基于遥感技术的棉田土壤质量评价研究
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摘要
新疆是我国主要的产棉区，棉田土壤质量及其评价对生产者和管理者具有重要的意义。本研究利用遥感技术对栅格数据的管理优势，将多时相棉田遥感信息中提取的NDVI等指标与实地获取的棉田理化数据相结合，探索棉田土壤属性信息迅速无损获取的理论依据和研究方法，构建基于遥感技术的棉田土壤质量评价指标体系，并进行评价和检验。拓展了遥感技术在棉田管理方面的应用领域和范围，为棉田管理的信息化提供了新的技术支持。
研究利用2009年至2011年的TM数据和HJ卫星数据以及数字化图件、田间实测数据，参考常规土壤质量评价的物理指标、化学指标、生物指标，结合研究区棉田植株生长发育的特点，运用遥感影像分析软件和地理信息系统处理平台，综合使用传统统计学方法、地统计方法、遥感影像处理方法等技术手段（监督分类、相关分析、主成分分析、矢量栅格相互转换等），对获取信息进行充分挖掘，筛选出适合评价棉田土壤质量的指标，构建基于遥感技术的棉田土壤质量评价指标体系，并对棉田土壤质量进行评价，主要研究结果如下：
一、通过多种遥感图像分析技术，实现了棉田基本信息的获取，为棉田土壤质量监测奠定了基础。利用不同作物种植类型及其生长发育特点在遥感监测信息上的差别，提取棉田种植区域和面积信息；结合裸土质地样点，实现棉田土壤质地的分类；通过DEM高程数据的分析获得棉田土壤地形状况；并将全国土壤图与研究区卫星数据校正叠加后，提取了研究区土壤类型数据。研究证明用国产遥感影像对棉田土壤质量评价物理指标的获取是可行、有效的。
二、研究分析了土壤养分空间变异性和棉花苗期至花铃期的生长状况，利用遥感获取的归一化植被指数NDVI进行密度分割。得到棉田长势分级图，研究表明该分级图能够揭示相应地区棉花的长势状况，并且与土壤有机质、碱解氮含量、速效钾含量、含量在51-63mg/kg范围的速效磷在空间布局上基本一致。根据多时相的NDVI数据能够得到长势持续增加的棉田，并以此作为判断集约化种植措施下棉田土壤质量的依据，为利用遥感技术对棉田土壤质量的监测和评价奠定了理论基础。
三、研究表明棉花产量形成关键生育时期的遥感监测指标——植被指数能够用于预测棉花产量，采用多时相指数对棉花产量空间布局进行反演的研究表明，遥感技术获取的植被指数，特别是比值植被指数（RVI）、归一化植被指数（NDVI），不仅与土壤有效氮、有机质等土壤养分具有显著的相关性，而且与棉花单铃重、单产、小区总产具有显著相关性。采用遥感多时相指数能够将棉花产量作为评价棉田土壤质量的关键指标之一，提高利用遥感技术评价棉田土壤质量的科学性和准确性。
四、研究构建了基于遥感技术的棉田土壤质量评价体系。该体系利用多时相遥感监测数据与棉花产量、棉田土壤理化性状的相关性，结合常用土壤养分关键指标，通过多种分析方法对棉田土壤质量进行了综合评价，初步构建的棉田土壤质量评价指标体系包括：1、物理指标：作物种植类型、土壤质地、土壤类型以及地形条件；2、化学指标：土壤有机质、碱解氮、速效磷、速效钾含量；3生物指标：棉田关键生育时期多时相植被指数、产量。实测数据的检验证实，本研究构建的基于遥感技术的棉田土壤质量评价体系具有快速、精确、便于管理的特点，适合大规模棉田信息化管理的需求。
Xinjiang is the major region of cotton production in China, It has great significance toevaluate the soil quality of cotton fields for producers and managers.This research take theadvantages of grid data management by remote sensing technology, combined with evaluationindex such as NDVI, which extracted by remote sensing technology, and a small amount ofphysical and chemical index of measuring point data. Research a quick, convenient andlossless method to obtain the soil attribute information of the cotton fields, using themulti-spectral remote sensing data to construct cotton soil quality evaluation index system,explore the application of remote sensing technology on cotton soil quality evaluation.
From2009to2011, TM data, HJ satellite data, digital maps, field measured data wereused; years study about soil evaluation indexes, include physical indicators, nutrientindicators, biological indicators in the study area were referenced; and remote sensing imageprocessing methods such as: supervised classification, correlation analysis, principalcomponent analysis, vector and raster conversion and other technical means were utilized,using geographical information system and remote sensing image analysis softwareprocessing platform to get information for cotton fields in soil quality evaluation index system,and to evaluate soil quality, the main research results are as follows:
(1) Achieved basic information of cotton field by different kinds of RS image analysismethods, establishes the foundation for monitoring cotton field’s soil quality. Study thedifference spectral information between various land use patterns and growing characteristics,and extract information about position and area of cotton field in study area; use real samplesto classified the soil texture; obtain the topography information by DEM data; and gain thesoil type classification by layer-stacking the National Soil map and remote sensing image ofstudy area. The conclusion is that it is feasible and effective to extract physical indicators ofcotton soil quality evaluation by indigenous satellite.
(2) Study the space distribution of soil fertility and the growing condition of crops, findout that: the normalized difference vegetation index NDVI classification map is obtained bydensity slicing can reveal the corresponding region of cotton growing conditions, and soilorganic matter, alkali-hydro nitrogen, rapidly-available potassium content, content of51-63mg/kg on the range of available P2O5in the spatial layout are basically identical.Multi-temporal NDVI data can reveal the growing situation of cotton field and it can be aaccording to evaluate the soil quality, meanwhile, it laying a good theory foundation formonitoring and evaluating soil quality.
(3) It is concluded that: the key period of cotton growing for production can implyimportant information to predicted yield. Using Multi-temporal vegetation index and somesample data to achieve inversion model. Results shows that: vegetation index, especially theratio vegetation index(RVI) and normalization vegetation index (NDVI), are not only haverelationships with soil nutrient such as available nitrogen, soil organic matter, but also hassignificant correlation with cotton single boll weight, yield and total output of residential area.It will become one of the most important indexes to evaluate cotton field soil quality, andimprove the scientificalness and veracity of the evaluation.
(4) Structure the cotton Soil quality evaluation indicator system, tentatively. The systemmake use of the relationship between multi-temporal remote sensing, cotton yield, and soilphysical and chemical properties, comprehensive utilization of soil fertility index, use variedanalysis method evaluated the cotton soil quality. The evaluation index system including:1,physical indexes: land use type, soil texture, soil type and topography conditions;2, nutrientindexes: soil organic matter, alkali solution nitrogen, available phosphorus, availablepotassium content;3, biological indicators: key growth period long, vegetation index, thecotton yield. It also test and verify that the indicator system is rapid, accurate and manageablewhen evaluating and it will be appropriate for informatization management of cotton field.
