The SIR-B Observations of Microwave Backscatter Dependence on Soil Moisture, Surface Roughness, and Vegetation Covers

An experiment was conducted from an L-band syntheticaperture perture radar aboard space shuttle Challenger in October 1984 to study the microwave backscatter dependence on soil moisture, surface roughness, and vegetation cover. The results based on the anlyses of an image obtained at 21° incidence angle show a positive correlation between scattering coefficient and soil moisture content, with a sensitivity comparable to that derived from the ground radar measurements [1]. The surface roughness strongly affects the microwave backscatter. A factor of 2 change in the standard deviation of surface roughness height gives a corresponding change of about 8 dB in the scattering coefficient. The microwave backscatter also depends on the vegetation types. Under the dry soil conditions, the scattering coefficient is observed to change from about -24 dB for an alfalfa or lettuce field to about -17 dB for a mature corn field. These results suggest that observations with a synthetic-aperture radar system of multiple frequencies ies and polarizations are required to unravel the effects of soil ture,oisre, surface roughness, and vegetation cover.     

Multifrequency Measurements of the Effects of Soil Moisture, Soil Texture, And Surface Roughness

An experiment on remote sensing of soil moisture content was conducted over bare fields with microwave radiometers at the frequencies of 1.4, 5, and 10.7 GHz, during July-September of 1981. Three bare fields with different surface roughnesses and soil textures were prepared for the experiment. Ground-truth acquisition of soil temperatures and moisture contents for 5 layers down to the depths of 15 cm was made concurrently with radiometric measurements. The experimental results show that the effect of surface roughness is to increase the soil's brightness temperature and to reduce the slope of regression between brightness temperature and moisture content. The slopes of regression for soils with different textures are found to be comparable and the effect of soil texture is reflected in the difference of regression line intercepts at brightness-temperature axis. The result is consistent with laboratory measurement of soil's dielectric permittivity. Measurements on wet smooth bare fields give lower brightness temperatures at 5 than at 1.4 GHz. This phenomenon is not expected from current radiative transfer theory, using laboratory measurements of the relationship between dielectric permittivity and moisture content for different soil-water mixtures at frequencies of <5 GHz.     

Microwave Bistatic Reflectivity Dependence on the Moisture Content And Matric Potential of Bare Soil

Results are presented of an experimental program to determine the functional dependence of the microwave reflectivity of nonvegetated soil surfaces upon volumetric soil moisture and matric potential. A combination evaporation-drainage field experiment was conducted on a bare Captina silt loam with reflectivity, soil moisture content, and matric potential monitored for extended time periods. Results show that for a restricted pressure range (approximately -0.05 to -0.75 bar) there is excellent linear correlation between the log of bistatic reflectivity and both volumetric moisture content and matric potential. Layering effects due to steep moisture content (and matric potential) gradients in the profile are demonstrated to have two distinct and significant effects on the reflectivity response. At near saturation of rough surfaces a very thin dry surface layer appears to modify the effective roughness. This leads to a saturation of reflectivity at high moisture contents. As the surface proceeds to dry further, deeper layers produce coherent interference patterns in the reflectivity response, particularly at the higher frequencies.     

Soil Moisture Information And Thermal Microwave Emission

This paper presents theoretical and experimental results that demonstrate the depth to which soil moisture can be directly measured using microwave radiometers. The experimental results also document the effect of uniform surface roughness on the response of thermal microwave emission to soil moisture. Experimental measurements were executed in July 1980 at the Texas A&M University Research Farm near College Station, TX. Thermal microwave emission measurements were made at 1.4, 4.9, and 10.7 GHz at both vertical and horizontal polarization at off nadir angles from 0 to 50°. It has been demonstrated that passive microwave measurements at frequencies down to 1.4 GHz can only measure soil moisture directly to very shallow soil depths, approximately 2 cm. This is due to the fact that the soil moisture dependence of the transmission coefficient across the air-soil interface predominates over the soil moisture dependence of the total energy originating within the soil volume. It also has been demonstrated that the combination of low incident angle and measurement frequency in the C-band range does not minimize the effect of surface roughness for passive microwave measurements. This result is significant in view of the fact that this combination of frequency and incident angle has been described as the optimum combination for minimizing the effect of surface roughness on the response of radar-backscatter measurements to soil moisture.     

