盐渍土介电特性及模型改进研究

基于控制试验对配制的具有不同含水量和含盐量的土壤样本进行介电特征量测和分析,同时结合Stogryn盐水介电模型和土壤溶液离子浓度、电导率、含水量和含盐量等参数对介电常数虚部的影响,将饱和度这个关键参量引入盐渍土介电模型中,提高盐渍土介电模型模拟精度。结果表明：①当土壤体积含水量较低时,土壤含盐量对介电常数的实部和虚部均未产生明显的作用。当土壤体积含水量较高时,介电常数实部则随着土壤含盐量的增加呈逐渐下降趋势,介电常数虚部以增加态势为主;②修正后的盐渍土介电模型可以较好地刻画介电常数变化特征。此外,将修正后的模型在白银采样点进行验证,同样取得较好的模拟结果,表明修正后的盐渍土介电模型对不同土壤类型具有一定的适用性。     

Dielectric properties of salt-affected soils

A detailed laboratory experiment was conducted on three soils of different textures viz., sand, sandy clay loam and clay to study the influence of soil salinity and sodicity on the complex dielectric behaviour of soils as a function of volumetric soil moisture using an L-band (1 ·25 GHz) dielectric probe. The results revealed that soil salinity has no influence on the real part of the dielectric constant (?') whereas, the imaginary part (?'') is dependent and increases with increase in salinity for all the soils considered. It was found that the real part is more dependent on soil moisture and imaginary part on soil salinity. The sodicity of a soil has no influence either on real part or imaginary part. This study shows L-band (1·25 GHz) microwave response to soil salinity. It also demonstrates the possibility of separating saline soils from sodic soils at L-band frequencies under moist soil conditions.     

Comparative Analysis of Soil Water and Salt Dielectric Model

The soil dielectric constant，the basis of the microwave remote sensing inversion of soil water and salt，is one of the main parameters of microwave remote sensing research.It is very important to select the high precision soil water and salt dielectric model to improve the precision of soil water and salt inversion.However，the existing soil water and salt model still can’t quantitatively describe the effect of salt factor on soil permittivity.This paper simulates the complex permittivity of different texture，water content and salinity wet soil by Dobson model，Dobson\|S model，GRMDM model，HQR model and WYR model at L，Cand X bands when soil temperature equal 25 ℃.Comparison and analysis the simulation values with measured values by microwave vector network analyzer.The results show：(1)Dobson model and GRMDM model can accurately simulate the real part of dielectric constant of non\|saline soil，while the stimulated values of imaginary part is less than the measured values;(2)Dobson\|S model can well simulate the real part of the dielectric constant of saline soil，at L，C\nd Xbands the correlation coefficient R equal 0.97，the RMSE is less than 2.10.But for the imaginary part of the dielectric constant of saline soil，the Dobson\|S model，HQR model and WYR model with different simulation accuracy，when soil water content different.This study would benefit the choice of a suitable soil dielectric model for soil moisture and salinity retrieval.     

Modified Alex–Behari model for soil moisture as a function of salinity,texture and frequency

Alex and Behari obtained experimental soil moisture data at microwave frequencies and computed emissivity from these. Following this they suggested an empirical model which provides a good agreement up to a soil moisture value of 25%. Taking into consideration the soil texture, the modified Alex–Behari (MAB) model provides agreement with the available data up to 40%. A non-linear relationship between volumetric soil moisture and emissivity is obtained. The dielectric constant shows an increase with volumetric soil moisture. The dielectric properties of the soil are known to depend on soil moisture content along with other factors like salinity, texture and frequency. In the present investigations the experimental dielectric constant of various types of soils was taken in the frequency range (1.4–18.0 GHz) to fit the modified model in the given range of moisture content. The computed data show that the real part of the dielectric constant decreases and imaginary part increases with soil salinity. It is suggested that the proposed model will be of interest to agricultural scientists, and applicable to remote sensing of salt-affected areas.     

