农田土壤水分遥感反演及其时空变异特征分析
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摘要
土壤湿度是气候、水文、生态、农业等领域的重要参数,在地表与大气界面的水分和能量交换中起重要作用。土壤湿度的变化会引起土壤热学特性的改变、地表光学特性的改变,从而影响气候的变化。区域性和大尺度的陆地土壤湿度变化信息对于陆-气交互作用平衡和陆面水文研究、改善区域及全球气候模式预报结果、水涝和干旱的监测、农作物生长态势评估、自然和生态环境问题的研究等都是十分关键的因素。遥感能够快速方便地获取大区域的地表信息,因而,使用遥感手段反演区域或大范围不同深度的土壤水分以及研究其时空变异性和影响因子具有重要意义。
本文在综述国内外土壤水分的遥感定量反演研究文献基础上,分析了各种定量反演土壤水分的遥感模型,结合仪征地区当地农田作物的根系特征,选择使用温度/植被指数(Ts/NDVI)模型来反演农田深层的土壤湿度,并且利用主成分分析的方法对仪征地区土壤水分的影响因子进行了分析。主要研究结果如下:
1.对地面实测数据进行了初步分析,使用克吕格方法对仪征地区2004年5月、2004年9月、2004年11月、2005年3月和2005年5月实测的0-20cm和20-40cm深度土壤湿度数据进行地统计插值,统计结果显示仪征地区0-20cm深度土壤湿度的基底比平均值为58.53%,20-40cm深度土壤湿度的基底比平均值为55.58%,均为中等的空间相关性。说明该区域由非区域因素引起的变异超过50%左右,非区域因素起的作用表现的比较明显,这与仪征地区实际状况相吻合,仪征紧邻长江、河网密布、灌溉比较发达,使当地的土壤含水量受人为因素影响比较大。
2.利用2004年和2005年1km空间分辨率、8天合成的MODIS地表温度产品和1km分辨率、16天合成的MODIS植被指数产品,使用Ts/NDVI法反演了仪征地区2004年5月、9月、11月和2005年3月、5月共五个月的20-40cm深度的土壤湿度,并使用与卫星同步的野外采样点数据进行验证及与使用地统计插值的结果相比较,结果显示本研究采用Ts/NDVI法反演0-20cm和20-40cm深度的土壤湿度可以达到较高的精度,有一定的应用价值。与地统计插值结果相比,使用遥感法反演的土壤湿度可以不依靠地面数据,而且更加快速、迅捷。
3.使用遥感手段反演的仪征地表土壤湿度信息反映了该地区湿度分布的整体趋势,仪征地区土壤湿度分布图表明仪征地区主要存在两个土壤湿度高值区,分别位于仪征南部的长江冲积平原和西北部的谷底平原地带;土壤湿度低值区主要分布在仪征中部的缓岗丘陵区。
4.利用遥感反演的结果对仪征地区土壤水分空间分布的各影响因子进行了分析,本研究中各影响因子主要包括地形、潜水埋深、耕层厚度、土壤容重、土壤孔隙度及土壤非毛管孔隙度。结果在中等含水量土壤水分状态下,0-20cm深度土壤水分分布的主要影响因子为潜水埋深、地形和耕层厚度,20-40cm深度土壤水分分布的主要影响因子为地形、潜水埋深和耕层厚度;高含水量和低含水量状态下,0-20cm深度土壤水分分布的主要影响因子为地形和耕层厚度,而在20-40cm土壤深度本研究所列影响因子均不是主要影响因子。
Soil moisture is an important indicator for climate、water resources、economy and agriculture. It plays an important role on the water and energy exchange at the land surface/atmosphere interface. The change of the soil moisture will lead to change of the thermotics characteristic of soil and optical properties of surface, even to the change of climate.The information of the land soil moisture change in regional and large-scale is important to the research as the balance of land-atmosphere interaction, land hydrology, improving the forecast accuracy of regional and GCM, monitoring of flooding and drought, assessment of the growth condition of corps, the natural and ecology problems.It is significant to do research on spatial and time variability of soil moisture and on how to monitor soil moisture by remote sensing, which can provide information on large area quickly and easily.