Utilization of Active Microwave Roughness Measurements to Improve Passive Microwave Soil Moisture Estimates Over Bare Soils

Investigators have researched operational microwave techniques for the remote estimation of soil moisture for sometime now. Both active and passive microwave sensors respond to variations in soil moisture, but also respond to vegetation and roughness parameters. This has led to research in multisensor techniques which account for the interference. Previously, techniques have been developed which used visible and infrared bands (similar to Landsat) to compensate for the vegetation masking on the L-band passive radiometer's response to soil moisture. In contrast, this study compensates for the surface roughness effect by using microwave scatterometer data on the same L-band radiometer. It was found that the L-band radiometer's capability to estimate soil moisture over bare fields was significantly improved when surface roughness was accounted for with scatterometers.     

Effects of Varying Soil Moisture Contents And Vegetation Canopies on Microwave Emissions

This paper presents an analysis of radiometric data taken at 21, 2.8, and 1.67 cm during a NASA sponsored flight over agricultural fields in Phoenix, AZ. The objective of the mission was to provide comprehensive information concerning microwave responses due to a broad range of soil moisture contents. Generally, data taken over bare fields agree well with theoretical estimates from a combined multilayer radiative transfer model with simple roughness correction. With the surface moisture content ranging between <5 and >35 percent, the emissivity ranges between >0.9 and ~0.7. The response to soil moisture content at 21 cm is more senstive than that at either 2.8 or 1.67 cm. The vegetation model takes into account both the effect of dielectric coefficient and the volume scattering characteristics of the vegetation layer. At the longer wavelengths (e.g., 21 cm) radiation from soil penetrates through vegetation layers of wheat and alfalfa and provides surface moisture information. However, short wavelength radiation from soil cannot penetrate through vegetation canopies; the volume scattering characteristics of vegetation controls the overall microwave signatures.     

FOSMEX: Forest Soil Moisture Experiments With Microwave Radiometry

The microwave Forest Soil Moisture Experiment (FOSMEX) was performed at a deciduous forest site at the Research Centre Julich (Germany). An L- and an X-band radiometer were mounted 100 m above ground and directed to the canopy. The measurements consist of dual- and single-polarized L- and X-band data and simultaneously recorded ground moisture, temperature, and meteorological data. The canopy L-band transmissivity was estimated from a subset of the FOSMEX data, where the ground was masked with a metalized foil. For the foliage-free canopy, the reflecting foil diminished the L-band brightness by ap24 K, whereas brightness increased by ap14 K when the foil was removed from below the foliated canopy. Depending on the assumption made on the scattering albedo of the canopy, the transmissivities were between 0.2 and 0.51. Furthermore, the contribution of the foliage was quantified. Although, the evaluation revealed the semitransparency of the canopy for L-band frequencies, the brightness sensitivity with respect to ground moisture was substantially reduced for all foliation states. The effect of ground surface moisture was explored in an irrigation experiment. The L-band measurements were only affected for a few hours until the water drained through the litter layer. This emphasizes the significance of the presence of litter for soil moisture retrieval from remotely sensed L-band brightness data. The FOSMEX database serves for further testing and improving radiative transfer models used for interpreting microwave data received from future spaceborne L-band radiometers flying over areas comprising a considerable fraction of deciduous forests.     

A Parameterization of the Effect of Surface Roughness on Microwave Emission

A simple model is developed to represent the net effect of surface roughness on the microwave emission from soils. The reflectivity of a rough soil surface is defined in a theoretical model that includes both coherent and incoherent reflectivities in terms of the statistical properties of the rough surface, i.e., the surface height standard deviation ? and its horizontal correlation length l. It is shown that the rough surface reflectivity obtained from this theoretical model can be presented in a form that is simply the reflectivity Ro of a smooth surface attenuated by a "rough thickness" G. It is found that the rough thickness G can be parameterized as a function of the statistical slope ratio m (=?/l) of a rough surface by a simple power-law relationship. Since the slope of a rough surface can be determined experimentally, the rough thickness G can be quantitatively estimated from the parametric representation. Model calculations show that this simple model can provide reasonably accurate results of predicted brightness temperatures that agree well with field measurements within experimental uncertainty.     

Comparison of Three in Situ Surface Soil Moisture Measurements And Application to C-Band Scatterometer Calibration

C-band scatterometers can be used to measure the surface soil moisture. This technique does not directly give the water content and a signal calibration is necessary. This is done by comparing the scatterometer signal (expressed as a scattering cross section per unit area) to gravimetric samples. The gravimetric sample calibration takes a lot of time and people, hence it is not adapted to airborne or satellite remote-sensing measurements. In this paper, new automatic equipment based on the measurement of the real part of the complex permittivity of moist soil is presented. The results of a one-month experiment show that this technique is well adapted to the automatic monitoring of soil moisture in general. In particular, it can be used for the calibration of microwave remote-sensing equipment.     

