了项目区土地开发整理后土壤质量改善提高情况,分析成果与实地情况一致,量化了土地整理效果。
     (5)研究了植被指数、植被覆盖度与土壤质量的定量关系。综合分析了比值植被指数RVI、归一化植被指数NDVI、差值植被指数DVI、土壤调节植被指数SAVI、增强植被指数EVI以及植被覆盖度等与土壤质量之间的关系特征;提出了MSAVI(称为“修正型土壤调整植被指数”)模型,像元二分植被盖度模型;通过试验区多种遥感影像MSAVI指数、像元二分模型参数提取分析,证实了它们是适合评价试验区土壤质量的指标。
     (6)通过研究土壤潜育化与土壤质量相关关系的特性,潜育化土壤热力学特征及其遥感解译机理,指出了涝渍灾害土壤的热惯量概念模型、数值解算模型,得出了用遥感的方法研究农田涝渍灾害致使土壤潜育化理论和实际可行性。
     研究指出,卫星遥感影像上存在着三个重要的地物遥感特征,即地物的总辐射水平L、可见光-红外光辐射平衡B和地物辐射随波段变化的方向和速度—向量V,进而提出用遥感图像LBV数据变换法进行试验区IKONOS等遥感影像的变换与信息提取,试验和证实了所建立的LBV变换方程。成果证明试验区开发复垦之前土地荒芜、积水严重、潜育化厉害,与实际情况相同。
     通过本文的系统研究和项目区实际检验,证实了定量遥感能很好地应用于土地丌发整理的工程量评价和土壤质量评价,其研究成果,能为国土局以及相关部门对土地复垦项目的验收提供有力支持;充分说明了遥感反演技术用于评价土地丌发整理项目的工程量完成情况真实、可靠、可行,为遥感的应用开辟了新途径;有力证明了应用定量遥感----遥感反演监测评价土地整治质量准确、有效,动态性强、时效性高。本研究在大规模的土地开发整理工程评价中大有发展潜力。
Land consolidation is a result of civilized land use of human beings, an approach to utilize and transform the nature by human, and an inevitable choice to solve the problem of land use when economy developed into a certain degree. From the point of view of the practice of land development and land consolidation in our country, there commonly exist problems of preferring quantity to quality and ecologic environment; consolidation planning, feasibility study, calculation of consolidation engineering volume, soil quality assessment after consolidation are done by hand, rarely with advanced and effective technologies and methods such as remote sense, geographic information system etc. Soil quality acceptance and result management after consolidation lack advanced and effective methods; and if the consolidated land is of inferior quality, it will not own certain production capacity and in the contrary will result in land lying waste. This kind of consolidation has not realized the real consolidation and development of cultivated land and even resulted in destruction of resources and wasting of development fund.
     With the development of land consolidation practice, at present, the acceptance of a great number of completed projects has entered the operational phase. It is still unclear whether these projects are correct and whether the anticipatory goals and benefits can be achieved. Hence, post-evaluation is urgently needed.
     Remote Sense provides quick access to vast amounts of high-resolution information. Application of "RS" in the acquisition, processing and analysis of land development information and consolidation information can further standardize the compiling of land development and consolidation plan, and greatly increase the technical contents in land development and consolidation design, implementation of dynamic monitoring, acceptance of projects, particularly, appraisal of project achievements, thus improving the quality and efficiency of the projects. Motivated by the research subject of "Evaluation of Land Development and Consolidation Based on RS", a key project sponsored by The Land and Resources Department of Hunan Province, we applied advanced method-RS to evaluate land development and consolidation for the first time in China.
     By comprehensively employing multi research approaches, including evaluation system study which combines static analysis with development forecasting, policy regulations with practical engineering needs, and scientific integrated analysis approach which combines RS qualitative analysis with quantitative analysis, traditional technology with modern new technology, the systematic study comes to fruition:
     (1) In conformity with the relevant laws and regulations, such as the Land Administration Law of the PRC and The Acceptance Codes of Land Development and Consolidation Project, combined with the actual situation of experimental areas and the land development and consolidation of Hunan, the research, based on the features of the high-resolution remote sensing information and the remote sensing interpretation system, proposes quantitative remote sensing method, which can evaluate the engineering quantity of the land development and consolidation project according to land-leveling project, water conservancy and irrigation, crisscross footpaths project and other projects (windbreak forest project etc.). The experiment in project area shows that this method has such characteristics as high speed, high efficiency, high degree of accuracy, extremely low labor intensity, etc; also it can reflect the performance of the project in a complete way. And the extracted index information of classification closely meets the actual conditions.
