Improvement of Moisture Estimation Accuracy of Vegetation-Covered Soil by Combined Active/Passive Microwave Remote Sensing

The measured effects of vegetation canopies on radar and radiometric sensitivity to soil moisture are compared to first-order emission and scattering models. The models are found to predict the measured emission and backscattering with reasonable accuracy for various crop canopies at frequencies between 1.4 and 5.0 GHz, especially at angles of incidence less than 30°. The vegetation loss factor L (?) increases with frequency and is found to be dependent upon canopy type and water content. In addition, the effective radiometric power absorption coefficient of a mature corn canopy is roughly 1.75 times that calculated for the radar at the same frequency. Comparison of an L-band radiometer with a C-band radar shows the two systems to be complementary in terms of accurate soil moisture sensing over the extreme range of naturally occurring soil-moisture conditions. The combination of both an L-band radiometer and a C-band radar is expected to yield soil-moisture estimates that are accurate to better than +/-30 percent of true soil moisture, even for a soil under a lossy crop canopy such as mature corn. This is true even without any other ancillary information.     

L-band radiometer measurements of soil water under growing clover grass

A field experiment with an L-band radiometer at 1.4 GHz was performed from May-July 2004 at an experimental site near Zurich, Switzerland. Before the experiment started, clover grass was seeded. Thermal infrared, in situ temperature, and time-domain reflectometer (TDR) measurements were taken simultaneously with hourly radiometer measurements. This setup allowed for investigation of the microwave optical depths and mode opacities (parallel and perpendicular to the soil surface) of the clover grass canopy. Optical depths and opacities were determined by in situ analysis and remotely sensed measurements using a nonscattering radiative transfer model. Due to the canopy structure, optical depth and opacity depend on the polarization and radiometer direction, respectively. A linear relation between vegetation water-mass equivalent and polarization-averaged optical depth was observed. Furthermore, measured and modeled radiative transfer properties of the canopy were compared. The model is based on an effective-medium approach considering the vegetation components as ellipsoidal inclusions. The effect of the canopy structure on the opacities was simulated by assuming an anisotropic orientation of the vegetation components. The observed effect of modified canopy structure due to a hail event was successfully reproduced by the model. It is demonstrated that anisotropic vegetation models should be used to represent the emission properties of vegetation. The sensitivity of radiometer measurements to soil water content was investigated in terms of the fractional contribution of radiation emitted from the soil to total radiation. The fraction of soil-emitted radiation was reduced to approximately 0.3 at the most developed vegetation state. The results presented contribute toward a better understanding of the interaction between L-band radiation and vegetation canopies. Such knowledge is important for evaluating data generated from future satellite measurements.     

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.     

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.     

Backscattering properties of boreal forests at the C- and X-bands

The backscattering properties of boreal forests are studied using empirical airborne and spaceborne radar data from Finland. Airborne measurements were carried out in the summer of 1992 by the HUTSCAT scatterometer at the Teijo test area in southern Finland. The HUTSCAT scatterometer is an eight-channel helicopter-borne profiling radar operating at the C- and X-bands. The ranging capability of the HUTSCAT scatterometer was employed in the semiempirical modeling of forest backscatter. The backscatter profile information was used in the analysis of the canopy transmissivity and the canopy backscattering coefficient by distinguishing backscattering contributions from the canopy and the ground. Additionally, ERS-1 C-band satellite SAR measurements were obtained for the Teijo test area and for the reference test area in Sodankyla in northern Finland. The radar results were compared with operational ground-based forest assessment data on forest compartments (stands) of the area. The key parameter investigated was the stem (bole) volume per hectare. The results obtained show the behavior of the canopy transmissivity and the canopy backscatter as a function of stem volume (directly related to the forest biomass). The influence of seasonal and diurnal changes on, and the effects of the changes in soil moisture to the backscattering coefficient were also investigated     

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.     