研究利用2009年至2011年的TM数据和HJ卫星数据以及数字化图件、田间实测数据，参考常规土壤质量评价的物理指标、化学指标、生物指标，结合研究区棉田植株生长发育的特点，运用遥感影像分析软件和地理信息系统处理平台，综合使用传统统计学方法、地统计方法、遥感影像处理方法等技术手段（监督分类、相关分析、主成分分析、矢量栅格相互转换等），对获取信息进行充分挖掘，筛选出适合评价棉田土壤质量的指标，构建基于遥感技术的棉田土壤质量评价指标体系，并对棉田土壤质量进行评价，主要研究结果如下：
一、通过多种遥感图像分析技术，实现了棉田基本信息的获取，为棉田土壤质量监测奠定了基础。利用不同作物种植类型及其生长发育特点在遥感监测信息上的差别，提取棉田种植区域和面积信息；结合裸土质地样点，实现棉田土壤质地的分类；通过DEM高程数据的分析获得棉田土壤地形状况；并将全国土壤图与研究区卫星数据校正叠加后，提取了研究区土壤类型数据。研究证明用国产遥感影像对棉田土壤质量评价物理指标的获取是可行、有效的。
二、研究分析了土壤养分空间变异性和棉花苗期至花铃期的生长状况，利用遥感获取的归一化植被指数NDVI进行密度分割。得到棉田长势分级图，研究表明该分级图能够揭示相应地区棉花的长势状况，并且与土壤有机质、碱解氮含量、速效钾含量、含量在51-63mg/kg范围的速效磷在空间布局上基本一致。根据多时相的NDVI数据能够得到长势持续增加的棉田，并以此作为判断集约化种植措施下棉田土壤质量的依据，为利用遥感技术对棉田土壤质量的监测和评价奠定了理论基础。
三、研究表明棉花产量形成关键生育时期的遥感监测指标——植被指数能够用于预测棉花产量，采用多时相指数对棉花产量空间布局进行反演的研究表明，遥感技术获取的植被指数，特别是比值植被指数（RVI）、归一化植被指数（NDVI），不仅与土壤有效氮、有机质等土壤养分具有显著的相关性，而且与棉花单铃重、单产、小区总产具有显著相关性。采用遥感多时相指数能够将棉花产量作为评价棉田土壤质量的关键指标之一，提高利用遥感技术评价棉田土壤质量的科学性和准确性。
四、研究构建了基于遥感技术的棉田土壤质量评价体系。该体系利用多时相遥感监测数据与棉花产量、棉田土壤理化性状的相关性，结合常用土壤养分关键指标，通过多种分析方法对棉田土壤质量进行了综合评价，初步构建的棉田土壤质量评价指标体系包括：1、物理指标：作物种植类型、土壤质地、土壤类型以及地形条件；2、化学指标：土壤有机质、碱解氮、速效磷、速效钾含量；3生物指标：棉田关键生育时期多时相植被指数、产量。实测数据的检验证实，本研究构建的基于遥感技术的棉田土壤质量评价体系具有快速、精确、便于管理的特点，适合大规模棉田信息化管理的需求。
Xinjiang is the major region of cotton production in China, It has great significance toevaluate the soil quality of cotton fields for producers and managers.This research take theadvantages of grid data management by remote sensing technology, combined with evaluationindex such as NDVI, which extracted by remote sensing technology, and a small amount ofphysical and chemical index of measuring point data. Research a quick, convenient andlossless method to obtain the soil attribute information of the cotton fields, using themulti-spectral remote sensing data to construct cotton soil quality evaluation index system,explore the application of remote sensing technology on cotton soil quality evaluation.
From2009to2011, TM data, HJ satellite data, digital maps, field measured data wereused; years study about soil evaluation indexes, include physical indicators, nutrientindicators, biological indicators in the study area were referenced; and remote sensing imageprocessing methods such as: supervised classification, correlation analysis, principalcomponent analysis, vector and raster conversion and other technical means were utilized,using geographical information system and remote sensing image analysis softwareprocessing platform to get information for cotton fields in soil quality evaluation index system,and to evaluate soil quality, the main research results are as follows:
(1) Achieved basic information of cotton field by different kinds of RS image analysismethods, establishes the foundation for monitoring cotton field’s soil quality. Study thedifference spectral information between various land use patterns and growing characteristics,and extract information about position and area of cotton field in study area; use real samplesto classified the soil texture; obtain the topography information by DEM data; and gain thesoil type classification by layer-stacking the National Soil map and remote sensing image ofstudy area. The conclusion is that it is feasible and effective to extract physical indicators ofcotton soil quality evaluation by indigenous satellite.
(2) Study the space distribution of soil fertility and the growing condition of crops, findout that: the normalized difference vegetation index NDVI classification map is obtained bydensity slicing can reveal the corresponding region of cotton growing conditions, and soilorganic matter, alkali-hydro nitrogen, rapidly-available potassium content, content of51-63mg/kg on the range of available P2O5in the spatial layout are basically identical.Multi-temporal NDVI data can reveal the growing situation of cotton field and it can be aaccording to evaluate the soil quality, meanwhile, it laying a good theory foundation formonitoring and evaluating soil quality.
(3) It is concluded that: the key period of cotton growing for production can implyimportant information to predicted yield. Using Multi-temporal vegetation index and somesample data to achieve inversion model. Results shows that: vegetation index, especially theratio vegetation index(RVI) and normalization vegetation index (NDVI), are not only haverelationships with soil nutrient such as available nitrogen, soil organic matter, but also hassignificant correlation with cotton single boll weight, yield and total output of residential area.It will become one of the most important indexes to evaluate cotton field soil quality, andimprove the scientificalness and veracity of the evaluation.
(4) Structure the cotton Soil quality evaluation indicator system, tentatively. The systemmake use of the relationship between multi-temporal remote sensing, cotton yield, and soilphysical and chemical properties, comprehensive utilization of soil fertility index, use variedanalysis method evaluated the cotton soil quality. The evaluation index system including:1,physical indexes: land use type, soil texture, soil type and topography conditions;2, nutrientindexes: soil organic matter, alkali solution nitrogen, available phosphorus, availablepotassium content;3, biological indicators: key growth period long, vegetation index, thecotton yield. It also test and verify that the indicator system is rapid, accurate and manageablewhen evaluating and it will be appropriate for informatization management of cotton field.
引文
[1]赵其国,孙波,张桃林.土壤质量与持续环境Ⅰ.土壤质量的定义及评价方法.土壤,1997(3):113-120.
[2]张国印.河北平原土壤质量评价指标和方法初探[硕士论文].北京:中国农业大学,2005.
[3]魏娜,姚艳敏,陈佑启.高光谱遥感土壤质量信息监测研究进展.中国农学通报.2008.24(10)491-496.
[4] Sumfleth K,Duttmann R.Prediction of soil property distribution in paddy soil landscapes using terraindata and satellite information as indicators.Ecological Indicators,2008,8(5):485-501.
[5]徐建明,张甘霖,谢正苗,吕晓男.土壤质量指标与评价.北京:科学出版社,2010.
[6]郑昭佩,刘作新.土壤质量及其评价.应用生态学报,2003,14(1):131-134.
[7] Doran J W,Parkin T B.Defining and assessing soil quality.Soil Science Society of American Publication.1994b(35):3-21.
[8] Karien D L,Maudbach M J,Doran J W,et al. Soil Quality:a concept, definition,and framework forevaluation (A guest editorial).Soil Science Society of American Journal,1997(61):4-10.
[9]徐建明,汪海珍.土壤质量指标及评价体系研究进展.中国土壤学会:面向农业与环境的土壤科学（综述篇）.北京:科学出版社,2004.
[10]刘世梁,傅伯杰,陈利顶,丘君,吕一河.两种土壤质量变化的定量评价方法比较.长江流域资源与环境,2003,12(5):422-426.
[11]刘世梁,傅伯杰,吕一河,陈利顶,马克明.坡面土地利用方式与景观位置对土壤质量的影响.生态学报,2006,23(3):414-419.
[12]张贞,魏朝富,高明,邵景安,秦建成.土壤质量评价方法进展.土壤通报,2006,37(5):999-1006.
[13] Larson W.E.and F.J.Pierce.1991.Conservation and enhancement of soil quality.In evaluation forsustainable land management in the developing world.VoL2.ISBRAM Proc.12(2).Int Board for SoilRes And Management.Bangkok,Thailand．IBSRAM proceedings:75-203.
[14]蔡崇法,丁树文,史志华,王天巍.GIS支持下乡镇域土壤肥力评价与分析.土壤与环境,2000,9(2):99-102.
[15]颜雄,张杨珠,刘晶.土壤肥力质量评价的研究进展.湖南农业科学,2008,(5):82-85.
[16]崔玉顺,章熙谷.南方红壤地区水稻土的肥力评价.自然资源学报,1994,9(4):341-349.
[17]郑立臣,宇万太,马强,王永宝.农田土壤肥力综合评价研究进展.生态学杂志,2004,23(5):156-161.
