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Engman, Edwin T.

Publications and source records attributed to Engman, Edwin T..

At least 19 records

Remote Sensing for Agriculture, Ecosystems and Hydrology III

The science need for remotely sensed soil moisture has been well established in the hydrologic, climate change and weather forecasting communities. In spite of this well documented science need there are currently no satellite missions flying or funded to make this very important geophysical measurement. There have been a number of experimental aircraft programs that have demonstrated the feasibility of using long wave microwave sensors for estimating soil moisture. Unfortunately, this science driver, soil moisture, imposes very difficult technical requirements for a satellite sensor system. Global soil moisture is driven by a spatial resolution on the order of 20 to 30 km and measurements need to be taken every two to three days to be useful to the science community. The principal sensor to accomplish the soil moisture measurements is an L- band passive microwave radiometer and achieving the spatial and temporal requirements requires a very large antenna. This paper describes the several alternatives to solve the very large antenna challenge and still meet the radiometer sensitivity requirement. The paper also discusses the alternatives considered to obtain the necessary ancillary data for characterizing the surface roughness, the surface temperature and the attenuation affects of vegetation needed to derive the geophysical parameter. Finally, the paper discusses proposed missions and how well they will meet the science requirements.

Engman, Edwin T.

Development of a Satellite Systems for Measuring Soil Moisture

The science need for remotely sensed soil moisture has been well established in the hydrologic, climate change and weather forecasting communities. There also have been a number of programs that have demonstrated the feasibility of using long wave microwave sensors for estimating soil moisture. These have ranged from truck mounted sensors, to intensive airborne campaigns with science objectives. Based on this history of truck and aircraft experiments, the science community has settled on a soil moisture product that meets the following criteria: a two day global repeat, a measured layer of 5 cm of soil, a footprint of 20 to 30 km, and an absolute accuracy of +/- 4% volumetric soil moisture. The principal sensor to accomplish this is an L-band passive microwave radiometer. A soil moisture mission is being proposed for the NASA Earth Systems Science Pathfinder (ESSP) mission which has very real constraints of a limited budget which includes the launch vehicle, and a three year award to launch time schedule. This paper describes ways to solve the very large antenna challenge, and the criteria used to choose the final design for an ESSP proposal. The paper also discusses the alternatives considered to obtain the necessary ancillary data for characterizing the surface roughness, the surface temperature and the attenuation affects of vegetation.

Engman, Edwin T.

Spatial Distribution and Pattern Persistence of Surface Soil Moisture and Temperature Over Prairie from Remote Sensing

Images remotely sensed aboard aircraft during FIFE, namely, PBMR (microwave) soil moisture and NS001 thermal infrared surface temperature, were mapped on the same coordinate system covering the 20 km x 20 km experimental site. For both kinds of image data, the frequency distributions were close to symmetric, and the area average compared reasonably well with the ground based measurements. For any image on any given day, the correlation between the remotely sensed values and collocated ground based measurements over the area was usually high in the case of NS001 surface temperature but low in the case of PBMR soil moisture. On the other hand, at any given flux station the correlation between the PBMR and gravimetric soil moisture over all available days was usually high. The correlation pixel by pixel between images of PBMR on different days was generally high. The preservation of the spatial patterns of soil moisture was also evaluated by considering the correlation station by station between ground-based soil moisture measurements on different days; no persistence of spatial pattern was apparent during wet periods, but a definite pattern gradually established itself toward the end of each drying episode. The spatial patterns of surface temperature revealed by NS001 were not preserved even within a single day. The cross-correlations among the two kinds of images and the vegetation index NDVI were normally poor. This suggests that different processes of vegetation growth, and of the near-surface soil water and energy budgets.

Chen, Daoyi

Soil Moisture: The Hydrologic Interface Between Surface and Ground Waters

A hypothesis is presented that many hydrologic processes display a unique signature that is detectable with microwave remote sensing. These signatures are in the form of the spatial and temporal distributions of surface soil moisture. The specific hydrologic processes that may be detected include groundwater recharge and discharge zones, storm runoff contributing areas, regions of potential and less than potential evapotranspiration (ET), and information about the hydrologic properties of soils. In basin and hillslope hydrology, soil moisture is the interface between surface and ground waters.

Engman, Edwin T.