     (2) When studying soil moisture, soil organic matter content, land surface temperature, vegetation index, vegetation condition index and vegetation-temperature condition index through remote sensing, soil quality is evaluated directly or indirectly. This fact can speak volumes for the ability of inaugurated applicable remote sensing technology to evaluate or assess the quality and agriculture potential of soil. Based on this conclusion, the reserch shows that there is neither any evaluation system which can systematically assess the land development and consolidation project through the organic combination of the land development and consolidation project with the improvement of the soil quality, nor any evaluation system to evaluate land development and consolidation project by means of remote sensing. Based on the previous application of remote sensing, this research proposes engineering quantity evaluation of land development and consolidation project by using remote sense, starting with the pretreatment and analysis of multi remote sensing data sources. This research makes relatively scientific and objective evaluation on the influence of the land development and consolidation project towards the soil quality through the utilization of the relatively critical indexes such as the MSAVI, vegetation coverage, soil moisture, soil gleying index, LBV transformation.
     (3) After analyzing information mechanism, interpretation theory of remote sensing image processing, features and extraction characteristics of remote sensing information of soil, this research first studies the high-resolution Quickbird image, which is used to sort the evaluation of the engineering quantity, through cutting the images on the home-produced software TITAN Image 6.5 (according to the regions of evaluation) and blending the images through the 2-D cubic convolution (4 monochromatic bands and 1 panchromatic band ); second, in order to assure the accuracy, this research adopts the GPS-measured ground control points, uses the polynomial as the geometric correction model to change the images spatial pixel position of the blended images, then utilizes the bi-cubic interpolation to calculate the pixel lightness value after the change of position, namely resampling of pixel lightness value. According to the results of calculation, the position errors of points are less than 1m; after converted into pixel, the errors are about 1 pixel, so they can meet the requirements of the information extraction of consolidation engineering quantity. Third, the research proposes and adopts the method of ISODATA (self-organizing classification) to effectively extract the area value of different areas in the project area and the length of threads such as ditches and roads. The accuracy of extracted area is above 97%; the accuracy of the extracted length is above 98%. Using classification map and onsite data, rationality analysis of irrigation and drainage systems layout, rationality analysis of windbreak forest distribution and rationality analysis of road network distribution can be made.
     (4) The paper analyzes the correlation between soil water content and soil quality, spectral signatures of soil moisture, soil moisture and relative reflection; probes into adaptability of extracting soil moisture content by using such remote sensing methods as crop water stress index method, average vegetation index method, microwave remote sensing orientation method, thermal inertia approach and data assimilation method; puts forward the idea of analyzing soil moisture with optical vegetation coverage remote sense; builds TM model of optical vegetation coverage and regression model between soil moistures at different depths and greenness indexes of remote sensing vegetation by using the approach of combining sample statistics with correlation analysis; makes information extraction and analysis of soil moisture content in three different layers on TM image of experimental area at different time. Meanwhile, IKONOS image in project area and soil moisture content information in three different layers of CBERS-1 satellite image are extracted with the help of this model. According to the information extracted, the improvement and promotion state of soil quality after land development and consolidation are analyzed. And the results of analysis are corresponding with the actual situation, thus quantizing the soil consolidation effects.
     (5) This paper studies the quantitative relationship among vegetation index, vegetation coverage and soil quality ; comprehensively analyzes the relationship characteristic between soil quality and such indexes as ratio vegetation index (RVI), normalized difference vegetation index (NDVI), difference vegetation index (DVI), soil adjusted vegetation index (SAVI), enhanced vegetation index (EVI) and vegetation coverage ; establishes MSAVT (called 'modified soil adjusted vegetation index') model and dimidiate pixel model of vegetation coverage. By analyzing MSAVI index of various remote sensing images in experimental area and dimidiate pixel model parameter, this paper testifies that these indexes are suitable for soil quality evaluation in experimental area.