[18]骆东齐,白洁,谢德体.论土壤肥力评价指标和方法.土壤与环境,2002,11(2):202-205.
[19]宋苏苏.土壤肥力评价方法研究[硕士论文].西安:西北农林科技大学,2011.
[20] Arshad M A,Coen G M.Characterization of soil quality:physical and chemical criteria.Am.J.Altern.Agric.1992,7:25-31.
[21] Larson W E,Pierce F J.Conservation and enhancement of soil quality.In Proc.Of the lnt.Workshop onevaluation for sustainable land management in the developing world.International Board for SoilResource and Management (IBSRAM).Proceeding no.123vol.2.Bangkok,Thailand,1991.
[22]吕新,寇金梅,李宏伟.模糊评判方法在土壤肥力综合评价中的应用研究.干旱地区农业研究,2004,22(3):56-59.
[23]李明悦.近20年来大同市土壤肥力质量的时空演化分析[硕士论文].北京:中国农业大学,2005.
[24]李双异,刘慧屿,张旭东,王秋兵,温礼,边振兴,迟凤琴,汪景,宽东.北黑土地区主要土壤肥力质量指标的空间变异性.土壤通报,2006,37(2):220-225.
[25]马媛,龚新梅,塔西甫拉提·特依拜,吕光辉.干旱区典型流域土壤肥力空间变异特征.生态学杂志,2006,25(10):1208-1213.
[26]张慧文.雅玛里克山污水灌溉区土壤肥力的空间变异规律研究[硕士论文].乌鲁木齐:新疆大学,2006.
[27]王博文,潘华,岳中辉,王洪峰,阎秀峰.不同盐碱化程度草地土壤肥力质量的季节动态特征.东北林业大学学报,2009,37(4):132-139.
[28]翟辉.湘西不同植被对土壤肥力质量的效应研究[硕士论文].长沙:湖南农业大学,2010.
[29]刘文杰,苏永忠,陈生云,杨荣,王雪峰,范桂萍.临泽绿洲农田土壤肥力量时空变化特征.中国沙漠,2012,32(1):132-139.
[30] McEweu M J.Considerations in determining soil quality and a conceptual strategy for the appraisal,maintenance and improvemrnt of soil quality.The evolution of herbicide resistance.http://www.phasm.co.uk,2004.
[31] Steinborn W,Svirezhev Y.Entropy as an indicator of sustainability in agro-ecosystems:North Germanycase study.Ecological Modelling,2000,133(3):247-257.
[32] Conry M J,Clinch P.The effect of soil quality on the yield class of a range of forest species grown onthe Slieve Bloom Mountain and foothills. Forestry,1989,62.397-407.
[33] Boehm M M,AndeersonD W.A landscape-scales study of soil quality in three Prairie farming systems.Soil Sci. Soc.Am.J,1997,61:1147-1159.
[34]孔祥斌,刘灵伟,秦静.基于农户行为的耕地质量评价指标体系构建的理论与方法.地理科学进展,2007,26(4):75-85.
[35]万存绪,张效勇.模糊数学在土壤质量评价中的应用.应用科学学报,1991,9(6):359-365.
[36]王效举,龚子同.红壤丘陵小区域水平上不同时段土壤质量变化的评价和分析.地理科学,1997,17(2):141-149.
[37] Fu B J,Liu S L,Chen L D,et al.Comparing the soil quality changes of different land uses determined bytwo quantitative methods.Journal of Environmental Sciences,2003,15(2):167-172.
[38]王军艳,张凤荣,王茹,贾小红,张彩月.2001.应用指数和法对潮土农田土壤肥力变化的评价研究.农村生态环境,17(3):13-16.
[39]马强,宇万太,赵少华,张璐,沈善敏,王永宝.黑土农田土壤肥力质量综合评价.应用生态学报,2004,15(10):1916-1920.
[40]胡月明,吴谷丰,江华,张馨远,徐剑波,李兴华.基于GlS与灰关联综合评价模型的土壤质量评价.西北农林科技大学学报(自然科学版),29(4):39-42.
[41]吴红玉,田霄鸿,侯永辉,周密,同延安.基于田块尺度的土壤肥力模糊评价研究.自然资源学报,2009.24(8):1422-1431.
[42]张庆利,潘贤章,王洪杰,刘付程,史学正.中等尺度上土壤肥力质量的空间分布研究及定量评价.土壤通报,2003,34(6):493-497.
[43]肖慈英,阮宏华,屠六邦.下蜀主要森林土壤肥力的灰色关联分析与评价.南京林业大学学报（自然科学版）2000.
[44] Andrew J C,Burton A M,M Paul,Andrew W Y,Shigeru A.2001.A principal component analysis offacial expressions.Vision Research.41:1179-1208.
[45] Hou W G,Jiang SC, Xiong S Q,et al.Evaluation of soil quality based on G1S. Geomatics andinformation Science of Wuhan University,2003,28(1):60-64.
[46]张庆利,史学正,潘贤章,于东升,刘付程.江苏省金坛市土壤肥力的时空变化特征.土壤学报,2004,41(2):315-319.
[47]张华,张甘霖,漆智平,赵玉国.热带地区农场尺度土壤质量现状的系统评价.土壤学报,2003,40(2):186-193.
[48]谢伯承.基于高光谱遥感不同发生层土壤的光谱信息提取研究.陕西杨凌:西北农林科技大学,2004.
[49] He Yong,Song Haiyan, Annia G P.A new approach to predict N, P, K and OM content in a loamymixed soil by using near infrared reflectance spectroscopy.Lecture Notes in Computer Science,2005,3644:859-867.
[50] Ben Dor E,Bania A.Soil Science Society of America Journal.1995,59:364.
[51]曾志远.土壤肥力的卫星遥感探测.土壤,1987,(2):72,73-78.
[52]祁亚琴.基于高光谱遥感数据提取农田土壤特征信息的研究[博士论文].石河子:石河子大学,2011.
[53] Hunt G R,Salisbury J W.Visible and near infrared spectra of minerals and rocks,I,Silicate Minerals.Mod.Geol,1970(1)283-300.
[54]徐彬彬,戴昌达.南疆土壤光谱反射特性与有机质含量的相关性分型科学通报.1980,282-284.
[55]程彬,姜琦刚.遥感影像在土壤属性估算中的应用.中国农学通报,2008,24(1):467-470.
[56]程彬,姜琦刚,陈凤臻,张红红,崔翰文.松辽平原黑土有机质含量的遥感反演研究水土保持研究,2011,8(1):264-267.
[57]梅安新,彭望碌,秦其明,刘慧平.遥感导论.北京:高等教育出版社,2001.
[58]赵英时.遥感应用分析原理与方法.北京:科学出版社,2003.
[59] Webster R.Statistics to support soil research and their presentation.European Journal of Soil Science,2001,52:331-340.
[60]沙晋明,利用土壤黑度值实现土壤肥力遥感监测机理.山西农业大学学报,1996,16(4):372-376.
[61]张法升,曲威,尹光华,刘作新.基于多光谱遥感影像的表层土壤有机质空间格局反演.应用生态学报,2010,21(4):883-888.
[62] Ben-Dor E,Patkin K, Banin A,et al.Mapping of several soil properties using DAIS-7915hyperspectralscanner data-a case study over clayey soils in Israel. International Journal of Remote Sensing,2002,23(6):1043-1062.
[63] Bowers S,Hanks R J.Reflectance of radiant energy from soil.Soil Sci.,1965,100:130-138.
[64] Baumgardner M F,Kristoff S J,Johannsen C J.The effect of organic matter on multi-spectral propertiesof soils.Proc Indiana Acad Sci,1970,79:413-422.
[65] Al-Abbas A H,Swain P H,Baumgardner M F.Relating soil organic matter and clay content to themulti-spectral radiance.Soil Sci,1972,114:477-485.
