Rock fraction effects on the interpretation of microwave emission from soils

Jackson, Thomas J.; Kostov, K.G.; Saatchi, S. S.

doi:10.1109/igarss.1991.579278

Cited by 6 publications

(6 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Rock fragment content has been shown to affect radar backscatter through its effect on water holding capacity [ Jackson et al , 1992] because rocks do not absorb appreciable amounts of water. This coupled with the fact that portable probes could only be inserted where rocks were absent caused an overestimation of bulk volumetric soil moisture.…”

Section: Methodsmentioning

confidence: 99%

Comparison of four models to determine surface soil moisture from C‐band radar imagery in a sparsely vegetated semiarid landscape

Thoma

Moran

Bryant

et al. 2006

Water Resources Research

View full text Add to dashboard Cite

[1] Four approaches for deriving estimates of near-surface soil moisture from radar imagery in a semiarid, sparsely vegetated rangeland were evaluated against in situ measurements of soil moisture. The approaches were based on empirical, physical, semiempirical, and image difference techniques. The empirical approach involved simple linear regression of radar backscatter on soil moisture, while the integral equation method (IEM) model was used in both the physical and semiempirical approaches. The image difference or delta index approach is a new technique presented here for the first time. In all cases, spatial averaging to the watershed scale improved agreement with observed soil moisture. In the empirical approach, variation in radar backscatter explained 85% of the variation in observed soil moisture at the watershed scale. For the physical and best semiempirical adjustment to the physical model, the root-mean-square errors (RMSE) between modeled and observed soil moisture were 0.13 and 0.04, respectively. Practical limitations to obtaining surface roughness measurements limit IEM utility for large areas. The purely image-based delta index has significant operational advantage in soil moisture estimates for broad areas. Additionally, satellite observations of backscatter used in the delta index indicated an approximate 1:1 relationship with soil moisture that explained 91% of the variability, with RMSE = 0.03. Results showed that the delta index is scaled to the range in observed soil moisture and may provide a purely image based model. It should be tested in other watersheds to determine if it implicitly accounts for surface roughness, topography, and vegetation. These are parameters that are difficult to measure over large areas, and may influence the delta index.

show abstract

Section: Methodsmentioning

confidence: 99%

Comparison of four models to determine surface soil moisture from C‐band radar imagery in a sparsely vegetated semiarid landscape

Thoma

Moran

Bryant

et al. 2006

Water Resources Research

View full text Add to dashboard Cite

show abstract

“…Results from early field and aircraft experiments demonstrated strong regression‐based relationships between surface moisture and both brightness temperature and surface emissivity [ Schmugge , 1976, 1977; Jackson et al , 1984]. Models have subsequently become more complex by accounting for canopy effects [ Mo et al , 1982; Jackson et al , 1982; Jackson and Schmugge , 1991], roughness [ Choudhury et al , 1979], polarization mixing [ Wang and Choudhury , 1981], and other perturbing factors [ Jackson and O'Neill , 1987; Jackson et al , 1992, 1997; O'Neill and Jackson , 1990]. While many of these models are based on radiative transfer theory, an element of empiricism often remains because of difficulty in parameterizing some components from other measurable biophysical properties and at more meaningful spatial scales.…”

Section: General Backgroundmentioning

confidence: 99%

Multisensor historical climatology of satellite‐derived global land surface moisture

Owe¹,

Jeu²,

Holmes³

2008

J. Geophys. Res.

861

700

View full text Add to dashboard Cite

[1] A historical climatology of continuous satellite-derived global land surface soil moisture is being developed. The data consist of surface soil moisture retrievals derived from all available historical and active satellite microwave sensors, including Nimbus-7 Scanning Multichannel Microwave Radiometer, Defense Meteorological Satellites Program Special Sensor Microwave Imager, Tropical Rainfall Measuring Mission Microwave Imager, and Aqua Advanced Microwave Scanning Radiometer for EOS, and span the period from November 1978 through the end of 2007. This new data set is a global product and is consistent in its retrieval approach for the entire period of data record. The moisture retrievals are made with a radiative transfer-based land parameter retrieval model. The various sensors have different technical specifications, including primary wavelength, spatial resolution, and temporal frequency of coverage. These sensor specifications and their effect on the data retrievals are discussed. The model is described in detail, and the quality of the data with respect to the different sensors is discussed as well. Examples of the different sensor retrievals illustrating global patterns are presented. Additional validation studies were performed with large-scale observational soil moisture data sets and are also presented. The data will be made available for use by the general science community.