     (6) By studying the nature of correlation between gleying process of soil and soil quality, thermodynamic characteristics of gleyed soil as well as remote interpretation mechanism, this paper puts forward thermal inertia conceptual model of water-logging disaster soil, number resolution model, and points out the theoretical and practical feasibility of using remote sense to study the phenomenon of water-logging disaster leading to soil gleying.
     The study points out that there are three important remote characteristics of surface features on satellite remote sensing imaging map, namely overall radiation level of surface features—L, the direction and speed of change of visible light-infrared radiation balance B and surface features radiation with band change—vector V; further proposes to adopt IKONOS and other remote sensing images transformation and information extraction in experimental area through remote sensing image LBV data transformation. The established LBV transformation equation is also testified by experiments. The serious degrees of land barrenness, standing water and gleying of soil before the reclamation in the experimental area are identical with the actual situation.
     Through systematic research in this paper and actual inspection in project area, it is verified that quantitative RS is well applicable for the evaluation of project quantity of land development and consolidation as well as soil quality assessment. The research findings can be forceful support of the acceptance of land reclamation project run by Land and Resources Bureau or relevant departments. This paper fully proves that applying RS retrieve technique to evaluate the performance of the engineering quantity of land development and consolidation project is true, reliable and feasible. This approach is a new way for RS application. This paper also forcefully proves that the approach of employing quantitative RS--RS retrieve monitoring to evaluate land consolidation quality is characterized by accuracy, effectiveness, strong dynamics and timeliness. This study has great development potential in the evaluation of large-scaled land development and consolidation projects.
引文
[1]王如渊.土地整理与耕地总量动态平衡[J].中国土地,1999(2):25-26
    [2]陈述彭,童庆禧,郭华东.遥感信息机理研究[M].北京:科学出版社,1998
    [3]罗明,张惠远.土地整理及其生态环境影响综述[J].资源科学,2002,24(2):36-39
    [4]郭洪泉.我国农村土地整理的法律思考[J].中国土地科学,2004(1):32-34
    [5]毕宝德.土地经济学(修订本)[M].北京,中国人民大学出版社1998
    [6]冯秀丽,王珂,施拥军等.基于遥感的土地整理研究[J].科技通报,2003,22(3):258-266
    [7]蒋一军.我国农村土地整理研究[D][博士论文],北京大学,2001
    [8]鞠正山,罗明,张凤荣等.区域土地整理的方向[J].农业工程学报,2003,19(2):6-11
    [9]桂林.土地开发整理(复垦)机制及效益评价研究---以秀山土家族苗族自治县为例[硕士学位论文].重庆:西南师范大学,2004
    [10]Davidson D.RenfrewshireA.The influence of land capability on rural land sales:a case study in Renfrewshire Scotland.Soil use and management.1989,1:38~44
    [11]Klingebiel.A.A.,and Montgomery.Land Capability Classification.P.H.USDA Handbook 210.U.S.Department of Agriculture,Washington,D.C,1961
    [12]FAO.A framework for land evaluation..Rome:FAO Soil Bulletin,1976,1~8
    [13]国土资源部.土地丌发整理项目验收规程[M](TD/T1013-2000),3-8
    [14]杨相和.国外土地整理的启示与借鉴.国土经济[J],2002,7:43-44
    [15]李相一,赵继成.遥感技术在我国土地管理中的应用.遥感信息[J],2003,1:26-27
    [16]Obukhov A I.Orlov D C.Spectral Reflectivity of the Major Soil Groups and possibility of Using Diffuse Reflection in Soil investigations[J].Pochvove- deniye,1964(2).
    [17]Baumgardner M F,Kristof S,Johannsen C J,et al.Effects of Organic Matter on the Multispectral Properties of Soils[J].Proc.Indiana Acad.Sci,1970(79):413-422.
    [18]Coleman T L,Montgomery 0 L.Soil Moisture Organic Mitterrand Iron Content Effect on Spectral Characteristics of Selected Verticals and Alfisols in Alabama[J].Photogrammetric Engineering and Remote Sensing,1987(12):1659-1663.