不同介电常数模型的平静海表面亮温仿真差异性分析

利用介电常数模型仿真平静海表面亮温是海洋盐度遥感反演的基础工作之一。利用Matlab软件对K-S模型、M-W模型和Bl模型3种介电常数模型进行了仿真。首先分析了3种介电常数的实部和虚部值随电磁波入射角变化的差异性,然后通过介电常数模型获得的3种平静海表面亮温,分析了在盐度为30～40psu以及不同入射角的情况下,3种介电常数模型得到的平静海表面亮温和盐度变化率的关系。研究结果表明,在L频段(1.4～1.427GHz),3种模型的差异主要体现在实部,K-S模型介电常数实部值相对于其他2个模型更高,电磁波衰减程度基本一致;在入射角为55°时,亮温与盐度的变化率差异最明显,3种模型的垂直极化亮温的变化率比水平极化亮温高30%左右。     

Evaluation of the Applicability of Different Dielectric Models for Soil Moisture Retrieval based on the Ground-based Radiometer Measurements

Based on soil moisture and freeze/thaw comprehensive experiments conducted at the north-eastern part of the Tibetan Plateau, the L-band brightness temperature, the in-situ soil moisture and temperature, vegetation leaf area index are measured simultaneously for the purpose of evaluating performances on forward brightness temperature simulation and soil moisture retrieval using four dielectric constant models, including Wang-Schmugge, Mironov, Dobson, and Four-Phase model. The forward brightness temperature simulations indicate that the difference of simulated brightness temperature between Wang schmugge model and the other three dielectric constant models is most significant at lower soil moisture content condition (soil moisture is less than 0.23 m3·m^-3) , nevertheless, the difference of Mironov model simulation is most significant in contrast with the ones of other three models at higher soil moisture condition (soil moisture is greater than 0.23 m3·m^-3). The practical retrieval of soil moisture from the ground-based radiometer measurements indicate that Wang-Schmugge model can effectively reduce the underestimation of soil moisture at the horizontal polarization, this resulted an improvement to the accuracy of retrieved soil moisture. Mironov model can reduce the underestimation of retrieved soil moisture at the vertical polarization. In accordance with a state-of-the-art parameterization scheme, the evaluation of performances of four dielectric constant models at the typical alpine meadow is potential for selecting optimum soil moisture retrieval by using soil dielectric model from space-borne L-band radiometer observation over the Tibetan Plateau     

基于地基微波辐射计数据评估不同土壤介电模型反演土壤湿度的适用性

以青藏高原开展的L波段地基微波辐射（ELBARA-III型）综合观测试验为依据,基于 \tau - \omega 辐射传输模型评估了Wang-Schmugge、Mironov、Dobson和 Four-Phase 4种土壤介电模型对L波段微波亮温模拟及土壤湿度反演的影响。结果表明：相同植被和粗糙度参数化方案条件下,4种土壤介电模型对微波亮温模拟存在明显差异,当土壤湿度小于0.23 m3·m^-3时,Wang-Schmugge模型与其他3种土壤介电模型微波亮温模拟结果差异最为显著,水平和垂直极化微波亮温模拟最大差值可达8.0 K和4.4 K;当模拟土壤湿度大于0.23 m3·m^-3时,Four-phase模型模拟的微波亮温显著高于其他3种土壤介电模型模拟结果;当土壤湿度饱和时,4种土壤介电模型间水平和垂直极化微波亮温模拟最大差值约为6.1 K和4.8 K,且4种土壤介电模型对水平极化微波亮温模拟的差异比垂直极化模拟的差异更为显著。而基于4种介电模型的土壤湿度反演对比试验表明,水平极化条件下基于Wang-Schmugge模型反演土壤湿度,较其他参数化方案,能有效减轻反演土壤湿度对观测土壤湿度的低估,Mironov模型减轻了垂直极化条件下反演土壤湿度对观测值的高估程度。在现有 \tau - \omega 模型参数化方案的基础上,总结了4种土壤介电模型在青藏高原典型草地下垫面的适用性,将为星载L波段辐射计青藏高原土壤湿度反演应用提供客观的土壤介电模型方案选取依据。     

吉林西部盐碱地特性微波双频差分无损探测

针对吉林西部盐碱地特性(内地苏打盐类型),应用车载双频段被动微波遥感系统,对不同盐碱状态的4个裸盐碱区进行双极化多角度微波辐射无损探测。基于多角度双频率双极化的观测数据优势,选择逼近式迭代算法来反演其介电常数虚部,Dobson模型反演介电常数实部。在此基础上,应用双频差分法研究了该区域盐碱地介电特性与含水量、含盐量的关系。双频差分结果表明:实部双频差分与盐碱土含水量呈线性关系,相关系数为0.9996;虚部双频差分与含盐量呈线性关系,相关系数为0.9977。这为应用被动微波遥感定量反演盐碱地特性(含水量、含盐量)奠定了理论基础。     

