Dr. Thomas J. Jackson Profile

Dr. Thomas J. Jackson

at US Dept of Agriculture

SPIE Involvement:

Author | Editor

Publications (20)

SPIE Journal Paper | 12 February 2019 Open Access

Estimating vegetation water content during the Soil Moisture Active Passive Validation Experiment 2016

Michael Cosh, William White, Andreas Colliander, Thomas Jackson, John Prueger, Brian Hornbuckle, E. Raymond Hunt, Heather McNairn, Jarrett Powers, Victoria Walker, Paul Bullock

JARS, Vol. 13, Issue 01, 014516, (February 2019) https://doi.org/10.1117/12.10.1117/1.JRS.13.014516

KEYWORDS: Vegetation, Soil science, Agriculture, Earth observing sensors, Landsat, Clouds, Satellites, Remote sensing, Climatology, Calibration

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Vegetation water content (VWC) is an important land surface parameter that is used in retrieving surface soil moisture from microwave satellite platforms. Operational approaches utilize relationships between VWC and satellite vegetation indices for broad categories of vegetation, i.e., “agricultural crops,” based on climatological databases. Determining crop type–specific equations for water content could lead to improvements in the soil moisture retrievals. Data to address this issue are lacking, and as a part of the calibration and validation program for NASA’s Soil Moisture Active Passive (SMAP) Mission, field experiments are conducted in northern central Iowa and southern Manitoba to investigate the performance of the SMAP soil moisture products for these intensive agricultural regions. Both sites are monitored for soil moisture, and the calibration and validation assessments had indicated performance issues in both domains. One possible source could be the characterization of the vegetation. In this investigation, Landsat 8 data are used to compute a normalized difference water index for the entire summer of 2016 that is then integrated with extensive VWC sampling to determine how to best characterize daily estimates of VWC for improved algorithm implementation. In Iowa, regression equations for corn and soybean are developed that provided VWC with root mean square error (RMSE) values of 1.37 and 1.10 kg / m2, respectively. In Manitoba, corn and soybean equations are developed with RMSE values of 0.55 and 0.25 kg / m2. Additional crop-specific equations are developed for winter wheat (RMSE of 0.07 kg / m2), canola (RMSE of 0.90 kg / m2), oats (RMSE of 0.74 kg / m2), and black beans (RMSE of 0.31 kg / m2). Overall, the conditions are judged to be typical with the exception of soybeans, which had an exceptionally high biomass as a result of significant rainfall as compared to previous studies in this region. Future implementation of these equations into algorithm development for satellite and airborne radiative transfer modeling will improve the overall performance in agricultural domains.

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Proceedings Article | 21 November 2012 Paper

Airborne active and passive L-band measurements using PALS instrument in SMAPVEX12 soil moisture field campaign

Andreas Colliander, Simon Yueh, Seth Chazanoff, Steven Dinardo, Ian O'Dwyer, Thomas Jackson, Heather McNairn, Paul Bullock, Grant Wiseman, Aaron Berg, Ramata Magagi, Eni Njoku

Proceedings Volume 8524, 85240G (2012) https://doi.org/10.1117/12.977600

KEYWORDS: Soil science, Calibration, L band, Radiometry, Algorithm development, Data acquisition, Reflectivity, Agriculture, Antennas, Temperature metrology

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SPIE Journal Paper | 14 September 2012

Effect of dew on aircraft-based passive microwave observations over an agricultural domain

Jinyang Du, Thomas Jackson, Rajat Bindlish, Michael Cosh, Li Li, Brian Hornbuckle, Erik Kabela

JARS, Vol. 6, Issue 01, 063571, (September 2012) https://doi.org/10.1117/12.10.1117/1.JRS.6.063571

KEYWORDS: Directed energy weapons, Soil science, Microwave radiation, Vegetation, X band, Temperature metrology, Agriculture, Scattering, Sensors, Satellites

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Proceedings Article | 16 September 2011 Paper

A MODIS-based vegetation index climatology

R. Bindlish, T. Jackson, T. Zhao

Proceedings Volume 8156, 815603 (2011) https://doi.org/10.1117/12.890311

KEYWORDS: Vegetation, Climatology, Soil science, MODIS, Microwave radiation, Algorithm development, Satellites, Remote sensing, Sensors, Signal attenuation

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Proceedings Article | 12 August 2010 Paper

Refinement of microwave vegetation indices

L. Chai, J. Shi, L. Zhang, T. Jackson

Proceedings Volume 7809, 780904 (2010) https://doi.org/10.1117/12.858356

KEYWORDS: Vegetation, Scattering, Microwave radiation, Remote sensing, Radiative transfer, Soil science, Satellites, Silver, Temperature metrology, Earth sciences

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SPIE Journal Paper | 1 May 2010

Vegetation water content mapping in a diverse agricultural landscape: National Airborne Field Experiment 2006

Michael Cosh, Jing Tao, Thomas Jackson, Lynn McKee, Peggy O'Neill

JARS, Vol. 4, Issue 01, 043532, (May 2010) https://doi.org/10.1117/12.10.1117/1.3449090

