Mapping field-scale soil moisture with L-band radiometer and ground-penetrating radar over bare soil

Active and passive remote sensing; Accurate measurement; Bare soils; Brightness temperatures; Empirical model; Field experiment; Field-scale soil moisture; Ground Penetrating Radar; Ground penetrating radars; Horizontal polarization; Irrigation patterns; L-band radiometer; L-band radiometry; Low frequency; Monte Carlo Simulation; Passive remote sensing; Reference data; Research fields; RMS errors; Root-mean-square errors; Surface reflections; Surface soil moisture; Time Domain Reflectometry; Vertical polarization; Calibration; Computer simulation; Geological surveys; Irrigation; Mapping; Moisture control; Moisture determination; Monte Carlo methods; Polarization; Radar; Radar measurement; Radar reflection; Radiometers; Radiometry; Remote sensing; Soil moisture; Surface properties; Surface roughness; Time domain analysis; Water content; Ground penetrating radar systems

Abstract :

[en] Accurate estimates of surface soil moisture are essential in many research fields, including agriculture, hydrology, and meteorology. The objective of this study was to evaluate two remote-sensing methods for mapping the soil moisture of a bare soil, namely, L-band radiometry using brightness temperature and ground-penetrating radar (GPR) using surface reflection inversion. Invasive time-domain reflectometry (TDR) measurements were used as a reference. A field experiment was performed in which these three methods were used to map soil moisture after controlled heterogeneous irrigation that ensured a wide range of water content. The heterogeneous irrigation pattern was reasonably well reproduced by both remote-sensing techniques. However, significant differences in the absolute moisture values retrieved were observed. This discrepancy was attributed to different sensing depths and areas and different sensitivities to soil surface roughness. For GPR, the effect of roughness was excluded by operating at low frequencies (0.2-0.8 GHz) that were not sensitive to the field surface roughness. The root mean square (rms) error between soil moisture measured by GPR and TDR was 0.038 m3 · m-3. For the radiometer, the rms error decreased from 0.062 (horizontal polarization) and 0.054 (vertical polarization) to 0.020 m3 · m-3 (both polarizations) after accounting for roughness using an empirical model that required calibration with reference TDR measurements. Monte Carlo simulations showed that around 20% of the reference data were required to obtain a good roughness calibration for the entire field. It was concluded that relatively accurate measurements were possible with both methods, although accounting for surface roughness was essential for radiometry. © 2011 IEEE.

Disciplines :

Environmental sciences & ecology
Earth sciences & physical geography

Author, co-author :

Jonard, François ; Université de Liège - ULiège > Département de géographie > Systèmes d'information géographiques

Weihermüller, L.; Agrosphere (IBG-3), Institute of Bio- and Geosciences, Forschungszentrum Jülich GmbH, 52425 Jülich, Germany

Jadoon, K. Z.; Agrosphere (IBG-3), Institute of Bio- and Geosciences, Forschungszentrum Jülich GmbH, 52425 Jülich, Germany

Schwank, M.; German Research Center for Geosciences GFZ, 14473 Potsdam, Germany

Vereecken, H.; Agrosphere (IBG-3), Institute of Bio- and Geosciences, Forschungszentrum Jülich GmbH, 52425 Jülich, Germany

Lambot, S.; Agrosphere (IBG-3), Institute of Bio- and Geosciences, Forschungszentrum Jülich GmbH, 52425 Jülich, Germany, Earth and Life Institute, Université Catholique de Louvain, 1348 Louvainla-Neuve, Belgium

Language :

English

Title :

Mapping field-scale soil moisture with L-band radiometer and ground-penetrating radar over bare soil

Publication date :

2011

Journal title :

IEEE Transactions on Geoscience and Remote Sensing

ISSN :

0196-2892

eISSN :

1558-0644

Publisher :

Institute of Electrical and Electronics Engineers, United States

Volume :

Issue :

Pages :

2863-2875

Peer reviewed :

Peer Reviewed verified by ORBi

Available on ORBi :

since 21 September 2021

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