Ku- and C-band SAR for discriminating agricultural crop and soilconditions

A method is proposed to estimate both green leaf area index (GLAI) and soil moisture (h_v), based on radar measurements at the Ku-band (14.85 GHz) and C-band (5.35 GHz) frequencies. The Ku-band backscatter at large incidence angles was found to be independent of soil moisture conditions and could be used alone to estimate GLAI. Then, the Ku-band estimate of GLAI could be used with a measurement of C-band backscatter in a canopy radiative transfer model to isolate the value of h_v. This concept was demonstrated with a set of Kuand C-band synthetic aperture radar (SAR) backscatter data acquired over agricultural fields in Arizona. The demonstration showed promise for operational application of the method, though several limitations were identified. Since both Ku- and C-band σ_° are sensitive to soil roughness, this approach must be applied only to fields of similar soil roughness or row direction. This limitation may be less serious for farm management applications since crop type and cultivation practices are generally well known and can be taken into consideration. Another limitation of the use of Ku- and C-band σ° is the apparent saturation of the Ku-band signal with increasing GLAI. Operational implementation of this approach will require dual-frequency sensors aboard an aircraft or orbiting satellite     

A method for retrieving high-resolution surface soil moisture from hydros L-band radiometer and Radar observations

NASA's Earth System Science Pathfinder Hydrospheric States (Hydros) mission will provide the first global scale space-borne observations of Earth's soil moisture using both L-band microwave radiometer and radar technologies. In preparation for the Hydros mission, an observation system simulation experiment (OSSE) has been conducted. As a part of this OSSE, the potential for retrieving useful surface soil moisture at spatial resolutions of 9 and 3 km was explored. The approach involved optimally merging relatively accurate 36-km radiometer brightness temperature and relatively noisy 3-km radar backscatter cross section observations using a Bayesian method. Based on the Hydros OSSE data sets with low and high noises added to the simulated observations or model parameters, the Bayesian method performed better than direct inversion of either the brightness temperature or radar backscatter observations alone. The root-mean-square errors of 9-km soil moisture retrievals from the Bayesian merging method were reduced by 0.5 %vol/vol and 1.4 %vol/vol from the errors of direct radar inversions for the entire OSSE domain of all 34 consecutive days for the low and high noise data sets, respectively. Improvement in soil moisture estimates using the Bayesian merging method over the direct inversions of radar or radiometer data were even more significant for soil moisture retrieval at 3-km resolution. However, to address the representativeness of these results at the global and multiyear scales, further performance comparison studies are needed, particularly with actual field data.     

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.     

The hydrosphere State (hydros) Satellite mission: an Earth system pathfinder for global mapping of soil moisture and land freeze/thaw

The Hydrosphere State Mission (Hydros) is a pathfinder mission in the National Aeronautics and Space Administration (NASA) Earth System Science Pathfinder Program (ESSP). The objective of the mission is to provide exploratory global measurements of the earth's soil moisture at 10-km resolution with two- to three-days revisit and land-surface freeze/thaw conditions at 3-km resolution with one- to two-days revisit. The mission builds on the heritage of ground-based and airborne passive and active low-frequency microwave measurements that have demonstrated and validated the effectiveness of the measurements and associated algorithms for estimating the amount and phase (frozen or thawed) of surface soil moisture. The mission data will enable advances in weather and climate prediction and in mapping processes that link the water, energy, and carbon cycles. The Hydros instrument is a combined radar and radiometer system operating at 1.26 GHz (with VV, HH, and HV polarizations) and 1.41 GHz (with H, V, and U polarizations), respectively. The radar and the radiometer share the aperture of a 6-m antenna with a look-angle of 39/spl deg/ with respect to nadir. The lightweight deployable mesh antenna is rotated at 14.6 rpm to provide a constant look-angle scan across a swath width of 1000 km. The wide swath provides global coverage that meet the revisit requirements. The radiometer measurements allow retrieval of soil moisture in diverse (nonforested) landscapes with a resolution of 40 km. The radar measurements allow the retrieval of soil moisture at relatively high resolution (3 km). The mission includes combined radar/radiometer data products that will use the synergy of the two sensors to deliver enhanced-quality 10-km resolution soil moisture estimates. In this paper, the science requirements and their traceability to the instrument design are outlined. A review of the underlying measurement physics and key instrument performance parameters are also presented.     