KEYWORDS: Vegetation, Reflectivity, Satellites, Agriculture, Soil science, Landsat, Satellite imaging, Short wave infrared radiation, Microwave radiation, Earth observing sensors

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Proceedings Article | 21 August 2009 Paper

Validation of microwave vegetation indices using field experiment data sets

T. J. Jackson, J. C. Shi, R. Bindlish, M. Cosh, L. Chai, J. Du, S. Zhao, J. Tao

Proceedings Volume 7454, 745406 (2009) https://doi.org/10.1117/12.823891

KEYWORDS: Vegetation, Microwave radiation, Soil science, Polarization, Landsat, Signal attenuation, MODIS, Sensors, Remote sensing, Earth observing sensors

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Proceedings Article | 10 September 2008 Paper

Soil Moisture Active/Passive (SMAP) Mission concept

D. Entekhabi, T. J. Jackson, E. Njoku, P. O'Neill, J. Entin

Proceedings Volume 7085, 70850H (2008) https://doi.org/10.1117/12.795910

KEYWORDS: Soil science, Algorithm development, Radar, Spatial resolution, Carbon, Climatology, Floods, L band, Data modeling, Radiometry

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Proceedings Article | 10 September 2008 Paper

Soil moisture retrieval from WindSat using the single channel algorithm toward a blended global soil moisture product from multiple microwave sensors

Jicheng Liu, Xiwu Zhan, Thomas Jackson

Proceedings Volume 7085, 70850I (2008) https://doi.org/10.1117/12.795065

KEYWORDS: Soil science, Microwave radiation, Vegetation, Sensors, Dielectrics, Satellites, Climatology, Remote sensing, Calibration, Data modeling

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Proceedings Article | 10 September 2008 Paper

Microwave vegetation indices derived from satellite microwave radiometers

T. Jackson, J. Shi, J. Tao

Proceedings Volume 7083, 708302 (2008) https://doi.org/10.1117/12.790529

KEYWORDS: Vegetation, Microwave radiation, Polarization, Satellites, Sensors, Radiometry, Signal attenuation, Soil science, Water, Remote sensing

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Proceedings Article | 12 October 2007 Paper

WindSat passive microwave polarimetric observations of soil moisture and land variables

Jinyang Du, Thomas Jackson, Rajat Bindlish, M. Cosh, Li Li

Proceedings Volume 6677, 66771I (2007) https://doi.org/10.1117/12.730684

KEYWORDS: Soil science, Vegetation, Error analysis, Microwave radiation, Climatology, Satellites, Polarimetry, Radiometry, Sensors, Polarization

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Proceedings Article | 8 December 2006 Paper

Azimuthal variations in polarimetric microwave measurements observed over Dome C, Antarctica

Parag Narvekar, Georg Heygster, Thomas Jackson, Rajat Bindlish, Li Li

Proceedings Volume 6410, 64100J (2006) https://doi.org/10.1117/12.693503

KEYWORDS: Polarimetry, Microwave radiation, Radiometry, Remote sensing, Domes, Temperature metrology, Scattering, Sensors, Calibration, Lithium

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Proceedings Article | 1 September 2006 Paper

Validation of satellite-based soil moisture algorithms

Thomas Jackson

Proceedings Volume 6301, 63010D (2006) https://doi.org/10.1117/12.677851

KEYWORDS: Soil science, Satellites, Microwave radiation, Sensors, Climatology, Calibration, Microwave remote sensing, Environmental sensing, Remote sensing, Autoregressive models

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Proceedings Article | 22 December 2004 Paper

Estimation of soil moisture with L-band multipolarization radar

Jiancheng Shi, K. S. Chen, Y. Kim, J. J. Van Zyl, E. Njoku, G. Sun, P. O'Neill, T. Jackson, D. Entekhabi

Proceedings Volume 5654, (2004) https://doi.org/10.1117/12.578311

KEYWORDS: Soil science, Scattering, Backscatter, Polarization, Vegetation, Data modeling, Error analysis, Radar, Dielectric polarization, L band

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Proceedings Article | 17 December 1999 Paper

Defining the range of uncertainty associated with remotely sensed soil moisture estimates with microwave radiometers

Charles Laymon, Andrew Manu, William Crosson, Thomas Jackson

Proceedings Volume 3868, (1999) https://doi.org/10.1117/12.373129

KEYWORDS: Soil science, Vegetation, Error analysis, Surface roughness, Microwave radiation, Dielectrics, Hydrology, Remote sensing, Temperature metrology, Radiometry

