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.     

Subpixel variability of remotely sensed soil moisture: aninter-comparison study of SAR and ESTAR

The representation of subpixel variability in soil moisture estimates from passive microwave data was investigated through sensitivity analysis and by comparison against the spatial structure of soil moisture fields derived from radar data. This work shows that the subpixel variability not represented in brightness temperature fields is directly associated with the spatial organization of soil hydraulic properties and the spatial distribution of vegetation. The significant implication of this result is that the physical connection between soil moisture estimates at the pixel scale and local values within the pixel weakens strongly as the sensor resolution decreases. Subsequently, the application of scaling and fractal interpolation principles to downscale passive microwave data to the spatial resolution of radar data was investigated as a means to recover spatial structure. In particular, ESTAR soil moisture data was successfully downscaled from 200 to 40 m using only one radar frequency (e.g., L-band). This application suggests that the combined use of active and passive single-band microwave remote-sensing of soil moisture is a viable approach to improve the spatial resolution of soil moisture remote-sensing     

The NAFE'05/CoSMOS Data Set: Toward SMOS Soil Moisture Retrieval, Downscaling, and Assimilation

The National Airborne Field Experiment 2005 (NAFE'05) and the Campaign for validating the Operation of Soil Moisture and Ocean Salinity (CoSMOS) were undertaken in November 2005 in the Goulburn River catchment, which is located in southeastern Australia. The objective of the joint campaign was to provide simulated Soil Moisture and Ocean Salinity (SMOS) observations using airborne L-band radiometers supported by soil moisture and other relevant ground data for the following: (1) the development of SMOS soil moisture retrieval algorithms; (2) developing approaches for downscaling the low-resolution data from SMOS; and (3) testing its assimilation into land surface models for root zone soil moisture retrieval. This paper describes the NAFE'05 and CoSMOS airborne data sets together with the ground data collected in support of both aircraft campaigns. The airborne L-band acquisitions included 40 km times 40 km coverage flights at 500-m and 1-km resolution for the simulation of a SMOS pixel, multiresolution flights with ground resolution ranging from 1 km to 62.5 m, multiangle observations, and specific flights that targeted the vegetation dew and sun glint effect on L-band soil moisture retrieval. The L-band data were accompanied by airborne thermal infrared and optical measurements. The ground data consisted of continuous soil moisture profile measurements at 18 monitoring sites throughout the 40 km times 40 km study area and extensive spatial near-surface soil moisture measurements concurrent with airborne monitoring. Additionally, data were collected on rock coverage and temperature, surface roughness, skin and soil temperatures, dew amount, and vegetation water content and biomass. These data are available at www.nafe.unimelb.edu.au.     

High-resolution change estimation of soil moisture using L-band radiometer and Radar observations made during the SMEX02 experiments

The soil moisture experiments held during June-July 2002 (SMEX02) at Iowa demonstrated the potential of the L-band radiometer (PALS) in estimation of near surface soil moisture under dense vegetation canopy conditions. The L-band radar was also shown to be sensitive to near surface soil moisture. However, the spatial resolution of a typical satellite L-band radiometer is of the order of tens of kilometers, which is not sufficient to serve the full range of science needs for land surface hydrology and weather modeling applications. Disaggregation schemes for deriving subpixel estimates of soil moisture from radiometer data using higher resolution radar observations may provide the means for making available global soil moisture observations at a much finer scale. This paper presents a simple approach for estimation of change in soil moisture at a higher (radar) spatial resolution by combining L-band copolarized radar backscattering coefficients and L-band radiometric brightness temperatures. Sensitivity of AIRSAR L-band copolarized channels has been demonstrated by comparison with in situ soil moisture measurements as well as PALS brightness temperatures. The change estimation algorithm has been applied to coincident PALS and AIRSAR datasets acquired during the SMEX02 campaign. Using AIRSAR data aggregated to a 100-m resolution, PALS radiometer estimates of soil moisture change at a 400-m resolution have been disaggregated to 100-m resolution. The effect of surface roughness variability on the change estimation algorithm has been explained using integral equation model (IEM) simulations. A simulation experiment using synthetic data has been performed to analyze the performance of the algorithm over a region undergoing gradual wetting and dry down.     

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.     