show abstract

“…High frequency (active) microwave retrievals are difficult to obtain in regions with hi& rock contenl: due to increased backscatter and a weaker relationship with soil moisture (Jackson 1992) even when aggregated to 280 meter resolution, and thus remains an issue. Clearly, if there were more images available, particularly during and immediately following rainfall events, PEST-Noah would be able to perform better as for the M90 case.…”

Section: Calibration Experimentsmentioning

confidence: 99%

Using remotely-sensed estimates of soil moisture to infer soil texture and hydraulic properties across a semi-arid watershed

Santanello

Peters‐Lidard²,

Garcia

et al. 2007

Remote Sensing of Environment

115

View full text Add to dashboard Cite

Near-surface soil moisture is a critical component of land surface energy and water balance studies encompassing a wide range of disciplines. However, the processes of infiltration, runoff, and evapotranspiration in the vadose zone of the soil are not easy to quantify or predict because of the difficulty in accurately representing soil texture and hydraulic properties in land surface models. This study approaches the problem of parameterizing soils from a unique perspective based on components originally developed for operational estimation of soil moisture for mobility assessments. Estimates of near-surface soil moisture derived fiom passive (L-band) microwave remote sensing were acquired on six dates during the Monsoon '90 experiment in southeastern Arizona, and used to calibrate hydraulic properties in an offline land surface model and infer information on the soil conditions of the region. Specifically, a robust parameter estimation tool (PEST) was used to calibrate the Noah land surface model and run at very high spatial resolution across the Walnut Gulch Experimental Watershed. Errors in simulated versus observed soil moisture were minimized by adjusting the soil texture, which in turn controls the hydraulic properties through the use of pedotransfer functions. By estimating a continuous range of widely applicable soil properties such as sand, silt, and clay percentages rather than applying rigid soil texture classes, lookup tables, or large parameter sets as in previous studies, the physical accuracy and consistency of the resulting soils could then be assessed.In addition, the sensitivity of this calibration method to the number and timing of microwave retrievals is determined in relation to the temporal patterns in precipitation and soil drying. The resultant soil properties were applied to an extended time period demonstrating the improvement in simulated soil moisture over that using default or county-level soil parameters. The methodology is also applied to an independent case at Walnut Gulch using a new soil moisture product fiom active (C-band) radar imagery with much lower spatial and temporal resolution. Overall, results demonstrate the potential to gain physically meaningful soils information using simple parameter estimation with few but appropriately timed remote sensing retrievals. This study exarnines the ability of microwave remote sensing estimates of soil moisture to be used to calibrate a land surface model and, in the process, infer soil textural and hydraulic properties across spatially heterogeneous landscapes. Results also demonstrate the limitations and potential improvements in simulating soil moisture evolution using a combination of remote sensing, modeling, and parameter estimation techniques. Watershed. E r r m in simulated versus observed soil moistwe were m&mized by adjustbg the soil texae, which k ttt.m eontrols the hytlraa1-iit:propefiies though k use of pedob-msfer h e k s . By estimating a continms range of widely applicable soil prope~es swh sts sad, silt, and cl...

show abstract

Rock fraction effects on the interpretation of microwave emission from soils

Cited by 6 publications

References 5 publications

Comparison of four models to determine surface soil moisture from C‐band radar imagery in a sparsely vegetated semiarid landscape

Comparison of four models to determine surface soil moisture from C‐band radar imagery in a sparsely vegetated semiarid landscape

Multisensor historical climatology of satellite‐derived global land surface moisture

Using remotely-sensed estimates of soil moisture to infer soil texture and hydraulic properties across a semi-arid watershed

Contact Info

Product

Resources

About