After analyze all kinds of information about soil moisture reversion and compare different quantitative remote sensing models, we think it is reasonable to use Ts/NDVI model to retrieve depth soil moisture and do research on respect factors of the soil moisture with principal components analysis.To summarize, main findings of this study are:
1. After analyze the ground truth data, and interpolated 0-20cm and 20-40cm depth soil moisture in May 2004, September 2004, November 2004, March 2005 and May 2005 with Kring method, the result show that it was the middle of the space-related that the mean Nugget/Sill was 58.53% in 0-20cm depth and was 55.58% in 20-40cm depth soil. In the region caused by non-regional variations in more than 50 percent, the non-regional factors performance of the role of the more obvious,which match the actual situation in Yizheng ,Yizheng close to the Yangtze River,so the soil moisture by man-made factors are considerable.
2. We use Ts/NDVI model to monitor soil moisture in Yizheng in May、September、November of 2004 and March、May of 2005, based on the MODIS products MOD11A2 and MOD13A2. Validation of the retrieved information by the field data has show that the model is very well to obtain the depth soil moisture. We find that the space continuity and detail performance of soil moisture by remote sensing is better.
3. We obtain the distribution of moisture in the overall trend with remote sensing, the result show that there are two high-value soil moisture area in Yizheng, one is in the south of the Yangtze flood plains, and another is in the north-west plains. The low-value soil moisture area is mainly distributed in the central hilly region.
4. we analyze the factors which impact the spatial distribution of soil moisture in Yizheng with remote sensing, the respect factors contain Terrain,Bulk Density,Soil Porosity,Soil Non-capillary Porosity,Cultivated Thickness and Groundwater Depth.The result show that the main factors are Groundwater Depth, Terrain and Cultivated Thickness in 0-20cm depth soil and Terrain, Groundwater Depth and Cultivated Thickness in 2040cm depth soil under medium moisture. The main factors are Terrain and Cultivated Thickness in 0-20 cm , but the factors in this research are not the main factors in the 2040cm depth soil moisture under high moisture and low moisture.
本文在综述国内外土壤水分的遥感定量反演研究文献基础上,分析了各种定量反演土壤水分的遥感模型,结合仪征地区当地农田作物的根系特征,选择使用温度/植被指数(Ts/NDVI)模型来反演农田深层的土壤湿度,并且利用主成分分析的方法对仪征地区土壤水分的影响因子进行了分析。主要研究结果如下:
1.对地面实测数据进行了初步分析,使用克吕格方法对仪征地区2004年5月、2004年9月、2004年11月、2005年3月和2005年5月实测的0-20cm和20-40cm深度土壤湿度数据进行地统计插值,统计结果显示仪征地区0-20cm深度土壤湿度的基底比平均值为58.53%,20-40cm深度土壤湿度的基底比平均值为55.58%,均为中等的空间相关性。说明该区域由非区域因素引起的变异超过50%左右,非区域因素起的作用表现的比较明显,这与仪征地区实际状况相吻合,仪征紧邻长江、河网密布、灌溉比较发达,使当地的土壤含水量受人为因素影响比较大。
2.利用2004年和2005年1km空间分辨率、8天合成的MODIS地表温度产品和1km分辨率、16天合成的MODIS植被指数产品,使用Ts/NDVI法反演了仪征地区2004年5月、9月、11月和2005年3月、5月共五个月的20-40cm深度的土壤湿度,并使用与卫星同步的野外采样点数据进行验证及与使用地统计插值的结果相比较,结果显示本研究采用Ts/NDVI法反演0-20cm和20-40cm深度的土壤湿度可以达到较高的精度,有一定的应用价值。与地统计插值结果相比,使用遥感法反演的土壤湿度可以不依靠地面数据,而且更加快速、迅捷。
3.使用遥感手段反演的仪征地表土壤湿度信息反映了该地区湿度分布的整体趋势,仪征地区土壤湿度分布图表明仪征地区主要存在两个土壤湿度高值区,分别位于仪征南部的长江冲积平原和西北部的谷底平原地带;土壤湿度低值区主要分布在仪征中部的缓岗丘陵区。
4.利用遥感反演的结果对仪征地区土壤水分空间分布的各影响因子进行了分析,本研究中各影响因子主要包括地形、潜水埋深、耕层厚度、土壤容重、土壤孔隙度及土壤非毛管孔隙度。结果在中等含水量土壤水分状态下,0-20cm深度土壤水分分布的主要影响因子为潜水埋深、地形和耕层厚度,20-40cm深度土壤水分分布的主要影响因子为地形、潜水埋深和耕层厚度;高含水量和低含水量状态下,0-20cm深度土壤水分分布的主要影响因子为地形和耕层厚度,而在20-40cm土壤深度本研究所列影响因子均不是主要影响因子。