Uncertainties Associated With the Surface Texture of Ice Particles in Satellite-Based Retrieval of Cirrus Clouds—Part I: Single-Scattering Properties of Ice Crystals With Surface Roughness

Surface roughness of ice crystals is a morphological parameter important to the scattering characteristics of these particles. The intent of this paper, reported in two parts (hereafter, Parts I and II), is to investigate the accuracy associated with some simplifications in calculating the single-scattering properties of roughened ice crystals and to quantify the effect of surface roughness on the retrieval of the optical and microphysical properties of ice clouds from satellite observations. In Part I, two ray-tracing schemes, a rigorous algorithm and an approximate algorithm with a simplified treatment of surface roughness, are employed to calculate the single-scattering properties of randomly oriented hexagonal ice crystals with size parameters in the geometric optics regime. With the rigorous approach, it requires substantial computational effort to accurately account for the multiple external reflections between various roughness facets and the reentries of outgoing rays into the particles in the ray-tracing computation. With the simplified ray-tracing scheme, the ray-tracing calculation for roughened particles is similar to that for smooth particles except that, in the former case, the normal of the particle surface is statistically perturbed for each reflection-refraction event. The simplified ray-tracing scheme can account for most the effects of surface roughness on particle single-scattering properties without incurring substantial demand on computational resources and, thus, provides an efficient way to compute the single-scattering properties of roughened particles. The effect of ice-crystal surface roughness on the retrieval of the optical thicknesses and effective particle sizes of cirrus clouds is reported in Part II.     

Effects of Vegetation Cover on the Microwave Radiometric Sensitivity to Soil Moisture

The reduction in sensitivity of the microwave brightness temperature to soil moisture content due to vegetation cover is analyzed using airborne observations made at 1.4 and 5 GHz. The data were acquired during six flights in 1978 over a test site near Colby, Kansas. The test site consisted of bare soil, wheat stubble, and fully mature corn fields. The results for corn indicate that the radiometric sensitivity to soil moisture S decreases in magnitude with increasing frequency and with increasing angle of incidence (relative to nadir).The sensitivity reduction factor, defined in terms of the radiometric sensitivities for bare soil and canopy-covered conditions Y=1 - Scan/ Ss was found to be equal to 0.65 for normal incidence at 1.4 GHz, and increases to 0.89 at 5 GHz. These results confirm previous conclusions that the presence of vegetation cover may pose a serious problem for soil moisture detection with passive microwave sensors.     

利用主被动遥感数据估算土壤湿度和粗糙度的新方法

土壤的散射和热辐射特性与土壤表面的粗糙度及含水量密切相关。利用本文给出的结果，可方便地由主被抽感的实验数据推断地表的湿度和粗糙度。     

Passive Microwave Remote Sensing of Soil Moisture: The Effect of Tilled Row Structure

The tilled row structure is known to be one of the important factors affecting the observations of the microwave emission from a natural surface. Measurements of this effect were carried out with both L-and X-band radiometers mounted on a mobile truck on a bare 40 m × 45 m row tilled field. The soil moisture content during the measurements ranged from ~10 to ~30 percent by dry weight. The results of these measurements showed that the variations of the antenna temperatures with incident angle ? changed with the azimuthal angle ? measured from the row direction. In particular, at ? = 0° and ? ? 45°, the observed horizontally and vertically polarized antenna temperatures, TBH(?, ?) and TBV(?, ?), were not equal. In general, TBH(?°, ?) > TBV(?°, ?) when 0° ? ? < 45° and TBH(?°, ?) < TBV(0°, ?) when 45° < ? ? 90°. The difference between TBH(0°, ?) and TBV(0°, ?) was observed to decrease with ? approaching 45° and/or with soil moisture content. A numerical calculation based on a composite surface roughness-a small-scale RMS height variations superimposed on a large periodic row structure-was made and found to predict the observed features within the model's limit of accuracy. It was concluded that the difference between TBV(0°, ?) and TBH(0°, ?) was due to the change in the local angle of field emission within the antenna field of view caused by the large-scale row structure.     