    [19]Galvao L S,et al.Variations in Reflectance of Tropical Soils:Spectral-Cihemical Composition Relationships from AVIRIS Data[J].Remote Sens.Envir.,2001(75):245-255.
    [20]Alicia P 0.Susan L.U.Remote Sensing of Soil Properties in the Santa Monica Mountains I.Spectral Analysis[J].Remote Sense.Envir.,1998(65):170-183.
    [21]冷疏影,李秀彬.土地质量指标体系国际研究的新进展[J].地理学报,1999,54(2):177-185
    [22]刘晓冰,刑宝山.土壤质量及其评价指标[J].农业系统科学与综合研究,2002,2,4-6.
    [23]张国印.河北平原土壤总质量评价和方法初探[硕士论文].中国农业大学,p6-8.
    [24]蒲春玲,吴郁玲,金晶.国外土地整理实施经验对新疆土地整理的启示[J].农村经济,2004,2:95-97
    [25]杨相和.国外土地整理的启示与借鉴.国土经济[J].2002,7:43-44
    [26]Ray W.Archer.Lessons from the PB Selayang Land Consolidation Project in Medanlndonesia[J].Land Use Policy.1992(October):287-299
    [27]Philip Oldenburg.Land Consolidation as Land Reform in India[J].World Development,1990,18(2):183-195.
    [28]Erich wei β(贾生华译),联邦德国的乡村土地整理[M].北京:中国农业出版社,1999,10-18
    [29]范金梅.土地整理效益评价研究[J].中国土地,2003(10):14-15
    [30]范树印,许建斌.探索土地开发整理新路[J].中国土地,2002(8):39-41
    [31]范文义,周洪泽.资源与环境地理信息系统[M].北京:科学出版社,2003
    [32]范志书.土地利用工程[M].北京:农业出版社,1987
    [33]张献忠,底艳,董棉安等.土地开发整理项目的土地质量评价[J].资源科学,2004,26(2):138-144
    [34]韩毅.土地利用动态遥感监测成果应用现状及信息共享策略[J].国土资源信息化,2006,2:2-5
    [35]徐金鸿,徐瑞松,夏斌等.土壤遥感监测研究进展[J].水土保持研究,2006,13(2):17-20
    [36]Price J C.The potential of remotely sensed thermal infrared data to infer surface soil moisture and evaporation[J].Water Resources Research,1980,16(4):787-795
    [37]邢素丽,张广录.我国农业遥感的应用现状与展望[J].农业工程学报,2003,19(6):174-178
    [38]孙家抦.遥感原理与应用[M].武汉:武汉大学出版社,2003
    [39]梅安新 彭望琭 秦其明等.遥感导论[M].北京:高等教育出版社,2004
    [40]李元 鹿心社.国土资源与经济布局国土资源开发利用50年[M].北京,地质出版社 1999
    [41]严全明 钟金发 池国仁.土地整理[M].北京:经济管理出版社,998
    [42]国家土地管理局规划司.国内外土地整理借鉴[M].北京:中国大地出版社,1998
    [43]刘文甲.抓整理-促转变-保发展[J].中国土地,1999(4):3-45
    [44]郑威 陈述彭.资源遥感纲要[M].中国科学技术出版社,175-178,1995
    [45]徐冠华.再生资源遥感的理论与技术应用[M].中国林业出版社,1994
    [46]李建智.土地整理理论基础与政策取向的探究[J].南方国土资源,2003,(8):55-57
    [47]罗明.龙花楼.土地整理理论初探[N].中国国土资源报,2002-4-25(3).
    [48]王瑷玲.区域土地整理时空配置及其项目后评价研究与应用[博士论文].山东农业大学,2006
    [49]张永生 王仁礼.遥感动态监测[M].北京:解放军出版社,1999
    [50]章孝灿.黄智才.赵元洪.遥感数字图像处理[M].杭州:浙江大学出版社.1997.