Discrete scatter model for microwave radar and radiometer responseto corn: comparison of theory and data

As part of the Multisensor Aircraft Campaign, MACHYDRO, two microwave sensors, NASA's Airborne Synthetic Aperture Radar (AIRSAR) and Pushbroom Microwave Radiometer (PBMR) collected data over the same corn fields during the summer of 1990. During these flights, measurements were made on the ground of soil moisture and plant parameters. In this paper the measured canopy and soil parameters are used in a discrete scatter model to predict the response of both sensors (radar and radiometer). A distorted Born approximation is used to compute the scattering coefficient for the corn canopy. The backscatter coefficient gives the radar response and the radiometer response is obtained by integrating the bistatic coefficient over all scattering angles above ground. The objective of this analysis is to test the model and, in particular, to determine how well a single set of plant parameters and single model can yield agreement with both the radar and radiometer measurements. The model values are in reasonably good agreement with the measurements at horizontal polarization and reflect observed changes in soil moisture     

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.      

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.     

Results from the Push Broom Microwave Radiometer flights over theKonza Prairie in 1985

Four flights of the NASA C-130 aircraft carrying the Push Broom Microwave Radiometer (PBMR) over the Konza Prairie Research Natural Area in eastern Kansas were made to observe surface soil moisture variations. The radiometer operates at the 21-cm wavelength and has four beams that sweep out a swath of about 1.2 times the aircraft altitude. The resolution of each beam is 0.3 times the altitude. At the time of the flights the soil conditions ranged from very wet to moist and the microwave emission expressed as brightness temperatures for the burned watersheds ranged from below 200 to about 245 K. The brightness temperatures were correlated (r²=0.5) with surface moisture measurements, and the slope of the regression was in good agreement with prior results over other grasslands. However, for the unburned watersheds the brightness temperatures were around 270 K and roughly independent of the soil moisture conditions. In these unburned watersheds, a buildup of a thatch layer serves as highly emissive layer above the soil, causing high brightness, especially when wet     

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     

Dual-band dual-polarized perforated microstrip antennas for SARapplications

For dual-band dual-polarized synthetic aperture radar (SAR) applications a compact low-profile design is investigated. The operating frequencies are in the L and C-bands, centered about 1.275 and 5.3 GHz, respectively. Since the C-band frequency is larger by a factor of four, its array elements and inter-element separations are smaller by the same ratio. Thus, to allow similar scan ranges for both bands, the L-band elements are selected as perforated patches to enable the placement of C-band elements within them. Stacked-patch configurations were used to meet the bandwidth requirements, especially in the L-band. The C-band element was designed numerically, but the perforated L-band one required final experimental optimization. Also, in the latter case of L-band, a balanced transmission line feed was used to minimize cross polarization. For the C-band elements, slot coupling was used and, to simplify the feed, symmetric parasitic slots were incorporated to minimize cross polarization. No vertical connections were utilized, and electromagnetic couplings resulted in a compact low-profile design, with an electrically and thermally symmetric geometry     

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/.     

Estimation of snow water equivalence using SIR-C/X-SAR. I. Inferring snow density and subsurface properties

Algorithms for estimating dry snow density and the dielectric constant and roughness of the underlying soil or rock use backscattering measurements with VV and HH polarization at L-band frequency (1.25 GHz). Comparison with field measurements of snow density during the first SIR-C/X-SAR overpass shows absolute accuracy of 42 kg m/sup -3/ (13% relative error). For the underlying soil, comparisons with the ground scatterometer measurements showed errors of 4% by volume for soil moisture estimation and 4 mm for the surface root mean square (RMS) height. Values of snow density and the properties of the underlying soil are necessary for the estimation of snow water equivalence.     

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。     

Galactic noise and passive microwave remote sensing from space at L-band

The spectral window at L-band (1.413 GHz) is important for passive remote sensing of soil moisture and ocean salinity from space, parameters that are needed to understand the hydrological cycle and ocean circulation. At this frequency, radiation from celestial (mostly Galactic) sources is strong and, unlike the constant cosmic background, this radiation is spatially variable. This paper presents a modern radiometric map of the celestial sky at L-band and a solution for the problem of determining what portion of the sky is seen by a down-looking radiometer in orbit. The data for the radiometric map are derived from recent radio astronomy surveys and are presented as equivalent brightness temperature suitable for remote sensing applications. Examples using orbits and antennas representative of those contemplated for remote sensing of soil moisture and sea surface salinity from space are presented to illustrate the signal levels to be expected. Near the Galactic plane, the contribution can exceed several kelvin.