[66] Garey A. Fox,George J.Sabbagh.Estimation of soil organic matter from red and near-infrared remotelysensed data using a soil line Euclidean Distance Technique.Soil Sci Soc Am J,2002,66:1922-1929.
[67] Chen F, Kissell D E,West L T,et al.Field-scale mapping of surface soil organic carbon using remotelysensed imagery.Soil Sci Soc Am J,2000,64:746-753.
[68] Frazier B E,and Cheng Y.Remote sensing of soils in the eastern palouse region with landsat thematicmapper.Remote Sensing of Environment,1989,28:317-325.
[69]潘瑜春,王纪华,陆安祥,陆洲.基于小麦长势遥感监测的土壤氮素累积估测研究.农业工程学报,2007,23(9):58-63.
[70]陈蓉蓉,周治国,曹卫星,戴延波.基于GIS的农田土壤、作特征空间变异性及其相互关系.应用生态学报,2004,15(9):1678-1680.
[71]张素梅,王宗明,张柏,宋开山,刘殿伟,李方,任春颖,黄健,张惠琳.利用地形和遥感数据预测土壤养分空间分布.农业工程学报,2010,26(5):188-194.
[72]潘剑君,刘世峰,赵美芳.遥感估测土壤元素技术体系建立的研究初探——以溧水水田土壤全氮为例中国土壤与肥料.2010,4:18-23.
[73]李欣宇,宇万太,李秀珍.遥感与地统计方法在表层土壤有机碳空间格局研究中的应用比较.农业工程学报,2009,25(3):148-152.
[74]潘文超,李少昆,王克如,肖华,陈兵,王方永,苏毅,陈江鲁,赖军臣,黄芳德.基于棉花冠层光谱的土壤氮素监测研究.棉花学报,2010,22(1):70-76.
[75]陈兵,李少昆,王克如,柏军华,随学艳,白彩云.作物病虫害遥感监测研究进展.棉花学报,2007,19(1):57-63.
[76] CHEN F, Kissel D E, West L T, et al.Mapping surface soil organic carbon for crop fields with remotesensing.Journal of soil and water conservation,2005,60(1):51-57.
[77] SULLIVAN D, Shaw J N, Rickman D. IKONOS imagery to estimate surface soil property variabilityin two Alabama physiographies Soil Science Society of America Journal,2005,69(6):1789-1798.
[78]陈玉福,董鸣.毛乌素沙地景观的植被与土壤特征空间格局及其相关分析.植物生态学报,2001,25(3):265-269.
[79]柏军华.棉田管理信息的遥感提取研究[博士论文].北京:中国农业科学院,2009.
[80]宋晓宇,王纪华,刘良云,黄文江,沈涛,喻铮铮.基于Quickbird遥感影像的农田管理分区划分研究.中国农业科学,2007,40(9):1996-2006.
[81]谭昌伟.稻麦主要调优栽培指标的遥感监测研究[博士论文].扬州:扬州大学,2010.
[82]王来刚,王备战,冯伟,郑涛,冯晓,郑国清. SPOT-5与HJ遥感影像用于冬小麦氮素监测的效果对比.麦类作物学报.2011,31(2):331-336.
[83]刘世峰,潘剑君,杨志强,胡若婧,刘莎.利用中巴-2号卫星CCD估测土壤全氮的研究.遥感应用,2010,1:57-63.
[84] Levine E R,Ranson K J,Smith I,et al.Forest ecosystem dynamics: linking forest succession,soilprocess,and radiation models.Ecological Modeling,1993,65:199-219.
[85] Lydia Serrano,Iolanda Filella,Josep Penuelas. Remote sensing of biomass and yield of winter wheatunder different nitrogen supplies.Crop Science,2000,40:723-731.
[86] Wright D L,Rasmussen V P,Baker D J.Using remote sensing to manage wheat grain protein.NASASSC Report,2003, ARC-USU-001-02.
[87] NUMATA I,Soares J V,Roberts D A,et al.Relationships among soil fertility dynamics and remotelysensed measures across pasture chronosequences in Rondonia,Brazil. Remote Sensing of Environment,2003.87(4):446-455.
[88] Michael Flowers,Randall Weisz,Ronnie Heiniger. Remote sensing of winter wheat tiller density forearly nitrogen application decisions.Agron J,2001,93:783-789.
[89] Michael Flowers,Randall Weisz,Ronnie Heiniger,et al.Field validation of a remote sensing techniquefor early nitrogen application decisions in wheat.Agron J,2003,95:167-176.
[90] Wenjiang Huang,Jihua Wang,Zhijie Wang,et al.Inversion of foliar biochemical parameters at variousphysiological stages and grain quality indicators of winter wheat with canopy reflectance.International Journal of Remote Sensing,2004,25(12):2409-2419.
[91] Chunjiang Zhao,Liangyun Liu, Jihua Wang, et al. Predicting grain protein content of winter wheatusing remote sensing data based on nitrogen status and water stress. International Journal of AppliedEarth Observation and Geoinformation,2005,7(1):1-9.
[92] Chunjiang Zhao,Jihua Wang,Liangyun Liu,et al.Relationship of2100-2300nm spectral characteristicsof wheat canopy to leaf area index and leaf N as affected by leaf water content. Pedosphere,2006,16(3):333-338.
[93] Liangyun Liu,Jihua Wang,Yansong Bao,et al.Predicting winter wheat condition,grain yield and proteincontent using Multi-temporal EnviSat-ASAR and Landsat TMsatellite images.International Journal ofRemote Sensing,2006,27(4):737-753.
[94] Puzachenko Y G,Kozlov D N,Siunova E V,et al.Assessment of the reserves of organic matter in theworld＇s soils:Methodology and results.Eurasian Soil Science,2006,39(12):1284-1296.
[95] Takata Y,Funakawa S,Akshalov K,et al.Spatial prediction of soil organic matter in northernKazakhstan based on topographic and vegetation information.Soil Science and Plant Nutrition,2007,53(3):289-299.
[96] Takata Y,Funakawa S,Akshalov K,et al.Regional evaluation of the spatial-temporal variation in soilorganic carbon dynamics for rain-fed cereal farming in northern Kazakhstan.Soil Science and PlantNutrition,2008,54(5):794-806.
[97] Verhulst N,Govaerts B,Sayre K D,et al.Using NDVI and soil quality analysis to assess influence ofagronomic management on with-in-plot spatial variability and factors limiting production.Plant andSoil,2009,317(1-2):41-59.
[98] Leon C T,Shaw D R,Cox M S,et al.Utility of remote sensing in predicting crop and soil characteristics.Precision Agriculture.2003(4):359-384
[99]韩爱惠.用MODIS数据监测京津塘风沙源工程区植被指数的选择及合成.国土资源遥感,2004,3:54-56.
[100] Jordan C F.Derivation of leaf-area index from quality of light on the forest floor.Ecology,1969,50:663-666.
[101] Richardson A J,Wiegand C L.Distinguishing vegetation from soil background information.Photogrammetric Engineering and Remote Sensing,1977,43(12):1541-1552.
[102] SULLIVAN D G,Shaw J N,Rickman D.IKONOS imagery to estimate surface soil propertyvariability in two Alabama physiographies soil.Science Society of America Journal,2005,69(6):1789-1798.
[103]宋晓宇,王纪华,薛绪掌,刘良云,陈立平,赵春江.利用航空成像光谱数据研究土壤供氮量及变量施肥对冬小麦长势影响.农业工程学报,2004,20(4):45-49.
[104]卢艳丽,白由路,王磊,王贺,杨俐苹.黑土土壤中全氮含量的高光谱预测分析.农业工程学报,2010,26(1):256-261.
[105]曾志远.卫星图象密度-辐射量算与土壤资源探测.资源科学,1981(4):72-78.
[106]吕新.3S技术在精准农业中的应用.北京:中国科学文化出版社,2007,9.
[107]张竞成,顾晓鹤,王纪华,黄文江,何馨,王慧芳.基于HJ-CCD与TM影像的水稻LAI估测一致性分析.农业工程学报,2010,26(7):186-193.