Soil moisture is an important indicator for climate、water resources、economy and agriculture. It plays an important role on the water and energy exchange at the land surface/atmosphere interface. The change of the soil moisture will lead to change of the thermotics characteristic of soil and optical properties of surface, even to the change of climate.The information of the land soil moisture change in regional and large-scale is important to the research as the balance of land-atmosphere interaction, land hydrology, improving the forecast accuracy of regional and GCM, monitoring of flooding and drought, assessment of the growth condition of corps, the natural and ecology problems.It is significant to do research on spatial and time variability of soil moisture and on how to monitor soil moisture by remote sensing, which can provide information on large area quickly and easily.
After analyze all kinds of information about soil moisture reversion and compare different quantitative remote sensing models, we think it is reasonable to use Ts/NDVI model to retrieve depth soil moisture and do research on respect factors of the soil moisture with principal components analysis.To summarize, main findings of this study are:
1. After analyze the ground truth data, and interpolated 0-20cm and 20-40cm depth soil moisture in May 2004, September 2004, November 2004, March 2005 and May 2005 with Kring method, the result show that it was the middle of the space-related that the mean Nugget/Sill was 58.53% in 0-20cm depth and was 55.58% in 20-40cm depth soil. In the region caused by non-regional variations in more than 50 percent, the non-regional factors performance of the role of the more obvious,which match the actual situation in Yizheng ,Yizheng close to the Yangtze River,so the soil moisture by man-made factors are considerable.
2. We use Ts/NDVI model to monitor soil moisture in Yizheng in May、September、November of 2004 and March、May of 2005, based on the MODIS products MOD11A2 and MOD13A2. Validation of the retrieved information by the field data has show that the model is very well to obtain the depth soil moisture. We find that the space continuity and detail performance of soil moisture by remote sensing is better.
3. We obtain the distribution of moisture in the overall trend with remote sensing, the result show that there are two high-value soil moisture area in Yizheng, one is in the south of the Yangtze flood plains, and another is in the north-west plains. The low-value soil moisture area is mainly distributed in the central hilly region.
4. we analyze the factors which impact the spatial distribution of soil moisture in Yizheng with remote sensing, the respect factors contain Terrain,Bulk Density,Soil Porosity,Soil Non-capillary Porosity,Cultivated Thickness and Groundwater Depth.The result show that the main factors are Groundwater Depth, Terrain and Cultivated Thickness in 0-20cm depth soil and Terrain, Groundwater Depth and Cultivated Thickness in 2040cm depth soil under medium moisture. The main factors are Terrain and Cultivated Thickness in 0-20 cm , but the factors in this research are not the main factors in the 2040cm depth soil moisture under high moisture and low moisture.
引文
[1]国家统计局国民经济综合统计司.新中国五十年统计资料汇编.北京:中国统计出版社,1999
[2]肖斌,沙晋明.土壤水分遥感反演方法概述[J].遥感信息,2007.6:94-98
[3]王鹏新,龚健雅,李小文.条件植被指数及其在干早监测中的应用[J].武汉大学学报(信息科学版),2001,26(5):412-418.