    [51]George Wolberg,H M Sueyllam,M A Ismail,et al.One-Dimensional Resembling with Inverse and Form and mapping Functions[J].Joana loaf Graphics Tools,2000,5(3):11-33
    [52]P Chalemwat.High Performance Automatic Image Registration for Remote Sensing[Ph D Thesis].George Mason University,1999
    [53]浦瑞良 宫鹏.高光谱遥感及其应用[M].北京:高等教育出版社,2000
    [54]徐彬彬 等.土壤光谱反射特性研究及其应用[J].土壤学进展,1987,15(1):1-7
    [55]戴昌达 等译.遥感技术在土壤和水资源研究中的应用[M].北京:科学出版社,1981
    [56]Stoner E R,et al,Soil spectral characterization IGARSS,1981,1426-1437.
    [57]朱震福 等.遥感定量方法[M].北京:科学出版社,1984
    [58]张均萍 张哗 周廷显.成像光谱技术超光谱图像分类研究现状与分析[J].中国空间科学技术,2001,(1):37-34
    [59]田庆久 阂祥军.植被指数研究进展[J].地球科学进展,1998(4):327-333
    [60]Vall derMeer F O,BakkerW H,ScliolteK,et al.Spatial scale variation in vegetation indices and above-ground biomass estimates imp canons for MERIS [J].International Journal of Remote Sensing,2001,22(17):3351-3396
    [61]李新 陈贤章 程国.地形对高山区积雪定量遥感的影响[J].遥感技术与应用,1999,12(1):1-7
    [62]徐兴个 林朝晖 薛峰等.气象因子与地表植被生长相关性分析[J].生态学报,2003,23(2):221-230
    [63]舒宁.国内外有关成像光谱数据影像分析方法研究[J].国土资源遥感,1998,(1):16-20
    [64]李天宏 杨海宏 赵永平.成像光谱仪遥感现状与展望[J].遥感技术与应用,1997,(2):54-58
    [65]孟庆香.基于遥感、GIS和模型的黄土高原生态环境质量综合评价[博士学位论文].西北农林科技大学,2006
    [66]张成才 吴泽宁 余弘蜻.遥感计算土壤含水量方法的比较研究[J].灌溉排水学报,2004,23(2):69-72
    [67]陈怀亮 毛留喜.遥感监测土壤水分的理论、方法及研究进展[J].遥感技术与应用.1999,14(2):55-65.
    [68]刘培君 张琳.卫星遥感估测土壤水分的种方法[J].遥感学报.1997,1(2):135-139.
    [69]裴浩.范一大.利用气象卫星遥感监.测土壤含水量[J].干旱区资源与环境资源与环境.1999,13(1):73-76
    [70]陆家驹 张和平.应用遥感技术连续监测地表土壤含水量[J].水利学进展,1997,8(3):281-287
    [71]D Singh,P K Mukherjee.Effect of soil moisture and crop cover in remote sensing[J].Adv Space Res.1996,18(7):63-66
    [72]覃志豪等:用陆地卫星TM 6数据演算地表温度的单窗算法[J].地理学报,2001,56(4):456-466
    [73]Hurtado E,V idalA,CasellesV.Comparison of two atmospheric correction methods for Landsat TM thermal band[J].International Journal of Remote Sensing,1996,17,237-247
    [73]徐金鸿 徐瑞松 夏斌 朱照宇.土壤遥感监测研究进展[J].水上保持研究,2006,13(2):17-20
    [74]Elienne Muller,Henri Decamps.Modeling soil moisture reflectance[J].Remote Sensing of Environment,2000,76:173-180
    [75]Dalal R C,Henry R J.Simultaneous determination of moisture,organic carbon and total nitrogen by near infrared reflectance spectroscopy[J].Soil Sci.Soc.Am.J.,1986,50:120-123
    [76]Ben-Dor E,Banin A.Near-infrared analysis as a rapid method to simultaneously evaluate several soil properties[J].Soil Sci.Soc.Am.J.,1995,59:364-372
    [77]沙晋明 陈鹏程 陈松林.土壤有机质光谱响应特性研究[J].水上保持研究,2003,10(2):21-24