介电溶液测试土壤水分传感器性能的实证研究

利用土壤等效介电溶液代替土壤测试与评估土壤水分传感器的性能,具有便捷、快速的优点。为验证传感器在介电溶液中的测试结果是否与实际土壤中一致,利用去离子水和2—异丙氧基乙醇(2-isoproxyethanol)或二氧六环(dioxane)2种溶液混合,配制了一系列等效土壤体积含水率为0.9%~51.8%的待测介电溶液,同时取广州地区的典型红壤和雷州半岛的典型砖红壤,配制一系列与介电溶液等效含水率相对应的土样,分别从电气特性、与土壤含水率的函数关系、温度变异性和稳定性4个方面测试传感器的性能,并将介电溶液中的测试结果与2种土样中比较。实验结果表明:介电溶液中的测试结果与红壤和砖红壤中基本上一致,介电溶液在某种程度上可以代替土样进行土壤水分传感器的性能测试。     

GA-PLS方法提取土壤水盐光谱特征的精度分析

光谱定量遥感已成为土壤盐渍化大尺度调查的有效手段之一,但黄河三角洲地区盐渍化土壤的光谱响应特征尚未明确。以黄河三角洲野外测定土壤体积含水率、电导率为例,应用遗传偏最小二乘法(GA-PLS)在小样本集条件下提取盐渍土壤的水分-盐分的光谱响应特征,利用蒙特卡罗方法随机模拟结果表明:在不同土壤水盐含量条件下,GA-PLS方法所提取的光谱特征具有鲁棒性,含水率模型稳定在23个波段变量,即响应特征为365~425,500~515,720~740,755~765与955~965 nm;土壤电导率模型的特征集数目为20个波段变量,特征为370~385,405~425\,500~535,650~660,755~760与1 030~1 050 nm。实验在不同预处理模型下,GA-PLS算法所建立水盐光谱模型较PLSR模型均显示出更高的精度。其中,包络线预处理方法与GA-PLS算法相结合效果最优,其水分光谱模型测试集拟合精度(R²),预测残差平方和(PRSS)与残差预测方差(RPD)分别为0.88,9.36与15.80;土壤光谱模型测试集精度R²,PRSS与RPD分别为0.71,15.68与13.76。     

非接触式物料水分传感器

为实现固体物料水分含量的在线监测,设计了基于频域反射原理的非接触式物料水分传感器。该传感器基于固体状物料含水量与介电常数的关系,利用电容式探头对介电常数的测量能力,通过水分变化关系实验建立了容积含水量与介电常数的数学模型,并完成了传感器的结构设计和电路设计。实验结果表明:该传感器实现了对固体颗粒状物料水分的准确测量,满足物料水分测量的实际需求。     

Utilizing calibrated GPS reflected signals to estimate soil reflectivity and dielectric constant: Results from SMEX02

Extensive reflected GPS data was collected using a GPS reflectometer installed on an HC130 aircraft during the Soil Moisture Experiment 2002 (SMEX02) near Ames, Iowa. At the same time, widespread surface truth data was acquired in the form of point soil moisture profiles, areal sampling of near-surface soil moisture, total green biomass and precipitation history, among others. Previously, there have been no reported efforts to calibrate reflected GPS data sets acquired over land. This paper reports the results of two approaches to calibration of the data that yield consistent results. It is shown that estimating the strength of the reflected signals by either (1) assuming an approximately specular surface reflection or (2) inferring the surface slope probability density and associated normalization constants give essentially the same results for the conditions encountered in SMEX02. The corrected data is converted to surface reflectivity and then to dielectric constant as a test of the calibration approaches. Utilizing the extensive in-situ soil moisture related data this paper also presents the results of comparing the GPS-inferred relative dielectric constant with the Wang-Schmugge model frequently used to relate volume moisture content to dielectric constant. It is shown that the calibrated GPS reflectivity estimates follow the expected dependence of permittivity with volume moisture, but with the following qualification: The soil moisture value governing the reflectivity appears to come from only the top 1-2 cm of soil, a result consistent with results found for other microwave techniques operating at L-band. Nevertheless, the experimentally derived dielectric constant is generally lower than predicted. Possible explanations are presented to explain this result.     