Microwave L-band emission of freezing soil

We report on field-measured microwave emission in a period of frost penetration into a grassland soil. The measurements were recorded with a high temporal resolution using an L-band radiometer mounted on a 7-m high tower. The observation period (December 2002 to March 2003) included two cycles of soil freezing and thawing with maximum frost depth of 25 cm. In situ soil temperature and liquid water content were measured at five depths down to 45 cm. Soil moisture profiles were calculated using the COUP numerical soil water and heat model in combination with measured soil properties and meteorological data monitored at the site. The L-band radiation data clearly showed the penetration and thawing of seasonal soil frost. We calculated soil reflectivities based on in situ measured and modeled soil moisture profiles by applying a coherent radiative transfer model. The calculated reflectivities were compared with the radiometrically determined soil reflectivities. It was demonstrated that the quantitative consistency between these reflectivities was significantly improved by applying an impedance matching approach accounting for surface effects. In this particular case, the dielectric structure of the uppermost soil horizon was largely influenced by soil roughness, vegetation, and snow cover. The radiometrically measured soil reflectivities were fitted using a radiative transfer model in combination with a roughness model assuming a soil surface roughness of 25 mm. The analysis during a period of frost penetration shows coherent behavior of the soil reflectivity. Temporal oscillation of the measured L-band radiation appears to be a coherent effect. This effect has the potential to be used for estimating the frost penetration velocity.     

Attenuation of soil microwave emission by corn and soybeans at 1.4and 5 GHz

Theory and experiments have shown that passive microwave radiometers can be used to measure soil moisture. However, the presence of a vegetative cover alters the measurement that might be obtained under bare conditions. Two significant obstacles to the practical use of this approach are deterministically accounting for the effect of vegetation; and developing algorithms for extracting soil moisture from observations of a vegetation-soil complex. The presence of a vegetation canopy reduces the sensitivity of passive microwave instruments to soil moisture variations. Data collected using truck-mounted microwave radiometers were used to examine the specific effects of corn and soybean canopies     

Ground-based passive microwave remote sensing observations of soilmoisture at S-band and L-band with insight into measurementaccuracy

A ground-based experiment in passive microwave remote sensing of soil moisture was conducted in Huntsville, AL, from July 1-14, 1996. The goal of the experiment was to evaluate the overall performance of an empirically-based retrieval algorithm at S-band and L-band under a different set of conditions and to characterize the site-specific accuracy inherent within the technique. With high temporal frequency observations at S-band and L-band, the authors were able to observe large scale moisture changes following irrigation and rainfall events, as well as diurnal behavior of surface moisture among three plots, one bare, one covered with short grass and another covered with alfalfa. The L-band emitting depth was determined to be on the order of 0-3 or 0-5 cm below 0.30 cm³/cm³ with an indication that it is less at higher moisture values. The S-band emitting depth was not readily distinguishable from L-band. The uncertainty in remotely sensed soil moisture observations due to surface heterogeneity and temporal variability in variables and parameters was characterized by imposing random errors on the most sensitive variables and parameters and computing the confidence limits on the observations. Discrepancies between remotely sensed and gravimetric soil moisture estimates appear to be larger than those expected from errors in variable and parameter estimation. This would suggest that a vegetation correction procedure based on more dynamic modeling may be required to improve the accuracy of remotely sensed soil moisture     

The L-band PBMR measurements of surface soil moisture inFIFE

The NASA Langley Research Center's L-band pushbroom microwave radiometer (PBMR) aboard the NASA C-130 aircraft was used to map surface soil moisture at and around the Konza Prairie Natural Research Area in Kansas during the four intensive field campaigns of FIFE in May-October 1987. A total of 11 measurements were made when soils were known to be saturated. This measurement was used for the calibration of the vegetation effect on the microwave absorption. Based on this calibration, the data from other measurements on other days were inverted to generate soil moisture maps. Good agreement was found when the estimated soil moisture values were compared with those independently measured on the ground at a number of widely separated locations. There was a slight bias between the estimated and measured values, the estimated soil moisture on the average being lower by about 1.8%     

Remote Sensing of Soil Moisture: Recent Advances

In the past few years there have been many advances in our understanding of microwave approaches for the remote sensing of soil moisture. These advances include a method for estimating the dependence of the soil's dielectric constant on its texture; the use of percent of field capacity to express soil moisture magnitudes independently of soil texture; experimental and theoretical estimates of the soil moisture sampling depth; models for describing the effect of surface roughness on the microwave response in terms of surface height variance and the horizontal correlation length; verification of the ability of radiative transfer models to predict the microwave emission from soils; and experimental and theoretical estimates of the effects of vegetation on the microwave response to soil moisture. This research has demonstrated that it is possible to remotely sense soil moisture in the surface layer of the soil (about 0-5 cm). In addition there have been simulation studies indicating how remotely sensed surface soil moisture may be used to estimate evapotranspiration rates and root-zone soil moisture.     

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.     