    [78]陈怀亮,麦田土壤水分NOAA/AVHRR遥感监测方法研究[J].遥感技术与应用,1998,13(4):27-35
    [79]彭玉魁 张建新 何绪牛等.土壤水分、有机质和总氮含量的近红外光谱分析[J].土壤学报,1998,35(4):553-559
    [80]闫娜娜 吴炳方 黄慧萍 牟伶俐.植被状态指数和温度条件指数的提取方法[J].世界科技研究与发展,2005,27(4):65-71
    [81]Kogan F N.Remote sensing of weather impacts on vegetation in non-homogenous areas[J].International Journal of Remote Sensing,199011:1405-1419
    [82]Liu W,Kogan F N.Monitoring regional drought using the vegetation condition index[J].International Journal of Remote Sensing,1996,17:2761~2782
    [83]蔡斌 陆文杰等.气象卫星条件植被指数监测土壤状况[J].国土资源遥感,1995,4:45~50
    [84]齐述华 王长耀 牛铮.利用温度植被旱情指数(TVDI)进行全国旱情监测研究[J].遥感学报,2003,7(5):420~423
    [85]刘成林.中国陆地1km AVHRR数据集开发方法研究[博士学位论文].中国科学院研究生院,2004
    [86]冯强 田国良 王昂生 柳钦火.基于植被状态指数的全国干旱遥感监测试验研究(Ⅰ)-资料分析与处理部分[J].干旱区地理,2004,27(2):131~136
    [87]冯强 田国良 王昂生.基于植被状态指数的土壤湿度遥感方法研究[J].自然灾害学报,2004,13(3):81~87
    [88]王鹏新 龚健雅 李小文.条件植被温度指数及其在干旱监测中的应用[J].武汉大学学报(信息科学版),2001,26:412~418
    [89]王鹏新 WAM Zheng-ming龚健雅 李小文 王锦地.基于植被指数和 土地表面温度的干旱监测模型[J].地球科学进展,2003,18(4):528~533
    [90]国土资源部.土地开发整理项目验收规程(TD/T1013-2000),3-8
    [91]Price J.C.Using Spatial Context in Satellite Data to Infer Regional Scale Evapotranspiration.IEEE Transactions on Geoscience and Remote Sensing,1999,28:940-948
    [92]Moran M S.,Clarke T R.Inoue Y.Estimating Crop Water Deficit U-sing the Relation between Surface-Air Temperature and Spectral Vegetation Index Remote Sense[J].Environ,1994,49(3):246-263
    [93]李首成.川中丘陵区人为影响下的乡村景观格局和碳氮长期变化研究[博士学位论文].中国农业大学,2005
    [94]傅泊杰 陈利顶 马克明等.景观生态学原理及应用[M].北京:科学出版社,2001
    [95]高永光 胡振琪.高光谱遥感技术在土壤调查中的应用[J].矿业研究与开发.2006,26(1):44-46
    [96]Bowers S A,hanks R J.Reflection of radiant energy from soil[J].Soil Science,1965,100:130-138
    [97]Stoned E R,Baunganluer M F.Characteristic variations in reflectance of surface soils[J].Soil Sci,1981,45:1161--1165
    [98]Liu W D,Bare F,Gu X F,eatal.Relating soil surface moisture to reflectance[J].Remote Sense,2002,81(2/3):238-246
    [99]刘伟东,张兵,等.高光谱遥感土壤湿度信息提取研究[J].土壤学报.2004,41(50):700-706
    [100]李新举 胡振琪 刘宁等.黄河三角洲土壤肥力质量的时空演变--以垦利县为例[J].植物营养与肥料学报,2006,12(6):778--783
    [101]郭云开.基于广义夹角的遥感图像计算机分类方法研究[J].中国公路学报,2002,15(2):28-30
    [102]郭云开等.应用遥感进行土壤含水量分析[J].遥感技术,1995,10(3):16-19
    [103]林辉 何安国 赵煜鹏等.QUICKBIRD数据处理及其应用[J].遥感信 息,2004,2:20-23
    [104]刘仁钊 廖文峰.遥感图像分类应用研究综述[J].地理空间信息,2005,3(5):11-13
    [105]赵春霞 钱乐祥.遥感影像监督分类与非监督分类的比较[J].河南大学学报,2004,34(3):90-93
    [106]Marroquin J,Mitter S K,Poggio T.Probabilistic solution of ill-posed problems in computational vision[J].J Amer.Stat Assoc,1987,82(3):76-89.