Estimation of Bare Surface Soil Moisture and Surface Roughness Parameter Using L-Band SAR Image Data

An algorithm based on a fit of the single-scattering Integral Equation Method (IEM) was developed to provide estimation of soil moisture and surface roughness parameter (a combination of rms roughness height and surface power spectrum) from quasi-polarized synthetic aperture radar (SAR) measurements. This algorithm was applied to a series of measurements acquired at L-band (1.25 GHz) from both AIRSAR (Airborne Synthetic Aperture Radar operated by Jet Propulsion Laboratory) and SIR-C (Spaceborne Imaging Radar-C) over a well-managed watershed in southwest Oklahoma. It was found that the two co-polarized backscattering coefficients and their combinations would provide the best input to the algorithm for estimation of soil moisture and roughness parameter. Application of the inversion algorithm to the co-polarized measurements of both AIRSAR and SIR-C resulted in estimated values of soil moisture and roughness parameter for bare and short-vegetated fields that compared favorably with those sampled on the ground. The root-mean-square (rms) errors of the comparison were found to be 3.4% and 1.9 dB for soil moisture and surface roughness parameter, respectively.

Shi, Jian-Cheng

Microwave Remote Sensing of Soil Moisture for Estimation of Soil Properties

Surface soil moisture dynamics was derived using microwave remote sensing, and employed to estimate soil physical and hydraulic properties. The L-band ESTAR radiometer was employed in an airborne campaign over the Little Washita watershed, Oklahoma during June 10-18, 1992. Brightness temperature (TB) data were employed in a soil moisture inversion algorithm which corrected for vegetation and soil effects. Analyses of spatial TB and soil moisture dynamics during the dry-down period revealed a direct relationship between changes in TB, soil moisture and soil texture. Extensive regression analyses were carried out which yielded statistically significant quantitative relationships between ratio of percent sand to percent clay (RSC, a term derived to quantify soil texture) and saturated hydraulic conductivity (Ksat) in terms of change components of TB and surface soil moisture. Validation of results indicated that both RSC and Ksat can be estimated with reasonable accuracy. These findings have potential applications for deriving spatial distributions of RSC and Ksat over large areas.

Mattikalli, Nandish M.

Potential for Remotely Sensed Soil Moisture Data in Hydrologic Modeling

Many hydrologic processes display a unique signature that is detectable with microwave remote sensing. These signatures are in the form of the spatial and temporal distributions of surface soil moisture and portray the spatial heterogeneity of hydrologic processes and properties that one encounters in drainage basins. The hydrologic processes that may be detected include ground water recharge and discharge zones, storm runoff contributing areas, regions of potential and less than potential ET, and information about the hydrologic properties of soils and heterogeneity of hydrologic parameters. Microwave remote sensing has the potential to detect these signatures within a basin in the form of volumetric soil moisture measurements in the top few cm. These signatures should provide information on how and where to apply soil physical parameters in distributed and lumped parameter models and how to subdivide drainage basins into hydrologically similar sub-basins.

Engman, Edwin T.

Estimation of Bare Surface Soil Moisture and Surface Roughness Parameter Using L-Band SAR Image Data

An algorithm based on a fit of the single-scattering Integral Equation Method (IEM) was developed to provide estimation of soil moisture and surface roughness parameter (a combination of rms roughness height and surface power spectrum) from quad-polarized synthetic aperture radar (SAR) measurements. This algorithm was applied to a series of measurements acquired at L-band (1.25 GHz) from both AIRSAR (Airborne Synthetic Aperture Radar operated by the Jet Propulsion Laboratory) and SIR-C (Spaceborne Imaging Radar-C) over a well- managed watershed in southwest Oklahoma. Prior to its application for soil moisture inversion, a good agreement was found between the single-scattering IEM simulations and the L band measurements of SIR-C and AIRSAR over a wide range of soil moisture and surface roughness conditions. The sensitivity of soil moisture variation to the co-polarized signals were then examined under the consideration of the calibration accuracy of various components of SAR measurements. It was found that the two co-polarized backscattering coefficients and their combinations would provide the best input to the algorithm for estimation of soil moisture and roughness parameter. Application of the inversion algorithm to the co-polarized measurements of both AIRSAR and SIR-C resulted in estimated values of soil moisture and roughness parameter for bare and short-vegetated fields that compared favorably with those sampled on the ground. The root-mean-square (rms) errors of the comparison were found to be 3.4% and 1.9 dB for soil moisture and surface roughness parameter, respectively.

Shi, Jian-Cheng

Application of SIR-C SAR to Hydrology

The progress, results and future plans regarding the following objectives are presented: (1) Determine and compare soil moisture patterns within one or more humid watersheds using SAR data, ground-based measurements, and hydrologic modeling; (2) Use radar data to characterize the hydrologic regime within a catchment and to identify the runoff producing characteristics of humid zone watersheds; and (3) Use radar data as the basis for scaling up from small scale, near-point process models to larger scale water balance models necessary to define and quantify the land phase of GCM's (Global Circulation Models).

Engman, Edwin T.