SMEX02: Field scale variability, time stability and similarity of soil moisture

Evaluation of air- or space-borne remote sensors measuring soil moisture requires strategic ground-based sampling. As part of the Soil Moisture Experiment 2002 (SMEX02), daily surface soil moisture sampling at 90-140 locations were conducted in four fields in Walnut Creek watershed, Iowa. Various combinations of soils, vegetation, and topography characterize the fields. Depending on the field's characteristics and soil moisture content, 3-32 independent measurements were necessary to capture the field mean volumetric soil moisture with a ±2% bias and 95% confidence interval. Validation of the retrieved soil moisture products from the aircraft microwave instruments using the average of 14 samples per field is more appropriate for dry (<10% volumetric soil moisture) or wet (>25% volumetric soil moisture) range than for intermediate soil moisture range. Time stability analysis showed that an appropriately selected single sampling point could provide similar accuracy across a range of soil moisture conditions. Analyses based on landscape position (depression, hilltop, steep slope, and mild slope) showed that locations with mild slopes consistently exhibit time stable features. Hilltop and steep slope locations consistently underestimated mean field soil moisture. Soils parameters could not be used to identify time stable features as sampling locations with relatively high sand content consistently underestimated the field mean while those locations with relatively high clay content consistently overestimated the field mean. However, the slope position characterization of time stable features was enhanced using soils properties. The mild slope locations having the best time-stable features are those with moderate to moderately high clay content as compare to the field average (28-30% clay).     

基于LST-EVI特征空间的土壤水分含量反演

干旱是人类历史上的重大自然灾害之一,而土壤水分是干旱监测最重要的指标。利用遥感手段反演地表土壤水分,可以充分反映土壤水分的时空变化特征,适合进行大范围动态监测。研究基于Landsat TM数据,运用普适性单通道算法得到地表温度(LST,Land Surface Temperature),然后选用增强型植被指数(EVI,Enhanced Vegetation Index),构建了LST\|EVI特征空间,计算出温度植被干旱指数(TVDI,Temperature\|Vegetation Dryness Index)。在对实测土壤含水量数据和对应TVDI值进行回归分析的基础上,反演出2010年6月14日黄骅市自然地表20 cm深度处的体积含水量。结果表明:TVDI方法在该研究区是完全可行的,拟合精度较高;研究区自然地表土壤体积含水量分布差异明显,中等含水量地区面积最大,西南和部分北部地区含水量较低,而含水量高的区域主要分布在苇洼和沿海地区。     

基于FDR原理的自动灌溉系统设计

利用土壤的介电特性测量土壤含水量是一种快速、简便、可靠的方法。根据频域反射(FDR)法测量原理,电磁波在土壤中的传播频率可用来测试土壤的介电常数,从而得到土壤容积含水率,设计出了一种基于FDR原理的自动灌溉系统,介绍了FDR测量原理,阐述了自动灌溉系统的软硬件构成,土壤水分传感器测得的土壤水分含量信息,经信号处理,输出为0~5V电压信号,经A/D转换送至AT89S52单片机进行判断处理,根据输出数值的大小控制电磁阀的通断时间,从而实现自动灌溉和节水灌溉的目的。试验表明:该系统工作稳定,控制准确,反应灵敏,满足自动灌溉要求。     

Predicting water content using Gaussian model on soil spectra

This paper presents an approach to estimating soil moisture content through fitting an inverted Gaussian function to the continuum in soil spectra. The soil moisture Gaussian model (SMGM) estimates the water content by the declining reflectance in the near infrared (NIR) and shortwave infrared (SWIR) regions, 1.2-2.5 μm, due to the spreading of the fundamental water absorption at 2.8 μm. Convex hull boundary points were used to isolate the spectral continuum and to fit the inverted Gaussian function. The function extrapolates the continuum to the fundamental water absorption beyond the wavelength limits of common laboratory, field, and airborne instruments. Of the derived functional parameters, both amplitude and area on the shortwave side of the inverted Gaussian curve were highly correlated with soil water content.In this study, laboratory spectra, from 0.4 to 2.5 μm, were measured at sequential moisture levels in soil samples collected in Castilla-La Mancha, Spain and in California, USA. The Gaussian area was determined to be the best indicator of gravimetric water content with the initial modeling of 2592 spectra. The SMGM was validated with a separate set of 849 spectra. The model performance significantly improved for water contents below a critical level of 0.32 g water/g soil. Within this restricted range, the SMGM predicted water contents for all soils with a maximum of 0.027 RMSE for 1901 modeled spectra and 0.026 for 602 validation spectra. The water content estimates were improved slightly by stratifying the model and validation sets by the two locations, reducing the RMSE to 0.023 in Spain and 0.025 in California. Further stratifying the model spectra by landform and soil sodicity improved some predictions substantially, but less consistently. Stratifying the samples locally demonstrated that a priori knowledge of soil surfaces by landforms should be part of an image calibration strategy. The SMGM provides practical water content estimates and has a potential use in correcting the effects of soil moisture in hyperspectral images.     