    [107]Laferte J.M erez P.Heitz F.Discrete Markov image modeling and inference on the quadtree.IEEE Trans Image Processing,2000,9(3):390-404.
    [108]邢凡胜.基于遥感技术的土地整理及项目区路网布局评价:[硕士学位论文].长沙:长沙理工大学,2007
    [109]郭云开 陈正阳 王钦 邢凡胜.基于遥感技术的土地复垦工程量评价研究[J].测绘通报,2008,4,(373):17-20
    [110]Shi X Z.Yu D,S,Wamer E D,et al.A Framework for the 1:1000000 soil Database of China[A].In proceedings of the 17th world congress of soil science[C].Bangkok,2002,1757:1-5
    [111]McBratney A B.Mendonea Santos M L.MinasnyB.On Digital Soil Mapping[J].geoderma,2003,117:3-52.
    [112]Zhang J P.Wang D J.Wang Y K,et al.Discusses on Environment Changes in Dry-hot Valley of Yunnan,China[J].Journal of Arid Environment,2002,51:153-162
    [113]北京东方泰坦有限科技公司.TITAN遥感影像处理系统适用于手册:1-8
    [114]Thomas M.Lillesand,Ralph W.Kiefer.Remote Sensing and Image Interpretation[M],彭望琭等译.北京:电子工业出版社,2003,333-335
    [115]郭云开 陈正阳 彭悦 邢凡胜 王钦.土地复垦工程的遥感评价[J].遥感技术与应用,2008,23(3):249-254
    [116]刘伟东.高光谱土壤遥感信息提取与挖掘研究:[博士学位论文].北京:中国科学院遥感应用研究所,2002
    [117]Jackson R D,Idso S B.Reginao R J.Canopy temperature as a crop water stress indicator[J].Houston:Water Resource Research,1981,17(4):1133-1138
    [118]张立福.通用光谱模式分解算法及植被指数的建立:[博士学位论文].武汉:武汉大学,2005
    [119]韦红波.区域植被水土保持功能遥感评价研究:[博士学位论文].陕西杨凌:西北农林科技大学,2001
    [120]李苗苗.植被覆盖度的遥感估算方法研究:[硕士学位论文].北京:中国科学院遥感应用研究所,2003
    [121]熊明彪 舒芬 宋光煌等.南方丘陵区土壤潜育化的发生与生态环境建设[J].土壤与环境,2002,11(2):197-201
    [122]龚子同 韦启播,黄诫等.关于水稻土的次生潜育化问题[J].土壤学报,1981,18(2):122-135
    [123]朱祖祥.土壤学[M].北京:农业出版社.1983.280-285
    [124]马毅杰,陆彦椿,赵美芝,等.长江中游平原湖区土壤潜育化沼泽化的发展趋势与改良利用[J].土壤,1997(1):1-5
    [125]ZENG ZY,PAN X Z.Study on soil gleization in subtropic region of china using LBV transformed landsat images[J].Pedosphere,1997,7(3):219-224.
    [126]Moskul G A.Peculiarities of feeding two-year-old silver carp and bighead in esturaries of Krasnodarsk territory[J].Gidrobiol Zhum,1977,13:45-50
    [127]何力胜 李卫红 童成立.江汉平原农田渍害与土壤潜育化发展现状及治理对策[J].土壤与环境,2000,9(3):214-217
    [128]赵美芝 邓又军 马毅杰.长江中游潜沼化土壤限制因子及其对策研究[J].长江流域资源与环境,1997,6(1):18-23
    [129]PAN S Z.Characterization of gleyization of paddy soils in the middle reaches of the Yangtze River[J].Pedosphere,1996(2):111-119
    [130]四川省农牧厅四川省土壤普查办公室.四川土壤[M].成都:四川科技出版社,1995:392-442
    [131]喻光明.江汉平原渍害田热力学特性及其遥感研究[J].环境科学学报,1994,14(4):475-481
    [132]Price J.O.Remote Sensing of Environment.1966,18(1):42-59
    [133]张仁华.土壤热惯量遥感模型[J].科学通报.1991,26(12):918-924
    [134]曾志远.卫星遥感图像计算机分类与地学应用研究[M].北京:科学出版社,2004.163-194
    [135]倪绍祥.土地类型与土地评价概论[M].北京:高等教育出版社,1999
    [136]Zhou Y,Lu X X,Huang Y,et al.Anthropogenic Impacts on the Sediment Flux in the Dry-hot Valley of Southwest China-an Example of the Longchuan River[J].Journal of Mountain Science,2004,1(3):239-249.