[4]魏国栓,沈润平,丁国香.仪征地区农田深层土壤湿度遥感反演初探[J].遥感技术与应用,2008,23(1):36-41
[5]Pratt A,Ellyett C D.The thermal inertia approach to mapping of soil moisture and geology[J].Remote Sens Environ,1979,8:151-168
[6]姚春生,张增祥,汪潇.使用温度植被干旱指数法(TVDI)反演新疆土壤湿度[J].遥感技术与应用,2004,19(6):473-478.
[7]Watson K,Pohn H A.Thermal Inertia Mapping from Satellites Discrimination of Geologic Units in Oman[J].J Res Geol Suvr,1974,2(2):147-158
[8]Watson K,Rowen L C,Offield T W.Application of Thermal Modeling in the Geologic Interpretation of IR Images[J].Remote Sensing of Environment,1971,3,2017-2041.
[9]Price,J.C.Using spatial context in satellite data to infer regional scale evapotranspiration[J].IEEE Transactions on Geoscience and Remote Sensing,1990,28:940-948
[10]Goward,S.N,Xue,Y and Czajkowski,K.P.Evaluating land surface moisture conditions from the remotely sensed temperature/vegetation index measurements:An exploration with the simplified simple biosphere model[J].Remote Sensing of Environment,2002,79(2-3):225-242
[11]Sandholt,L.Rasmussen K.Andersen J.A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status[J].Remote Sensing of Enviromrent.2002,79:213-224
[12]张仁华.改进的热惯量模式及遥感土壤水分地理研究1990,19(2):101-112
[13]隋洪智,田国良.热惯量方法监测土壤水分.见:田国良主编.黄河流域典型地区遥感动态研究,北京:科学出版社,1990.
[14]田国良,杨希华,郑柯.冬小麦旱情遥感监测模型研究[J].环境遥感,1992,
[15]肖乾广,陈维英,盛永伟等.用气象卫星监测土壤水分的试验研究[J].应用气象学报1994.5(2):312-317
[16]余涛,田国良.热惯量法在监测土壤表层水分变化中的研究[J].遥感学报,1997,1(1):24-31
[17]隋洪智,田国良,李付琴.农田蒸散双层模型及其在干旱遥感监测中的应用[J].遥感学报,1997,1(3):220-224
[18]刘丽,周颖.用遥感植被供水指数监测贵州干旱,贵州气象,1998,122(6):17-21
[19]刘良云,张兵,郑兰芬.利用温度和植被指数进行地物分类和土壤水分反演[J],红外与毫米波学报,2002,21(4):269-273
[20]辛景峰.区域旱情遥感监测研究.中科院遥感应用研究所博士后研究工作报告,2003
[21]江苏省仪征县土壤志[M],南京:仪征县土壤普查办公室,1984,1-15
[22]邹源.不同地貌土壤属性空间变异研究,扬州大学硕士论文,2006
[23]赵鹏大.定量地学方法及应用,北京:高等教育出版社,2004,78-99
[24]汤国安,杨昕.ArcGIS地理信息系统空间分析实验教程,北京:科学出版社,2006363-422
[25]路鹏,彭佩钦,宋变兰等.洞庭湖平原土壤全磷含量地统计学和GIS分析[J],中国农业科学,2005,38(6):1204-1212
[26]Price J.C,Thermal inertia mapping:a new view of the Earth[J],J.Geophys Res,1977,82:2582-2590
[27]Price J.C,On the analysis of thermal infrared imagery:the Limited utility of apparent thermal inertia[J],Remote Sensing of Environment,1985,18(1),59-73
[28]Millard,J.P.,Jackson,R.D.,Crop water stress assessment using a airborne thermal scanner[J],Photog.Eng Rem Sens,1978,44,77-85
[29]Soer,G.J.R,Estimation of regional evapotranspiration and soil moisture conditions usingremotely sensed crop surface temperature[J],Remote Sensing of Environment,1980,9,27-45