Preliminary analysis of the sensitivity of AIRSAR images to soil moisture variations

Synthetic Aperture Radar (SAR) images acquired from various sources such as Shuttle Imaging Radar B (SIR-B) and airborne SAR (AIRSAR) have been analyzed for signatures of soil moisture. The SIR-B measurements have shown a strong correlation between measurements of surface soil moisture (0-5 cm) and the radar backscattering coefficient sigma(sup o). The AIRSAR measurements, however, indicated a lower sensitivity. In this study, an attempt has been made to investigate the causes for this reduced sensitivity.

Pardipuram, Rajan

Recent scientific advances in the use of radar in scientific hydrology

The data needs in scientific hydrology involve measurements of system states and fluxes. The microwave region is particularly well suited for measuring the system states of soil moisture and snow and the major flux into the earth as rainfall. This paper discusses the unique data needs of hydrology and presents some recent examples from AIRSAR experiments.

Engman, Edwin T.

Evaluation of polarimetric SAR parameters for soil moisture retrieval

Results of ongoing efforts to develop an algorithm for soil moisture retrieval from Synthetic Aperture Radar (SAR) imagery are reported. Estimates of soil moisture are of great importance in numerous environmental studies, including hydrology, meteorology, and agriculture. Previous studies using extensive scatterometer measurements have established the optimum parameters for moisture retrieval as C-band HH radar operating at incidence angles between 10 to 15 deg. However, these parameters were not tested or verified with imaging radar systems. The results from different investigators showed considerable variability in the relationship between soil moisture and radar backscattering. This variability suggests that those algorithms are site-specific. Furthermore, the small incidence angle requirement limits the spatial application, especially for airborne radar systems.

Shi, Jian-Cheng

Estimation of bare soil evaporation from a multi-frequency airborne SAR

An experiment was performed with the NASA/JPL airborne radar polarimeter in Sept. 1989 in an agricultural area near Fresno, CA. Based on 1st-order surface backscattering models, a physically based algorithm for retrieval of soil moisture and surface roughness was developed. It is shown that copolarization ratio is sensitive to soil moisture but not to soil roughness at high incidence angles (between 40 and 60 deg). The derived soil moisture was employed to derive a two-layer heat and energy flux model to estimate evaporation from bare soils.

Soares, Joao V.

Soil moisture needs in earth sciences

The author reviews the development of passive and active microwave techniques for measuring soil moisture with respect to how the data may be used. New science programs such as the EOS, the GEWEX Continental-Scale International Project (GCIP) and STORM, a mesoscale meteorology and hydrology project, will have to account for soil moisture either as a storage in water balance computations or as a state variable in-process modeling. The author discusses future soil moisture needs such as frequency of measurement, accuracy, depth, and spatial resolution, as well as the concomitant model development that must proceed concurrently if the development in microwave technology is to have a major impact in these areas.

Engman, Edwin T.

Development of soil moisture retrieval algorithm for L-band SAR measurements

A study of algorithm development and testing for soil moisture retrieval for bare fields using L-band synthetic aperture radar (SAR) imagery is reported. First-order surface scattering models predict that the copolarization ratio is sensitive to soil moisture but not to surface roughness. All possible ratios of the co-polarization signals and their linear combinations are evaluated. The best sensitivity to soil moisture is achieved from measurements as predicted by the first-order surface scattering model. The effects of system noise and volume scattering of soil are evaluated. To minimize the effect of the volume scattering, an algorithm which includes both the surface and volume scattering has been developed and tested using Jet Propulsion Laboratory Airborne SAR (JPL AIRSAR) data. The results show that the estimation of soil moisture can be improved after removing the system noise and including the volume scattering effect at large incidence angles.

Shi, Jiancheng

Hydrologic applications of SAR derived soil moisture

The MACHYDRO-90 was a multi-sensor aircraft campaign conducted to study drainage basin hydrology and the role of soil moisture in defining hydrologic characteristics and patterns. The results from the synthetic aperture radar (SAR) are presented. Data were collected over a period in which the soil conditions changed from dry to wet and then through a drying period which was close to ideal. Radar backscatter data are compared to detailed soil moisture samples taken to define soil moisture gradients within a watershed. The analysis also includes 40-MHz bandwidth SAR data, which provide very high spatial resolution. It is shown these data can be interpreted for hydrology and their application to hydrologic modeling is discussed.

Engman, Edwin T.

Soil moisture measurements from airborne SAR

The preliminary results of algorithm development and testing for soil moisture retrieval at high incidence angles are reported. Based on first-order surface backscattering models, a physically based algorithm for retrieval of soil moisture was developed and evaluated using NASA/JPL aircraft synthetic aperture radar (SAR) data. It shows that the copolarization ratio is sensitive to soil moisture change but not to surface roughness at high incidence angles. This algorithm performed well at L-band and should be useful. This study suggests that incidence angles greater than 40 degrees are optimal for such monitoring.

Shi, Jiancheng