    [137]Zhou H M.Chen X L.Tian L Q.A New Method to Retrieve Terrain Shadow Based on Mult-spectral Operation[A].IGARSS'06 Proceeding[c].2006.
    [138]Park S C.Park M K.Moon G K.Supper-Resolution Image Reconstruction:A Technical Overview[J].IEEE Signal Processing Magazine,2003,20(3):21-36
    [139]邹谋炎.反卷积和信号复原[M].北京:国防工业出版社,2001
    [140]黄文江 王纪华 刘良云等.冬小麦品质的影响因素及高光谱遥感监测方法[J].遥感科技与应用,2004,19(3):143-148.
    [141]Zhao C J.Liu L Y.Wang J H.et al.Predicting Grain Protein Content of Winter Wheat Using Remote Sensing Data Based on Nitrogen Status and Water Stress[J].International Journal of Earth Observation and Geoinformation,2005.7(1):1-9
    [142]Liu L Y.Wang J.H.Bao Y S.et al.Predicting Winter Wheat Condition,Grain Yield and Protein Content Using Multi-temporal EnviSat-ASAR and Landsat TM Satellite Images[J].International Journal of Remote Sensing,2006,27(4):737-753
    [143]Zhou Yi.Wang Shixin.Zhou Weiqi.et al.A New Approach to Identify Land Use and Land Cover Areas in Brazilian Amazon Areas using Neural Networks and IR-MSS Fraction Images from CBERS Satellite[A].IGARSS 04.Proceedings[C].2004.
    [144]Diverio V T.Formaggio A R.Shimabukuro Y E.Applications of CBERS-2 Image Data in Flood Disaster Remote Sensing Monitoring[A].IGARSS 03.Proceedings[C].2003.
    [145]罗亚 徐建华 岳文泽 等.植被指数在城市绿地信息提取中的比较研 究[J].遥感技术与应用,2006,21(3):212-219
    [146]赵萍 冯学智 林广发.SPOT卫星影响居民地信息自动提取的决策树方法研究[J].遥感学报,2003,7(4):309-315
    [147]Gitelson A A.Kaufman Y J.Robert S.et al.Novel Algorithms for Remote Estimation of Vegetation Fraction[J].Remote Sensing of Environment,2002,80:76-87.
    [148]Mohammad A A.Shi Z.Ahmad Y.et al.Application of GIS and Remote Sensing in Soil Degradation Assessments in the Syrian Coast[J].Journal of Zhejiang University(Agric.& Life Sci.),2002,26(2):191-196.
    [149]李苗苗 吴炳芳 颜长珍等.密云水库上游植被覆盖度的遥感估算[J].资源科学,2004,26(4):153-159
    [150]Goetz SJ.Wright R K.Smith A J.et al.IKONOS Imagery for Resource Management:Tree cover,Impervious Surfaces and Riparian Buffer Analyses in the Mid-Atlantic Region[J].Remote Sensing of Environment,2003,88:195-208.
    [151]孙丹峰 林培.自适应模糊规则分类方法及在TM土地覆盖分类中的应用研究[J].国土资源遥感,2002,(1):44-50.
    [152]Baatz et al.Cognition User Guide[Z].Munich:Defines Imaging GmBH,2002.
    [153]Van der Sande C J.et al.A Segmentation and Classification Approach of IKONOS-2 Imagery for Land Cover Mapping to Assist flood Risk and Flood Damage Assessment[J].International Journal of Applied Earth Observation and Geoinformation,2003,(4):217-229.

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700