[108]环境保护部卫星环境应用中心网站http://60.247.54.34/secPortal/portal/index.faces.
[109]邓书斌.ENVI遥感图像处理方法.科学出版社,北京:2010
[110]高建峰.辅以ETM+的MODIS影象土地利用变化监测及土壤有机碳库估算研究一一以吴江市为例[博士论文].南京:南京农业大学,2007.
[111]朱述龙.区域的深度计算及其在图像渐变处理中的应用.中国图像图形学报.2000,5(9):734-738.
[112]张芳.基于遥感技术的干旱区湿地信息提取方法研究[硕士论文].乌鲁木齐:新疆大学,2008.
[113] Xu L,Hou L C,Yang Q,Zhang Z,Jin Z L.Study on optimum band in land use/land cover informationextraction using TM image. Journal of Hubei University (Natural Science),2011,33(1):119-122.
[114] Institute of Soil Science,CAS.Physical and chemical analysis of soil.Shanghai:Shanghai Science andTechnology Press,1978.
[115]李卫国,李花,王纪华,黄文江.基于Landsat/TM遥感的冬小麦长势分级监测研究.麦类作物学报,2010,30(1):92-95.
[116]冉琼,迟耀斌,王智勇,陈正超.北京1号小卫星图像噪声评估.遥感学报,2009,13(3):554-558.
[117]唐华俊,吴文斌,杨鹏,周清波,陈仲新.农作物空间格局遥感监测研究进展.中国农业科学,2010,43(14):2879-2888.
[118]许菡,燕琴,徐泮林.多源遥感影像融合最佳波段选择及质量评价研究.测绘科学,2007,2(3):72-74,87.
[119]张若琳,万力,张发旺,石迎春.土地利用遥感分类方法研究进展.南水北调与水利科技,2006,4(2):39-42.
[120] Bertsch P M,Thomas G W.Potassium stassium of temperate region soils. In:Munson R E.Potassium inagriculture. Madison:American Society of Agronomy.1985,131-162.
[121]胡克林,李保国,林启美,李贵桐,陈德立.农田土壤养分的空间变异性特征.农业工程学报,1999,15(3):33-38.
[122]陈彦,吕新.基于GIS和地统计学的土壤养分空间变异特征研究—以新疆农七师125团为例.中国农学通报,2005,21(7):389-391,405.
[123] Stark C H,Condron L M,Stewart A.Small-scale Spatial variability of selected soil biologicalproperties.Soil Biology and Biochemistry,2004,36(4):601-608.
[124] Corre M D,Schnabel,Stout R.Spatial and seasonal variation of gross nitrogen transformations andmicrobial biomass in a northeastern US grassland.Soil Biology and Biochemistry,2002,34:445-457.
[125] Alex B,McBratney,Inakwu O.A.Odeh,Thomas F.A. Bishop, Marian S.Dunbar,Tamara M.Shatar.Anoverview of pedometric techniques for use in soil survey. Geoderma,2000,97(3):293-327.
[126] Sumfleth K,Duttmann R.Prediction of soil property distribution in paddy soil landscapes using terraindata and satellite information as indicators. Ecological Indicators,2008,8(5):485-501.
[127]杨玉玲,田长彦,盛建东.棉田土壤有机质、全氮、全钾全磷空间变异分析.干旱地区农业研究,2002,3:26-30.
[128]李晓燕,张树文,王宗明,张惠琳.吉林省德惠市土壤特性空间变异特征与格局.地理学报,2004,59(6):989-997.
[129]郭旭东,傅伯杰,陈立顶,马克明,李俊然.河北省遵化平原土壤养分的时空变异特征——变异函数与Kriging插值分析.地理学报,2000,55(5):555-566.
[130]李海滨,林忠辉,刘苏峡.Kriging方法在区域土壤水分估值.地理研究,2001,20(4):446-452.
[131]石小华,杨联安,张蕾.土壤速效钾养分含量空间插值方法比较.水土保持学报,2006.20(2):68-72.
[132] Combardella C A,Moorman T B,Novak J M,Parkin T B,Karlen D L,Turco R F,Konopka A E.Field-scale variability of soil properties in central Iowa soils.Soil Science Society of America journal,1994,58:1501-1511.
[133]郭胜利,刘文兆,史竹叶,侯喜禄,李凤民.半干旱区流域土壤养分分布特征极其与地形、植被的关系.干早地区农业研究,2003,21(4):40-43.
[134] Sullivan D q Shaw J N,Rickman D.IKONOS imagery to estimate surface soil property variability intwo Alabama physiographies. Soil Science Society of America Journal,2005,69(6):1789-1798.
[135]裴志远,杨邦杰.多时相归一化植被指数NDVI的时空特征提取与作物长势模型设计.农业工程学报,2000,16(5):20-22.
[136]阎晓娟.田块尺度作物长势与空间变异遥感监测研究[硕士论文].西安:西安科技大学,2008.
[137]陈兵.基于多平台棉花黄萎病的遥感监测研究[博士论文].石河子:石河子大学,2010.
[138]蒋桂英.新疆棉花主要栽培生理指标的高光谱定量提取与应用研究[博士论文].石河子:石河子大学,2004.
[139]刘世梁,傅伯杰,刘国华,马克明.我国土壤质量及其评价研究的进展.土壤通报,2006,1:137-143.
[140]周勇,李学垣,贺纪正,王庆云,刘勇.ARC/INFO信息系统在农地分等定级中的应用.土壤学报,1998,35(4):450-460.
[141]吴玉红,田霄鸿,同延安,南雄雄,周密,侯永辉.基于主成分分析的土壤肥力综合指数评价.生态学杂志,2010,29(1):173-180.
[142]王玲.基于GIS和RS的干旱区绿洲耕地质量评价方法及应用研究[博士论文].石河子:石河子大学,2011.
[143]苗军.基于GIS的最佳选点区域研究[硕士论文].昆明:昆明理工大学,2009,4.
[144]王瑞燕,赵庚星,陈丽丽.基于ANN-产量的耕地地力定量评价模型及其应用.农业工程学报,2008,24(l):113-118.
[145]柏军华,李少昆,李静,王克如,谢瑞芝,高世菊,陈兵,王方永,刘国庆,谭海珍.基于多时相棉花长势遥感的棉田质量诊断.中国农业科学,2008,41(4):1003-1011.
[146]严红萍,俞兵.主成分分析在遥感图像处理中的应用.资源环境与工程.2006,20(2):168-170.
[147]李梅,张学雷,武继承.GIS支持下豫东地区土壤野外采样布点方法探索.土壤,2011,43(3):459-465.
[148]范君华,刘明.新疆绿洲棉田土壤质量演变规律分析.中国棉花,2011,38(7):31-34.
[2]张国印.河北平原土壤质量评价指标和方法初探[硕士论文].北京:中国农业大学,2005.
[3]魏娜,姚艳敏,陈佑启.高光谱遥感土壤质量信息监测研究进展.中国农学通报.2008.24(10)491-496.
[4] Sumfleth K,Duttmann R.Prediction of soil property distribution in paddy soil landscapes using terraindata and satellite information as indicators.Ecological Indicators,2008,8(5):485-501.
[5]徐建明,张甘霖,谢正苗,吕晓男.土壤质量指标与评价.北京:科学出版社,2010.
[6]郑昭佩,刘作新.土壤质量及其评价.应用生态学报,2003,14(1):131-134.
[7] Doran J W,Parkin T B.Defining and assessing soil quality.Soil Science Society of American Publication.1994b(35):3-21.
[8] Karien D L,Maudbach M J,Doran J W,et al. Soil Quality:a concept, definition,and framework forevaluation (A guest editorial).Soil Science Society of American Journal,1997(61):4-10.
[9]徐建明,汪海珍.土壤质量指标及评价体系研究进展.中国土壤学会:面向农业与环境的土壤科学（综述篇）.北京:科学出版社,2004.