Multispectral Remote Sensing of Saline Seeps

An aircraft experiment was conducted in early summer of 1981 to determine the feasibility of optical and microwave remote sensing techniques for the detection of fully developed and incipient saline seeps in South Dakota and Montana. The NASA C-130 earth resources aircraft was used to acquire L-band and C-band scatterometer data (backscattering coefficient profiles), radiometer data (brightness temperature profiles), and color-infrared photography; additional passive microwave data and thermal images were acquired by the L- band radiometer on the Beechcraft D-18 aircraft operated by South Dakota State University. Intensive soil moisture and salinity data were collected on a uniform 20-m grid spacing and at several depths for the 600 × 600 m South Dakota site. The two Montana sites were over-flown with flight lines several kilometers in length, and ground truth information was obtained by identifying known geological and geohydrological units with varying soil salinities on a regional basis. The C-130 radiometers (both L- and C-bands) were effective in detecting wet soil areas including fully developed seeps; however, incipient seeps were not accurately detected by the radiometers. The D-18 L-band radiometer data did not appear to be sensitive to soil wetness. The C-130 scatterometer data profiles, although showing some sensitivity to soil moisture, were greatly influenced by surface roughness and appear to be ineffective in accurately delineating either fully developed or incipient seeps. Thermal-IR scanner data acquired by the D-18 aircraft did not appear to provide a reliable means for identifying potential seeps.     

A semiempirical model for interpreting microwave emission fromsemiarid land surfaces as seen from space

A radiative transfer model for simulating microwave brightness temperatures over land surfaces is described. The model takes into account sensor viewing conditions (spacecraft altitude, viewing angle, frequency, polarization) and atmospheric parameters over a soil surface characterized by its moisture, roughness, and temperature and covered with a layer of vegetation characterized by its temperature, water content, single scattering albedo, structure and percent coverage. In order to reduce the influence of atmospheric and surface temperature effects, the brightness temperatures are expressed as polarization ratios that depend primarily on the soil moisture and roughness, canopy water content, and percentage of cover. The approach used is described, and the sensitivity of the polarization ratio to these parameters is investigated. Simulation of the temporal evolution of the microwave signal over semiarid areas in the African Sahel is presented and compared to actual satellite data from the SMMR instrument on Nimbus-7     

Parameter sensitivity of soil moisture retrievals from airborne L-band radiometer measurements in SMEX02

Over the past two decades, successful estimation of soil moisture has been accomplished using L-band microwave radiometer data. However, remaining uncertainties related to surface roughness and the absorption, scattering, and emission by vegetation must be resolved before soil moisture retrieval algorithms can be applied with known and acceptable accuracy using satellite observations. Surface characteristics are highly variable in space and time, and there has been little effort made to determine the parameter estimation accuracies required to meet a given soil moisture retrieval accuracy specification. This study quantifies the sensitivities of soil moisture retrieved using an L-band single-polarization algorithm to three land surface parameters for corn and soybean sites in Iowa, United States. Model sensitivity to the input parameters was found to be much greater when soil moisture is high. For even moderately wet soils, extremely high sensitivity of retrieved soil moisture to some model parameters for corn and soybeans caused the retrievals to be unstable. Parameter accuracies required for consistent estimation of soil moisture in mixed agricultural areas within retrieval algorithm specifications are estimated. Given the spatial and temporal variability of vegetation and soil conditions for agricultural regions it seems unlikely that, for the single-frequency, single-polarization retrieval algorithm used in this analysis, the parameter accuracy requirements can be met with current satellite-based land surface products. We conclude that for regions with substantial vegetation, particularly where the vegetation is changing rapidly, any soil moisture retrieval algorithm that is based on the physics and parameterizations used in this study will require multiple frequencies, polarizations, or look angles to produce stable, reliable soil moisture estimates.     

N-parameter retrievals from L-band microwave observations acquired over a variety of crop fields

A number of studies have shown the feasibility of estimating surface soil moisture from L-band passive microwave measurements. Such measurements should be acquired in the near future by the Soil Moisture and Ocean Salinity (SMOS) mission. The SMOS measurements will be done at many incidence angles and two polarizations. This multiconfiguration capability could be very useful in soil moisture retrieval studies for decoupling between the effects of soil moisture and of the various surface parameters that also influence the surface emission (surface temperature, vegetation attenuation, soil roughness, etc.). The possibility to implement N-parameter (N-P) retrieval methods (where N = 2, 3, 4, ..., corresponds to the number of parameters that are retrieved) was investigated in this study based on experimental datasets acquired over a variety of crop fields. A large number of configurations of the N-P retrievals were studied, using several initializations of the model input parameters that were considered to be fixed or free. The best general configuration using no ancillary information (same configuration for all datasets) provided an rms error of about 0.059 m/sup 3//m/sup 3/ in the soil moisture retrievals. If a priori information was available on soil roughness and at least one vegetation model parameter, the rms error decreased to 0.049 m/sup 3//m/sup 3/. Using specific retrieval configurations for each dataset, the rms error was generally lower than 0.04 m/sup 3//m/sup 3/.     