Using ENVISAT ASAR Global Mode Data for Surface Soil Moisture Retrieval Over Oklahoma, USA

The advanced synthetic aperture radar (ASAR) onboard of the satellite ENVISAT can be operated in global monitoring (GM) mode. ASAR GM mode has delivered the first global multiyear C-band backscatter data set in HH polarization at a spatial resolution of 1 km. This paper investigates if ASAR GM can be used for retrieving soil moisture using a change detection approach over large regions. A method previously developed for the European Remote Sensing (ERS) scatterometer is adapted for use with ASAR GM and tested over Oklahoma, USA. The ASAR-GM-derived relative soil moisture index is compared to 50-km ERS soil moisture data and pointlike in situ measurements from the Oklahoma MESONET. Even though the scale gap from ASAR GM to the in situ measurements is less pronounced than in the case of the ERS scatterometer, the correlation for ASAR against the in situ measurements is, in general, somewhat weaker than for the ERS scatterometer. The analysis suggests that this is mainly due to the much higher noise level of ASAR GM compared to the ERS scatterometer. Therefore, some spatial averaging to 3–10 km is recommended to reduce the noise of the ASAR GM soil moisture images. Nevertheless, the study demonstrates that ASAR GM allows resolving spatial details in the soil moisture patterns not observable in the ERS scatterometer measurements while still retaining the basic capability of the ERS scatterometer to capture temporal trends over large areas.      

Monte Carlo Simulation of the Effect of Soil Moisture Variation on the Microwave Emission from Soils

In this paper, results of a Monte Carlo simulation of the effect of noise on the relationship between the microwave emissivity of soil and its moisture content are presented. It is found that whenever the magnitude of the noise for the independent variable, in this case the soil moisture, is increased, both the slope of the regression and the correlation coefficient decrease. In párticular, when the noise has a magnitude equivalent to a coefficient of variation of 0.25, the slope and correlation coefficient are in good agreement with those obtained from the data of a 21-cm airborne microwave radiometer which was flown over a test site in Hand County, South Dakota. The comparison was made using a linear relationship to determine the estimated emissivity from the ground measurements of soil moisture. The linear relationship was derived from a radiative transfer model calculation of the microwave emissivities using realistic soil-moisture profiles. The effect of surface roughness was included in the relationship, and the variability of the surface roughness was also simulated by a Monte Carlo technique.     

Impact of Multiresolution Active and Passive Microwave Measurements on Soil Moisture Estimation Using the Ensemble Kalman Smoother

An observing system simulation experiment is developed to test tradeoffs in resolution and accuracy for soil moisture estimation using active and passive L-band remote sensing. Concepts for combined radar and radiometer missions include designs that will provide multiresolution measurements. In this paper, the scientific impacts of instrument performance are analyzed to determine the measurement requirements for the mission concept. The ensemble Kalman smoother (EnKS) is used to merge these multiresolution observations with modeled soil moisture from a land surface model to estimate surface and subsurface soil moisture at 6-km resolution. The model used for assimilation is different from that used to generate "truth." Consequently, this experiment simulates how data assimilation performs in real applications when the model is not a perfect representation of reality. The EnKS is an extension of the ensemble Kalman filter (EnKF) in which observations are used to update states at previous times. Previous work demonstrated that it provides a computationally inexpensive means to improve the results from the EnKF, and that the limited memory in soil moisture can be exploited by employing it as a fixed lag smoother. Here, it is shown that the EnKS can be used in large problems with spatially distributed state vectors and spatially distributed multiresolution observations. The EnKS-based data assimilation framework is used to study the synergy between passive and active observations that have different resolutions and measurement error distributions. The extent to which the design parameters of the EnKS vary depending on the combination of observations assimilated is investigated     

基于Sentinel-1/2遥感数据的冬小麦覆盖地表土壤水分协同反演

冬小麦是我国重要粮食作物之一,对冬小麦覆盖地表土壤水分进行监测有助于解决因土壤供水导致的冬小麦歉收和农业用水浪费等问题.为了降低冬小麦覆盖地表土壤水分微波遥感反演过程中冬小麦对雷达后向散射系数的影响,该文基于Sentinel-1携带的合成孔径雷达(SAR)数据和Sentinel-2携带的多光谱成像仪(MSI)数据,结合水云模型,开展冬小麦覆盖地表土壤水分协同反演研究.首先,基于MSI数据,该文定义了一种新的植被指数,即融合植被指数(FVI),用于冬小麦含水量反演;然后,该文发展了一种基于主被动遥感数据的冬小麦覆盖地表土壤水分反演半经验模型,校正冬小麦在土壤水分反演过程中对雷达后向散射系数的影响;最后,以河南省某地冬小麦农田为研究区域,开展归一化水体指数(NDWI)和FVI两种指数与VV,VH,VV/VH 3种极化组合而成的6种反演方式下的土壤水分反演对比实验.结果表明:以FVI为植被指数,能够更好地去除冬小麦在土壤水分反演过程中对雷达后向散射系数的影响;6种反演方式中,FVI与VV/VH组合下的反演效果最优,其决定系数为0.7642,均方根误差为0.0209 cm3/cm3,平均绝对误差为0.0174 cm3/cm3,展示了该文所提土壤水分反演模型的研究价值和应用潜力.