[10]刘世梁,傅伯杰,陈利顶,丘君,吕一河.两种土壤质量变化的定量评价方法比较.长江流域资源与环境,2003,12(5):422-426.
[11]刘世梁,傅伯杰,吕一河,陈利顶,马克明.坡面土地利用方式与景观位置对土壤质量的影响.生态学报,2006,23(3):414-419.
[12]张贞,魏朝富,高明,邵景安,秦建成.土壤质量评价方法进展.土壤通报,2006,37(5):999-1006.
[13] Larson W.E.and F.J.Pierce.1991.Conservation and enhancement of soil quality.In evaluation forsustainable land management in the developing world.VoL2.ISBRAM Proc.12(2).Int Board for SoilRes And Management.Bangkok,Thailand．IBSRAM proceedings:75-203.
[14]蔡崇法,丁树文,史志华,王天巍.GIS支持下乡镇域土壤肥力评价与分析.土壤与环境,2000,9(2):99-102.
[15]颜雄,张杨珠,刘晶.土壤肥力质量评价的研究进展.湖南农业科学,2008,(5):82-85.
[16]崔玉顺,章熙谷.南方红壤地区水稻土的肥力评价.自然资源学报,1994,9(4):341-349.
[17]郑立臣,宇万太,马强,王永宝.农田土壤肥力综合评价研究进展.生态学杂志,2004,23(5):156-161.
[18]骆东齐,白洁,谢德体.论土壤肥力评价指标和方法.土壤与环境,2002,11(2):202-205.
[19]宋苏苏.土壤肥力评价方法研究[硕士论文].西安:西北农林科技大学,2011.
[20] Arshad M A,Coen G M.Characterization of soil quality:physical and chemical criteria.Am.J.Altern.Agric.1992,7:25-31.
[21] Larson W E,Pierce F J.Conservation and enhancement of soil quality.In Proc.Of the lnt.Workshop onevaluation for sustainable land management in the developing world.International Board for SoilResource and Management (IBSRAM).Proceeding no.123vol.2.Bangkok,Thailand,1991.
[22]吕新,寇金梅,李宏伟.模糊评判方法在土壤肥力综合评价中的应用研究.干旱地区农业研究,2004,22(3):56-59.
[23]李明悦.近20年来大同市土壤肥力质量的时空演化分析[硕士论文].北京:中国农业大学,2005.
[24]李双异,刘慧屿,张旭东,王秋兵,温礼,边振兴,迟凤琴,汪景,宽东.北黑土地区主要土壤肥力质量指标的空间变异性.土壤通报,2006,37(2):220-225.
[25]马媛,龚新梅,塔西甫拉提·特依拜,吕光辉.干旱区典型流域土壤肥力空间变异特征.生态学杂志,2006,25(10):1208-1213.
[26]张慧文.雅玛里克山污水灌溉区土壤肥力的空间变异规律研究[硕士论文].乌鲁木齐:新疆大学,2006.
[27]王博文,潘华,岳中辉,王洪峰,阎秀峰.不同盐碱化程度草地土壤肥力质量的季节动态特征.东北林业大学学报,2009,37(4):132-139.
[28]翟辉.湘西不同植被对土壤肥力质量的效应研究[硕士论文].长沙:湖南农业大学,2010.
[29]刘文杰,苏永忠,陈生云,杨荣,王雪峰,范桂萍.临泽绿洲农田土壤肥力量时空变化特征.中国沙漠,2012,32(1):132-139.
[30] McEweu M J.Considerations in determining soil quality and a conceptual strategy for the appraisal,maintenance and improvemrnt of soil quality.The evolution of herbicide resistance.http://www.phasm.co.uk,2004.
[31] Steinborn W,Svirezhev Y.Entropy as an indicator of sustainability in agro-ecosystems:North Germanycase study.Ecological Modelling,2000,133(3):247-257.
[32] Conry M J,Clinch P.The effect of soil quality on the yield class of a range of forest species grown onthe Slieve Bloom Mountain and foothills. Forestry,1989,62.397-407.
[33] Boehm M M,AndeersonD W.A landscape-scales study of soil quality in three Prairie farming systems.Soil Sci. Soc.Am.J,1997,61:1147-1159.
[34]孔祥斌,刘灵伟,秦静.基于农户行为的耕地质量评价指标体系构建的理论与方法.地理科学进展,2007,26(4):75-85.
[35]万存绪,张效勇.模糊数学在土壤质量评价中的应用.应用科学学报,1991,9(6):359-365.
[36]王效举,龚子同.红壤丘陵小区域水平上不同时段土壤质量变化的评价和分析.地理科学,1997,17(2):141-149.
[37] Fu B J,Liu S L,Chen L D,et al.Comparing the soil quality changes of different land uses determined bytwo quantitative methods.Journal of Environmental Sciences,2003,15(2):167-172.
[38]王军艳,张凤荣,王茹,贾小红,张彩月.2001.应用指数和法对潮土农田土壤肥力变化的评价研究.农村生态环境,17(3):13-16.
[39]马强,宇万太,赵少华,张璐,沈善敏,王永宝.黑土农田土壤肥力质量综合评价.应用生态学报,2004,15(10):1916-1920.
[40]胡月明,吴谷丰,江华,张馨远,徐剑波,李兴华.基于GlS与灰关联综合评价模型的土壤质量评价.西北农林科技大学学报(自然科学版),29(4):39-42.
[41]吴红玉,田霄鸿,侯永辉,周密,同延安.基于田块尺度的土壤肥力模糊评价研究.自然资源学报,2009.24(8):1422-1431.
[42]张庆利,潘贤章,王洪杰,刘付程,史学正.中等尺度上土壤肥力质量的空间分布研究及定量评价.土壤通报,2003,34(6):493-497.
[43]肖慈英,阮宏华,屠六邦.下蜀主要森林土壤肥力的灰色关联分析与评价.南京林业大学学报（自然科学版）2000.
[44] Andrew J C,Burton A M,M Paul,Andrew W Y,Shigeru A.2001.A principal component analysis offacial expressions.Vision Research.41:1179-1208.
[45] Hou W G,Jiang SC, Xiong S Q,et al.Evaluation of soil quality based on G1S. Geomatics andinformation Science of Wuhan University,2003,28(1):60-64.
[46]张庆利,史学正,潘贤章,于东升,刘付程.江苏省金坛市土壤肥力的时空变化特征.土壤学报,2004,41(2):315-319.
[47]张华,张甘霖,漆智平,赵玉国.热带地区农场尺度土壤质量现状的系统评价.土壤学报,2003,40(2):186-193.
[48]谢伯承.基于高光谱遥感不同发生层土壤的光谱信息提取研究.陕西杨凌:西北农林科技大学,2004.
[49] He Yong,Song Haiyan, Annia G P.A new approach to predict N, P, K and OM content in a loamymixed soil by using near infrared reflectance spectroscopy.Lecture Notes in Computer Science,2005,3644:859-867.
[50] Ben Dor E,Bania A.Soil Science Society of America Journal.1995,59:364.
[51]曾志远.土壤肥力的卫星遥感探测.土壤,1987,(2):72,73-78.
[52]祁亚琴.基于高光谱遥感数据提取农田土壤特征信息的研究[博士论文].石河子:石河子大学,2011.
[53] Hunt G R,Salisbury J W.Visible and near infrared spectra of minerals and rocks,I,Silicate Minerals.Mod.Geol,1970(1)283-300.
[54]徐彬彬,戴昌达.南疆土壤光谱反射特性与有机质含量的相关性分型科学通报.1980,282-284.
[55]程彬,姜琦刚.遥感影像在土壤属性估算中的应用.中国农学通报,2008,24(1):467-470.
[56]程彬,姜琦刚,陈凤臻,张红红,崔翰文.松辽平原黑土有机质含量的遥感反演研究水土保持研究,2011,8(1):264-267.
[57]梅安新,彭望碌,秦其明,刘慧平.遥感导论.北京:高等教育出版社,2001.
[58]赵英时.遥感应用分析原理与方法.北京:科学出版社,2003.