A parameterized surface reflectivity model and estimation of bare-surface soil moisture with L-band radiometer

Soil moisture is an important parameter for hydrological and climatic investigations. Future satellite missions with L-band passive microwave radiometers will significantly increase the capability of monitoring Earth's soil moisture globally. Understanding the effects of surface roughness on microwave emission and developing quantitative bare-surface soil moisture retrieval algorithms is one of the essential components in many applications of geophysical properties in the complex Earth terrain by microwave remote sensing. We explore the use of the integral equation model (IEM) for modeling microwave emission. This model was validated using a three-dimensional Monte Carlo model. The results indicate that the IEM model can be used to simulate the surface emission quite well for a wide range of surface roughness conditions with high confidence. Several important characteristics of the effects of surface roughness on radiometer emission signals at L-band 1.4 GHz that have not been adequately addressed in the current semiempirical surface effective reflectivity models are demonstrated by using IEM-simulated data. Using an IEM-simulated database for a wide range of surface soil moisture and roughness properties, we developed a parameterized surface effective reflectivity model with three typically used correlation functions and an inversion model that puts different weights on the polarization measurements to minimize surface roughness effects and to estimate the surface dielectric properties directly from dual-polarization measurements. The inversion technique was validated with four years (1979-1982) of ground microwave radiometer experiment data over several bare-surface test sites at Beltsville, Maryland. The accuracies in random-mean-square error are within or about 3% for incidence angles from 20/spl deg/ to 50/spl deg/.     

Sea surface emissivity observations at L-band: first results of the Wind and Salinity Experiment WISE 2000

Sea surface salinity can be measured by passive microwave remote sensing at L-band. In May 1999, the European Space Agency (ESA) selected the Soil Moisture and Ocean Salinity (SMOS) Earth Explorer Opportunity Mission to provide global coverage of soil moisture and ocean salinity. To determine the effect of wind on the sea surface emissivity, ESA sponsored the Wind and Salinity Experiment (WISE 2000). This paper describes the field campaign, the measurements acquired with emphasis in the radiometric measurements at L-band, their comparison with numerical models, and the implications for the remote sensing of sea salinity.     

SMOS REFLEX 2003: L-band emissivity characterization of vineyards

The goal of the Soil Moisture and Ocean Salinity mission over land is to infer surface soil moisture from multiangular L-band radiometric measurements. As the canopy affects the microwave emission of land, it is necessary to characterize different vegetation layers. This paper presents the Reference Pixel L-Band Experiment (REFLEX), carried out in June-July 2003 at the Vale/spl grave/ncia Anchor Station, Spain, to study the effects of grapevines on the soil emission and on the soil moisture retrieval. A wide range of soil moisture (SM), from saturated to completely dry soil, was measured with the Universitat Polite/spl grave/cnica de Catalunya's L-band Automatic Radiometer (LAURA). Concurrently with the radiometric measurements, the gravimetric soil moisture, temperature, and roughness were measured, and the vines were fully characterized. The opacity and albedo of the vineyard have been estimated and found to be independent on the polarization. The /spl tau/--/spl omega/ model has been used to retrieve the SM and the vegetation parameters, obtaining a good accuracy for incidence angles up to 55/spl deg/. Algorithms with a three-parameter optimization (SM, albedo albedo, and opacity) exhibit a better performance than those with one-parameter optimization (SM).     

A parametric study on passive and active microwave observationsover a soybean crop

This work investigates the potential use of passive and active microwave observations to monitor soil moisture and vegetation biomass over a soybean cover. The work is based on a sensitivity analysis from a large set of data generated by radiative-transfer models. Some appropriate configurations are identified. In particular, the combined use of passive data at 1.4 GHz, with multiangle active measurements at 5 GHz, is found to be promising     

L波段微波辐射计周期脉冲式干扰时域检测方法研究

L波段微波辐射计是探测土壤湿度和海水盐度的有效遥感器。但是,全球定位系统(GPS)信号、雷达信号以及一些商用电子产品的电磁辐射造成的频谱污染都可以对微波辐射计的探测造成干扰,使得被动微波遥感对地观测结果具有一定的偏差,降低了地表参数的反演精度。该文通过实验模拟脉冲式噪声干扰,观测其在L波段(全功率接收型式)微波辐射计系统中的传输特性,分析输出信号特性与辐射计参数(积分时间、灵敏度)的相关性,获取其数字特征参数,结合脉冲检测法(APB),提出一种新的自相关检测(ACD)算法,能够有效用于周期性的脉冲式辐射干扰的检测,在微波辐射计系统积分时间1 ms的情况下,能够检测1.5 K的噪声干扰,满足卫星遥感探测反演地表参数精度的需求。