[30]Jackson.R.D.Canopy temperature as a crop water stress indicator[J],Irrigation Science,1988,9:309-317
[31]郭铌.植被指数及其研究进展.干旱气象,2003,21(4),71-75
[32]于贵瑞.不同冠层类型的陆地植被蒸发散模型研究进展[J],资源科学,2001,23(6),72-84
[33]李亚春,王志华.我国干旱热红外遥感监测方法的研究进展[J].干旱地区农业研 究,1999,1(2)98-102
[34]佘万明,叶彩华.MODIS资料遥感监测土壤水分与干旱研究进展[J],河南气象,2006.144-46
[35]11.Fawwaz T.Ulaby,Percy P.Batlivala,Optimum Rada parameters for Mapping Soil Moisture,IEEE Transactions on Geoscience Electronics,1976,Vol.GE-14,No2,pp.81-93
[36]田国良.土壤水分的遥感监测方法[J].环境遥感,1991,6(2):89-98
[37]李杏朝.微波遥感监测十壤水分的研究初探[J],遥感技术与应用,1995,10(4):1-8
[38]Njoku E.Li L.Retrieval of Land Surface Parameters Using Passive Microwave Measurements at 6-18GHz[J],IEEE Trans Geosci Remote Sensing,1999,37(1):79-93
[39]杨虎.植被覆盖地表土壤水分变化雷达探测模型和应用研究,中国科学院研究生院博士学位论文,2003
[40]邓明弢,王宝珠.水分测定法(M),北京:高等教育出版社,1992.66-69
[41]http://edcimswww.cr.usgs.gov/pub/imswelcome/
[42]http://nfgis.nsdi.gov.cn/nfgis/chinese/c_xz.htm
[43]http://modis.gsfc.nasa.gov
[44]刘闯,葛成辉.美国对地观测系统(EOS)中分辨率成像光谱仪(MODIS)遥感数据的特点与应用[J].遥感信息2000.3:45-48
[45]马元喜.不同土壤对小麦根系生长动态的研究[J].作物学报,1987,3(1):37-44.
[46]邓辉,周清波.土壤水分遥感监测方法进展[J].中国农业资源与区划,2004,25(3):46-49.
[47]Nemani,R R,Pierce,L,Running,S.,and Goward,S.Developing satellite-derived estimates of surface moisture status[J].Journal of Applied Meteorology,1993,32(3):548557
[48]Nemani,R.Rurming,S.W.Estimation of regional surface resistance to evapotranspiration from NDVI and thermal IR AVHRR data[J].Journal of Applied Meteorology,1989,28:276-284
[49]Price,J.C.Using spatial context in satellite data to infer regional scale evapotranspiration [J].IEEE Transactions on Geoscience and Remote Sensing,1990,28:940-948
[50]强建华,赵鹏祥,陈国领.基于NDVI的油松天然林生长状况的遥感监测研究[J].西北林学院学报,2007,22(1):149-151.
[51]唐怡,刘良云,黄文江,王纪华.土壤背景对冠层NDVI的影响分析[J].遥感技术与应用,2006,21(2):142-148.
[52]钱允祺,陶士珩,王立祥等.土壤湿度的统计特征及应用分析[J].中国农业气象,1999,20(1):15-17
[53]赵鹏大.定量地学方法及应用,北京:高等教育出版社,2004,78-99
[54]汤国安,杨昕.ArcGIS地理信息系统空间分析实验教程[M],北京:科学出版社,2006363-422
[55]路鹏,彭佩钦,宋变兰等.洞庭湖平原土壤全磷含量地统计学和GIS分析[J],中国农业科学,2005,38(6):1204-1212
[56]邱扬,傅伯杰,王军等.土壤水分时空变异及其与环境因子的关系[J],生态学杂志,2007,26(1):100-107
[57]Andrew W.Westerna,Sen-Lin Zhou,Rodger B.Grayson,ThomasA.McMahon,Gunter Bloschlb,David J.Wilson.Spatial correlation of soil moisture in small catchments and its relationship to dominant spatial hydrological processes[J],Journal of Hydrology 2004 286,113-134
[58]Herbst M,Diekkruger B.Modeling the spatial variability of soil moisture in a micro-scale catchment and comparison with field data using geostatistics[J].Physics and Chemistry of the Earth,2003,28:239-245.