[59] Webster R.Statistics to support soil research and their presentation.European Journal of Soil Science,2001,52:331-340.
[60]沙晋明,利用土壤黑度值实现土壤肥力遥感监测机理.山西农业大学学报,1996,16(4):372-376.
[61]张法升,曲威,尹光华,刘作新.基于多光谱遥感影像的表层土壤有机质空间格局反演.应用生态学报,2010,21(4):883-888.
[62] Ben-Dor E,Patkin K, Banin A,et al.Mapping of several soil properties using DAIS-7915hyperspectralscanner data-a case study over clayey soils in Israel. International Journal of Remote Sensing,2002,23(6):1043-1062.
[63] Bowers S,Hanks R J.Reflectance of radiant energy from soil.Soil Sci.,1965,100:130-138.
[64] Baumgardner M F,Kristoff S J,Johannsen C J.The effect of organic matter on multi-spectral propertiesof soils.Proc Indiana Acad Sci,1970,79:413-422.
[65] Al-Abbas A H,Swain P H,Baumgardner M F.Relating soil organic matter and clay content to themulti-spectral radiance.Soil Sci,1972,114:477-485.
[66] Garey A. Fox,George J.Sabbagh.Estimation of soil organic matter from red and near-infrared remotelysensed data using a soil line Euclidean Distance Technique.Soil Sci Soc Am J,2002,66:1922-1929.
[67] Chen F, Kissell D E,West L T,et al.Field-scale mapping of surface soil organic carbon using remotelysensed imagery.Soil Sci Soc Am J,2000,64:746-753.
[68] Frazier B E,and Cheng Y.Remote sensing of soils in the eastern palouse region with landsat thematicmapper.Remote Sensing of Environment,1989,28:317-325.
[69]潘瑜春,王纪华,陆安祥,陆洲.基于小麦长势遥感监测的土壤氮素累积估测研究.农业工程学报,2007,23(9):58-63.
[70]陈蓉蓉,周治国,曹卫星,戴延波.基于GIS的农田土壤、作特征空间变异性及其相互关系.应用生态学报,2004,15(9):1678-1680.
[71]张素梅,王宗明,张柏,宋开山,刘殿伟,李方,任春颖,黄健,张惠琳.利用地形和遥感数据预测土壤养分空间分布.农业工程学报,2010,26(5):188-194.
[72]潘剑君,刘世峰,赵美芳.遥感估测土壤元素技术体系建立的研究初探——以溧水水田土壤全氮为例中国土壤与肥料.2010,4:18-23.
[73]李欣宇,宇万太,李秀珍.遥感与地统计方法在表层土壤有机碳空间格局研究中的应用比较.农业工程学报,2009,25(3):148-152.
[74]潘文超,李少昆,王克如,肖华,陈兵,王方永,苏毅,陈江鲁,赖军臣,黄芳德.基于棉花冠层光谱的土壤氮素监测研究.棉花学报,2010,22(1):70-76.
[75]陈兵,李少昆,王克如,柏军华,随学艳,白彩云.作物病虫害遥感监测研究进展.棉花学报,2007,19(1):57-63.
[76] CHEN F, Kissel D E, West L T, et al.Mapping surface soil organic carbon for crop fields with remotesensing.Journal of soil and water conservation,2005,60(1):51-57.
[77] SULLIVAN D, Shaw J N, Rickman D. IKONOS imagery to estimate surface soil property variabilityin two Alabama physiographies Soil Science Society of America Journal,2005,69(6):1789-1798.
[78]陈玉福,董鸣.毛乌素沙地景观的植被与土壤特征空间格局及其相关分析.植物生态学报,2001,25(3):265-269.
[79]柏军华.棉田管理信息的遥感提取研究[博士论文].北京:中国农业科学院,2009.
[80]宋晓宇,王纪华,刘良云,黄文江,沈涛,喻铮铮.基于Quickbird遥感影像的农田管理分区划分研究.中国农业科学,2007,40(9):1996-2006.
[81]谭昌伟.稻麦主要调优栽培指标的遥感监测研究[博士论文].扬州:扬州大学,2010.
[82]王来刚,王备战,冯伟,郑涛,冯晓,郑国清. SPOT-5与HJ遥感影像用于冬小麦氮素监测的效果对比.麦类作物学报.2011,31(2):331-336.
[83]刘世峰,潘剑君,杨志强,胡若婧,刘莎.利用中巴-2号卫星CCD估测土壤全氮的研究.遥感应用,2010,1:57-63.
[84] Levine E R,Ranson K J,Smith I,et al.Forest ecosystem dynamics: linking forest succession,soilprocess,and radiation models.Ecological Modeling,1993,65:199-219.
[85] Lydia Serrano,Iolanda Filella,Josep Penuelas. Remote sensing of biomass and yield of winter wheatunder different nitrogen supplies.Crop Science,2000,40:723-731.
[86] Wright D L,Rasmussen V P,Baker D J.Using remote sensing to manage wheat grain protein.NASASSC Report,2003, ARC-USU-001-02.
[87] NUMATA I,Soares J V,Roberts D A,et al.Relationships among soil fertility dynamics and remotelysensed measures across pasture chronosequences in Rondonia,Brazil. Remote Sensing of Environment,2003.87(4):446-455.
[88] Michael Flowers,Randall Weisz,Ronnie Heiniger. Remote sensing of winter wheat tiller density forearly nitrogen application decisions.Agron J,2001,93:783-789.
[89] Michael Flowers,Randall Weisz,Ronnie Heiniger,et al.Field validation of a remote sensing techniquefor early nitrogen application decisions in wheat.Agron J,2003,95:167-176.
[90] Wenjiang Huang,Jihua Wang,Zhijie Wang,et al.Inversion of foliar biochemical parameters at variousphysiological stages and grain quality indicators of winter wheat with canopy reflectance.International Journal of Remote Sensing,2004,25(12):2409-2419.
[91] Chunjiang Zhao,Liangyun Liu, Jihua Wang, et al. Predicting grain protein content of winter wheatusing remote sensing data based on nitrogen status and water stress. International Journal of AppliedEarth Observation and Geoinformation,2005,7(1):1-9.
[92] Chunjiang Zhao,Jihua Wang,Liangyun Liu,et al.Relationship of2100-2300nm spectral characteristicsof wheat canopy to leaf area index and leaf N as affected by leaf water content. Pedosphere,2006,16(3):333-338.
[93] Liangyun Liu,Jihua Wang,Yansong Bao,et al.Predicting winter wheat condition,grain yield and proteincontent using Multi-temporal EnviSat-ASAR and Landsat TMsatellite images.International Journal ofRemote Sensing,2006,27(4):737-753.
[94] Puzachenko Y G,Kozlov D N,Siunova E V,et al.Assessment of the reserves of organic matter in theworld＇s soils:Methodology and results.Eurasian Soil Science,2006,39(12):1284-1296.
[95] Takata Y,Funakawa S,Akshalov K,et al.Spatial prediction of soil organic matter in northernKazakhstan based on topographic and vegetation information.Soil Science and Plant Nutrition,2007,53(3):289-299.
[96] Takata Y,Funakawa S,Akshalov K,et al.Regional evaluation of the spatial-temporal variation in soilorganic carbon dynamics for rain-fed cereal farming in northern Kazakhstan.Soil Science and PlantNutrition,2008,54(5):794-806.
[97] Verhulst N,Govaerts B,Sayre K D,et al.Using NDVI and soil quality analysis to assess influence ofagronomic management on with-in-plot spatial variability and factors limiting production.Plant andSoil,2009,317(1-2):41-59.
[98] Leon C T,Shaw D R,Cox M S,et al.Utility of remote sensing in predicting crop and soil characteristics.Precision Agriculture.2003(4):359-384
[99]韩爱惠.用MODIS数据监测京津塘风沙源工程区植被指数的选择及合成.国土资源遥感,2004,3:54-56.