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We evaluate the response of a passive microwave soil moisture retrieval algorithm to errors in the estimation of input variables and parameters. The model is run varying one parameter at a time within a specified range to quantify the effects individual parameters have on soil moisture retrieval. Although errors in the estimation of most parameters yield total variations in soil moisture of less than about 4% volumetric water content (vwc), variations in the estimates of vegetation water content, vegetation b parameter, percent clay, and surface roughness yield the greatest total variations in calculated soil moisture. The effects of these parameter variations on calculated soil moisture are greater for wetter soils (above 25% vwc) and can result in total variations in soil moisture retrieval up to 24% vwc. These same parameters have a compound effect on calculated soil moisture when they vary collectively; variations in soil moisture retrieval with errors in vegetation water content and surface roughness may be as high as 38% vwc (-12%, +26%). Even over more common conditions between 10% and 25% vwc, errors in vegetation water content, percent clay, and surface roughness result in total soil moisture variations of 9% to 15% (plus or minus 4.5% to plus or minus 7.5%), which are unacceptably high for many applications. When random errors are imposed on these three parameters of the Southern Great Plains 1997 (SGP97) Hydrology Experiment data set, the macrostructure of the soil moisture distribution remains intact compared to the original calculations, but the moisture field is significantly more heterogeneous. It is demonstrated that the distribution (plus or minus 2(sigma) ) of soil moisture for given values of brightness temperature ranges between plus or minus 5% vwc from random errors imposed on the same three parameters. Improvements in parameter estimation in SGP97 contributed to a decrease in the soil moisture uncertainty ((alpha) equals 0.05) by about 67% to plus or minus 3% vwc.

Proceedings Article | 11 December 1998 Paper

Comparison of calibration techniques of an impedance probe for near-surface soil moisture measurement

Teferi Tsegaye, Tommy Coleman, Thomas Jackson

Proceedings Volume 3499, (1998) https://doi.org/10.1117/12.332735

KEYWORDS: Soil science, Calibration, Remote sensing, Microwave remote sensing, Sensors, Manufacturing

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An Impedance Probe (IP) was used during the Southern Great Plain 1997 field experiment to support the remote sensing soil moisture mapping effort in Oklahoma, USA. Soil moisture sampling techniques used as ground-truth for remote sensing are most often not adequate due to the time and cost associated with them. The need for fast, accurate, less expensive, and less destructive measurement techniques within the remote sensing discipline is increasingly growing. The IP offers an alternative for measuring soil moisture in remotely- sensed regions where the logistics of gravimetric sampling can restrict the number of samples obtained. The gravimetric technique has been the traditional and most accurate technique used to validate remotely measured soil moisture. This technique is very destructive and time consuming, thereby limiting our ability to apply it over large areas expected by coarse resolution microwave remote sensing products. Recent advances in the Time Domain Reflectometery (TDR) techniques have resulted in sensors with less noise and require minimum human intervention. Field sampling and laboratory experiments were conducted to evaluate and calibrate soil moisture data measured using an IP. The objectives were: to examine the best calibration technique that can be used to estimate the spatial distribution of soil moisture and/or a representative mean moisture level for a given location, and to evaluate the correlation of soil moisture values using the probe and gravimetric measurement techniques. Results indicated that a site specific calibration curve developed by using a pressure plate apparatus provided a representative mean value was equivalent to the gravimetric technique. Both, the simulated and manufacturer calibration techniques provide soil moisture values that are spatially correlated with the gravimetric measurement technique. Our results indicated that, the instrument can provide reproducible results comparable to the gravimetric technique. This instrument can be utilized to meet the requirement of measuring the soil moisture content in the upper 6-cm of the soil depth.

Proceedings Article | 30 December 1997 Paper

Ideal brightness temperature algorithm for estimating soil-profile water status: I. Algorithm development

William Belisle, Narayan Rajbhandari, Teferi Tsegaye, Ahmed Fahsi, Andrew Manu, Yanming Liu, G. Robertson, Tommy Coleman, T. Jackson, Peggy O'Neill, M. Collins

Proceedings Volume 3222, (1997) https://doi.org/10.1117/12.298145

KEYWORDS: Soil science, Microwave radiation, Algorithm development, Dielectrics, Remote sensing, Particles, Radiometry, Surface roughness, Hydrology, Climatology

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Proceedings Article | 24 November 1995 Paper

Estimating soil properties from microwave measurements of soil moisture

Nandish Mattikalli, Edwin Engman, Laj Ahuja, Thomas Jackson

Proceedings Volume 2585, (1995) https://doi.org/10.1117/12.227172

KEYWORDS: Soil science, Data modeling, Microwave radiation, Remote sensing, Microwave remote sensing, Vegetation, Geographic information systems, Volume rendering, Temperature metrology, Atmospheric modeling

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Proceedings Article | 21 December 1994 Paper

Radiometer aperture synthesis for soil moisture mapping

Thomas Schmugge, Thomas Jackson, David Le Vine, Calvin Swift

Proceedings Volume 2313, (1994) https://doi.org/10.1117/12.197342

KEYWORDS: Soil science, Antennas, Radiometry, Microwave radiation, Vegetation, Data modeling, Dielectrics, Water, Synthetic apertures, Remote sensing

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Proceedings Article | 31 August 1993 Paper

Estimating profile soil moisture from surface-layer measurements: a review

K. Kostov, Thomas Jackson

Proceedings Volume 1941, (1993) https://doi.org/10.1117/12.154681

KEYWORDS: Soil science, Data modeling, Microwave radiation, Error analysis, Statistical analysis, Remote sensing, Radiometry, Temperature metrology, Calibration, Dielectrics

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