[59]刘继龙,张振华,谢恒星等.烟台果园表层土壤水分的时空分布及分形特征[J],土壤通报,2006,37(6):1076-1080
[60]尤文忠,曾德慧,刘明国等.黄土丘陵区林草景观界面雨后土壤水分空间变异规律[J]应用生态学报,2005,16(9):1591-1596
[61]刘鑫,毕华兴,李笑吟等.晋西黄土区基于地形因子的土壤水分分异规律研究[J],土壤学报,2007,44(3):411-417
[62]张俊斌,黄雍杰,梁大庆.不同坡地土壤水分分布变化之研究[J],水土保持研究,2007,14(1):301-304
[63]陈伏生,曾德慧,陈广生等.不同土地利用方式下沙地土壤水分空间变异规律[J],生态学杂志 2003,22(6):43-48
[64]张继光,陈洪松,苏以荣等.湿润和干旱条件下喀斯特地区洼地表层土壤水分的空间变异性[J],应用生态学报,2006,17(12):2277-2282
[65]陈晓玲,龚威,李平湘等.遥感数字影像处理导论(第三版)[M].2007.北京:机械工业出版社,281-287
[66]赵鹏大.定量地学方法及应用[M],北京:高等教育出版社,2004,62-64
[67]徐建华.现代地理学中的数学方法[M],北京:高等教育出版社(第二版),2002,84-93
[68]钱允祺,陶士珩,王立祥,廖允诚等.土壤湿度的统计特征及应用分析[J].中国农业气象,1999,20(1):15-17
[2]肖斌,沙晋明.土壤水分遥感反演方法概述[J].遥感信息,2007.6:94-98
[3]王鹏新,龚健雅,李小文.条件植被指数及其在干早监测中的应用[J].武汉大学学报(信息科学版),2001,26(5):412-418.
[4]魏国栓,沈润平,丁国香.仪征地区农田深层土壤湿度遥感反演初探[J].遥感技术与应用,2008,23(1):36-41
[5]Pratt A,Ellyett C D.The thermal inertia approach to mapping of soil moisture and geology[J].Remote Sens Environ,1979,8:151-168
[6]姚春生,张增祥,汪潇.使用温度植被干旱指数法(TVDI)反演新疆土壤湿度[J].遥感技术与应用,2004,19(6):473-478.
[7]Watson K,Pohn H A.Thermal Inertia Mapping from Satellites Discrimination of Geologic Units in Oman[J].J Res Geol Suvr,1974,2(2):147-158
[8]Watson K,Rowen L C,Offield T W.Application of Thermal Modeling in the Geologic Interpretation of IR Images[J].Remote Sensing of Environment,1971,3,2017-2041.
[9]Price,J.C.Using spatial context in satellite data to infer regional scale evapotranspiration[J].IEEE Transactions on Geoscience and Remote Sensing,1990,28:940-948
[10]Goward,S.N,Xue,Y and Czajkowski,K.P.Evaluating land surface moisture conditions from the remotely sensed temperature/vegetation index measurements:An exploration with the simplified simple biosphere model[J].Remote Sensing of Environment,2002,79(2-3):225-242
[11]Sandholt,L.Rasmussen K.Andersen J.A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status[J].Remote Sensing of Enviromrent.2002,79:213-224
[12]张仁华.改进的热惯量模式及遥感土壤水分地理研究1990,19(2):101-112
[13]隋洪智,田国良.热惯量方法监测土壤水分.见:田国良主编.黄河流域典型地区遥感动态研究,北京:科学出版社,1990.