Likelihood parameter estimation for calibrating a soil moisture model using radar bakscatter

Land surface model parameter estimation can be performed using soil moisture information provided by synthetic aperture radar imagery. The presence of speckle necessitates aggregating backscatter measurements over large (> 100 m × 100 m) land areas in order to derive reliable soil moisture information from imagery, and a model calibrated to such aggregated information can only provide estimates of soil moisture at spatial resolutions required for reliable speckle accounting. A method utilizing the likelihood formulation of a probabilistic speckle model as the calibration objective function is proposed which will allow for calibrating land surface models directly to radar backscatter intensity measurements in a way which simultaneously accounts for model parameter- and speckle-induced uncertainty. The method is demonstrated using the NOAH land surface model and Advanced Integral Equation Method (AIEM) backscatter model calibrated to SAR imagery of an area in the Southwestern United States, and validated against in situ soil moisture measurements. At spatial resolutions finer than 100 m × 100 m NOAH and AIEM calibrated using the proposed radar intensity likelihood parameter estimation algorithm predict surface level soil moisture to within 4% volumetric water content 95% of the time, which is an improvement over a 95% prediction confidence of 10% volumetric water content by the same models calibrated directly to soil moisture information derived from synthetic aperture radar imagery at the same scales. Results suggest that much of this improvement is due to increased ability to simultaneously estimate NOAH parameters and AIEM surface roughness parameters.     

L波段多角度裸露地表土壤水分反演研究

土壤水分是气象预报、农情监测以及水文模型的重要参数之一,利用被动微波遥感技术可以有效获取土壤水分。欧空局（ESA）计划于2009年发射卫星SMOS(Soil Moisture and Ocean Salinity) ,其主要目的是监测全球范围内的土壤水分和海洋盐度变化。根据SMOS的设置情况,寻找精度较高的半经验模型以便为进一步的土壤水分反演提供简化模型。对于裸露地表,地表粗糙度、土壤介电常数等因素影响最终的微波发射率。运用Dobson半经验介电常数模型计算土壤的介电常数,将计算结果输入高级积分方程模型(AIEM)。通过AIEM模拟的数据库,利用回归关系建立了一个精度相对较高的L波段多角度半经验模型。     

模拟月壤微波介电特性的初步研究

月壤微波介电常数的确定是我国未来绕月星载微波辐射计资料反演的前提,作者在野外采集大量地球玄武岩和斜长岩样品的基础上配制了9个模拟月壤样品。并制成0．8g／cm^3、1．0g／cm^3、1．2g／cm^3、1．4g／cm^3和1．6g／cm^3 5个密度等级．在500MHz～20GHz的频率范围内,用同轴线终端开路法在HP8722C矢量网络分析仪上对其介电常数进行了系统测量,并用计算机方法对测量结果进行了综合处理和统计分析。结果表明,密度、频率和组分对介电常数都有显著影响。但以密度的作用最为强烈,频率次之,组分最弱;介电常数实部随密度的增加而线性增加。随频率的增加而线性减少;虚部则无论密度还是频率增加都呈增大趋势．但低于10GHz时,虚部和二者之间基本为线性关系,高于10GHz时,规律性变差;组分对介电常数的作用较为复杂,二者之间很大程度上不遵循简单的函数关系。样品主元素氧化物SiO2、Al2O3、CaO、MgO、TiO2和△Fe百分含量的多元回归显示,它们和介电常数之间倾向于符合一个多元一次函数,Ti和Fe氧化物未表现出其在对介电常数贡献上的特征组分的作用。     

Comparison of different soil dielectric models for microwave soil moisture retrievals

ABSTRACT

Soil dielectric model is an essential part of the microwave soil moisture retrieval process. This study compared the performance of four widely used dielectric models, the Wang-Schmugge model (WS), Dobson model, generalized refractive mixing dielectric model (GRMDM), and multi-relaxation generalized refractive mixing dielectric model (MRGRMDM), and investigated the effects of the uncertainties of each model on soil moisture retrievals. Furthermore, the simulated soil dielectric constants were evaluated by measured dielectric data at the P/L/C/X bands. The results showed that the uncertainties induced in soil moisture retrievals by an alternative dielectric model exceeded 0.09 m³ m^?3 in the worst case. The Dobson model is sensitive to the sand content. WS, GRMDM, and MRGRMDM model are sensitive to the clay content. The measured dielectric data further verified that the applicability of each dielectric model depends on the soil texture type and soil moisture condition. Compared with Dobson model, WS showed better performance at dry soil. GRMDM and MRGRMDM provided better results under lower clay content soil. Especially, MRGRMDM has better simulation accuracy than GRMDM in the low-frequency range (< 1 GHz).