[100] Jordan C F.Derivation of leaf-area index from quality of light on the forest floor.Ecology,1969,50:663-666.
[101] Richardson A J,Wiegand C L.Distinguishing vegetation from soil background information.Photogrammetric Engineering and Remote Sensing,1977,43(12):1541-1552.
[102] SULLIVAN D G,Shaw J N,Rickman D.IKONOS imagery to estimate surface soil propertyvariability in two Alabama physiographies soil.Science Society of America Journal,2005,69(6):1789-1798.
[103]宋晓宇,王纪华,薛绪掌,刘良云,陈立平,赵春江.利用航空成像光谱数据研究土壤供氮量及变量施肥对冬小麦长势影响.农业工程学报,2004,20(4):45-49.
[104]卢艳丽,白由路,王磊,王贺,杨俐苹.黑土土壤中全氮含量的高光谱预测分析.农业工程学报,2010,26(1):256-261.
[105]曾志远.卫星图象密度-辐射量算与土壤资源探测.资源科学,1981(4):72-78.
[106]吕新.3S技术在精准农业中的应用.北京:中国科学文化出版社,2007,9.
[107]张竞成,顾晓鹤,王纪华,黄文江,何馨,王慧芳.基于HJ-CCD与TM影像的水稻LAI估测一致性分析.农业工程学报,2010,26(7):186-193.
[108]环境保护部卫星环境应用中心网站http://60.247.54.34/secPortal/portal/index.faces.
[109]邓书斌.ENVI遥感图像处理方法.科学出版社,北京:2010
[110]高建峰.辅以ETM+的MODIS影象土地利用变化监测及土壤有机碳库估算研究一一以吴江市为例[博士论文].南京:南京农业大学,2007.
[111]朱述龙.区域的深度计算及其在图像渐变处理中的应用.中国图像图形学报.2000,5(9):734-738.
[112]张芳.基于遥感技术的干旱区湿地信息提取方法研究[硕士论文].乌鲁木齐:新疆大学,2008.
[113] Xu L,Hou L C,Yang Q,Zhang Z,Jin Z L.Study on optimum band in land use/land cover informationextraction using TM image. Journal of Hubei University (Natural Science),2011,33(1):119-122.
[114] Institute of Soil Science,CAS.Physical and chemical analysis of soil.Shanghai:Shanghai Science andTechnology Press,1978.
[115]李卫国,李花,王纪华,黄文江.基于Landsat/TM遥感的冬小麦长势分级监测研究.麦类作物学报,2010,30(1):92-95.
[116]冉琼,迟耀斌,王智勇,陈正超.北京1号小卫星图像噪声评估.遥感学报,2009,13(3):554-558.
[117]唐华俊,吴文斌,杨鹏,周清波,陈仲新.农作物空间格局遥感监测研究进展.中国农业科学,2010,43(14):2879-2888.
[118]许菡,燕琴,徐泮林.多源遥感影像融合最佳波段选择及质量评价研究.测绘科学,2007,2(3):72-74,87.
[119]张若琳,万力,张发旺,石迎春.土地利用遥感分类方法研究进展.南水北调与水利科技,2006,4(2):39-42.
[120] Bertsch P M,Thomas G W.Potassium stassium of temperate region soils. In:Munson R E.Potassium inagriculture. Madison:American Society of Agronomy.1985,131-162.
[121]胡克林,李保国,林启美,李贵桐,陈德立.农田土壤养分的空间变异性特征.农业工程学报,1999,15(3):33-38.
[122]陈彦,吕新.基于GIS和地统计学的土壤养分空间变异特征研究—以新疆农七师125团为例.中国农学通报,2005,21(7):389-391,405.
[123] Stark C H,Condron L M,Stewart A.Small-scale Spatial variability of selected soil biologicalproperties.Soil Biology and Biochemistry,2004,36(4):601-608.
[124] Corre M D,Schnabel,Stout R.Spatial and seasonal variation of gross nitrogen transformations andmicrobial biomass in a northeastern US grassland.Soil Biology and Biochemistry,2002,34:445-457.
[125] Alex B,McBratney,Inakwu O.A.Odeh,Thomas F.A. Bishop, Marian S.Dunbar,Tamara M.Shatar.Anoverview of pedometric techniques for use in soil survey. Geoderma,2000,97(3):293-327.
[126] Sumfleth K,Duttmann R.Prediction of soil property distribution in paddy soil landscapes using terraindata and satellite information as indicators. Ecological Indicators,2008,8(5):485-501.
[127]杨玉玲,田长彦,盛建东.棉田土壤有机质、全氮、全钾全磷空间变异分析.干旱地区农业研究,2002,3:26-30.
[128]李晓燕,张树文,王宗明,张惠琳.吉林省德惠市土壤特性空间变异特征与格局.地理学报,2004,59(6):989-997.
[129]郭旭东,傅伯杰,陈立顶,马克明,李俊然.河北省遵化平原土壤养分的时空变异特征——变异函数与Kriging插值分析.地理学报,2000,55(5):555-566.
[130]李海滨,林忠辉,刘苏峡.Kriging方法在区域土壤水分估值.地理研究,2001,20(4):446-452.
[131]石小华,杨联安,张蕾.土壤速效钾养分含量空间插值方法比较.水土保持学报,2006.20(2):68-72.
[132] Combardella C A,Moorman T B,Novak J M,Parkin T B,Karlen D L,Turco R F,Konopka A E.Field-scale variability of soil properties in central Iowa soils.Soil Science Society of America journal,1994,58:1501-1511.
[133]郭胜利,刘文兆,史竹叶,侯喜禄,李凤民.半干旱区流域土壤养分分布特征极其与地形、植被的关系.干早地区农业研究,2003,21(4):40-43.
[134] Sullivan D q Shaw J N,Rickman D.IKONOS imagery to estimate surface soil property variability intwo Alabama physiographies. Soil Science Society of America Journal,2005,69(6):1789-1798.
[135]裴志远,杨邦杰.多时相归一化植被指数NDVI的时空特征提取与作物长势模型设计.农业工程学报,2000,16(5):20-22.
[136]阎晓娟.田块尺度作物长势与空间变异遥感监测研究[硕士论文].西安:西安科技大学,2008.
[137]陈兵.基于多平台棉花黄萎病的遥感监测研究[博士论文].石河子:石河子大学,2010.
[138]蒋桂英.新疆棉花主要栽培生理指标的高光谱定量提取与应用研究[博士论文].石河子:石河子大学,2004.
[139]刘世梁,傅伯杰,刘国华,马克明.我国土壤质量及其评价研究的进展.土壤通报,2006,1:137-143.
[140]周勇,李学垣,贺纪正,王庆云,刘勇.ARC/INFO信息系统在农地分等定级中的应用.土壤学报,1998,35(4):450-460.
[141]吴玉红,田霄鸿,同延安,南雄雄,周密,侯永辉.基于主成分分析的土壤肥力综合指数评价.生态学杂志,2010,29(1):173-180.
[142]王玲.基于GIS和RS的干旱区绿洲耕地质量评价方法及应用研究[博士论文].石河子:石河子大学,2011.
[143]苗军.基于GIS的最佳选点区域研究[硕士论文].昆明:昆明理工大学,2009,4.
[144]王瑞燕,赵庚星,陈丽丽.基于ANN-产量的耕地地力定量评价模型及其应用.农业工程学报,2008,24(l):113-118.
[145]柏军华,李少昆,李静,王克如,谢瑞芝,高世菊,陈兵,王方永,刘国庆,谭海珍.基于多时相棉花长势遥感的棉田质量诊断.中国农业科学,2008,41(4):1003-1011.
[146]严红萍,俞兵.主成分分析在遥感图像处理中的应用.资源环境与工程.2006,20(2):168-170.
[147]李梅,张学雷,武继承.GIS支持下豫东地区土壤野外采样布点方法探索.土壤,2011,43(3):459-465.
[148]范君华,刘明.新疆绿洲棉田土壤质量演变规律分析.中国棉花,2011,38(7):31-34.