[14]田国良,杨希华,郑柯.冬小麦旱情遥感监测模型研究[J].环境遥感,1992,
[15]肖乾广,陈维英,盛永伟等.用气象卫星监测土壤水分的试验研究[J].应用气象学报1994.5(2):312-317
[16]余涛,田国良.热惯量法在监测土壤表层水分变化中的研究[J].遥感学报,1997,1(1):24-31
[17]隋洪智,田国良,李付琴.农田蒸散双层模型及其在干旱遥感监测中的应用[J].遥感学报,1997,1(3):220-224
[18]刘丽,周颖.用遥感植被供水指数监测贵州干旱,贵州气象,1998,122(6):17-21
[19]刘良云,张兵,郑兰芬.利用温度和植被指数进行地物分类和土壤水分反演[J],红外与毫米波学报,2002,21(4):269-273
[20]辛景峰.区域旱情遥感监测研究.中科院遥感应用研究所博士后研究工作报告,2003
[21]江苏省仪征县土壤志[M],南京:仪征县土壤普查办公室,1984,1-15
[22]邹源.不同地貌土壤属性空间变异研究,扬州大学硕士论文,2006
[23]赵鹏大.定量地学方法及应用,北京:高等教育出版社,2004,78-99
[24]汤国安,杨昕.ArcGIS地理信息系统空间分析实验教程,北京:科学出版社,2006363-422
[25]路鹏,彭佩钦,宋变兰等.洞庭湖平原土壤全磷含量地统计学和GIS分析[J],中国农业科学,2005,38(6):1204-1212
[26]Price J.C,Thermal inertia mapping:a new view of the Earth[J],J.Geophys Res,1977,82:2582-2590
[27]Price J.C,On the analysis of thermal infrared imagery:the Limited utility of apparent thermal inertia[J],Remote Sensing of Environment,1985,18(1),59-73
[28]Millard,J.P.,Jackson,R.D.,Crop water stress assessment using a airborne thermal scanner[J],Photog.Eng Rem Sens,1978,44,77-85
[29]Soer,G.J.R,Estimation of regional evapotranspiration and soil moisture conditions usingremotely sensed crop surface temperature[J],Remote Sensing of Environment,1980,9,27-45
[30]Jackson.R.D.Canopy temperature as a crop water stress indicator[J],Irrigation Science,1988,9:309-317
[31]郭铌.植被指数及其研究进展.干旱气象,2003,21(4),71-75
[32]于贵瑞.不同冠层类型的陆地植被蒸发散模型研究进展[J],资源科学,2001,23(6),72-84
[33]李亚春,王志华.我国干旱热红外遥感监测方法的研究进展[J].干旱地区农业研 究,1999,1(2)98-102
[34]佘万明,叶彩华.MODIS资料遥感监测土壤水分与干旱研究进展[J],河南气象,2006.144-46
[35]11.Fawwaz T.Ulaby,Percy P.Batlivala,Optimum Rada parameters for Mapping Soil Moisture,IEEE Transactions on Geoscience Electronics,1976,Vol.GE-14,No2,pp.81-93
[36]田国良.土壤水分的遥感监测方法[J].环境遥感,1991,6(2):89-98
[37]李杏朝.微波遥感监测十壤水分的研究初探[J],遥感技术与应用,1995,10(4):1-8
[38]Njoku E.Li L.Retrieval of Land Surface Parameters Using Passive Microwave Measurements at 6-18GHz[J],IEEE Trans Geosci Remote Sensing,1999,37(1):79-93
[39]杨虎.植被覆盖地表土壤水分变化雷达探测模型和应用研究,中国科学院研究生院博士学位论文,2003
[40]邓明弢,王宝珠.水分测定法(M),北京:高等教育出版社,1992.66-69
[41]http://edcimswww.cr.usgs.gov/pub/imswelcome/
[42]http://nfgis.nsdi.gov.cn/nfgis/chinese/c_xz.htm
[43]http://modis.gsfc.nasa.gov
[44]刘闯,葛成辉.美国对地观测系统(EOS)中分辨率成像光谱仪(MODIS)遥感数据的特点与应用[J].遥感信息2000.3:45-48
[45]马元喜.不同土壤对小麦根系生长动态的研究[J].作物学报,1987,3(1):37-44.
[46]邓辉,周清波.土壤水分遥感监测方法进展[J].中国农业资源与区划,2004,25(3):46-49.
[47]Nemani,R R,Pierce,L,Running,S.,and Goward,S.Developing satellite-derived estimates of surface moisture status[J].Journal of Applied Meteorology,1993,32(3):548557
[48]Nemani,R.Rurming,S.W.Estimation of regional surface resistance to evapotranspiration from NDVI and thermal IR AVHRR data[J].Journal of Applied Meteorology,1989,28:276-284
[49]Price,J.C.Using spatial context in satellite data to infer regional scale evapotranspiration [J].IEEE Transactions on Geoscience and Remote Sensing,1990,28:940-948
[50]强建华,赵鹏祥,陈国领.基于NDVI的油松天然林生长状况的遥感监测研究[J].西北林学院学报,2007,22(1):149-151.
[51]唐怡,刘良云,黄文江,王纪华.土壤背景对冠层NDVI的影响分析[J].遥感技术与应用,2006,21(2):142-148.
[52]钱允祺,陶士珩,王立祥等.土壤湿度的统计特征及应用分析[J].中国农业气象,1999,20(1):15-17
[53]赵鹏大.定量地学方法及应用,北京:高等教育出版社,2004,78-99
[54]汤国安,杨昕.ArcGIS地理信息系统空间分析实验教程[M],北京:科学出版社,2006363-422
[55]路鹏,彭佩钦,宋变兰等.洞庭湖平原土壤全磷含量地统计学和GIS分析[J],中国农业科学,2005,38(6):1204-1212
[56]邱扬,傅伯杰,王军等.土壤水分时空变异及其与环境因子的关系[J],生态学杂志,2007,26(1):100-107
[57]Andrew W.Westerna,Sen-Lin Zhou,Rodger B.Grayson,ThomasA.McMahon,Gunter Bloschlb,David J.Wilson.Spatial correlation of soil moisture in small catchments and its relationship to dominant spatial hydrological processes[J],Journal of Hydrology 2004 286,113-134
[58]Herbst M,Diekkruger B.Modeling the spatial variability of soil moisture in a micro-scale catchment and comparison with field data using geostatistics[J].Physics and Chemistry of the Earth,2003,28:239-245.
[59]刘继龙,张振华,谢恒星等.烟台果园表层土壤水分的时空分布及分形特征[J],土壤通报,2006,37(6):1076-1080
[60]尤文忠,曾德慧,刘明国等.黄土丘陵区林草景观界面雨后土壤水分空间变异规律[J]应用生态学报,2005,16(9):1591-1596
[61]刘鑫,毕华兴,李笑吟等.晋西黄土区基于地形因子的土壤水分分异规律研究[J],土壤学报,2007,44(3):411-417
[62]张俊斌,黄雍杰,梁大庆.不同坡地土壤水分分布变化之研究[J],水土保持研究,2007,14(1):301-304
[63]陈伏生,曾德慧,陈广生等.不同土地利用方式下沙地土壤水分空间变异规律[J],生态学杂志 2003,22(6):43-48
[64]张继光,陈洪松,苏以荣等.湿润和干旱条件下喀斯特地区洼地表层土壤水分的空间变异性[J],应用生态学报,2006,17(12):2277-2282
[65]陈晓玲,龚威,李平湘等.遥感数字影像处理导论(第三版)[M].2007.北京:机械工业出版社,281-287
[66]赵鹏大.定量地学方法及应用[M],北京:高等教育出版社,2004,62-64
[67]徐建华.现代地理学中的数学方法[M],北京:高等教育出版社(第二版),2002,84-93
[68]钱允祺,陶士珩,王立祥,廖允诚等.土壤湿度的统计特征及应用分析[J].中国农业气象,1999,20(1):15-17
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