De Baets, Bernard

Hoffmann, L

Lievens, Hans

Matgen, P

Mattia, F

Montanari, M

Verhoest, Niko

Vernieuwe, Hilde

English

Ghent University Academic Bibliography

Soil moisture retrieval from co-polarized ALOS PALSAR backscattering in the Zwalmand Alzette catchmentsHans Lievens, H. Vernieuwe, N. Verhoest, B. De Baets, P. Matgen, M. Montanari, L. Hoffmann, F. MattiaALOS PI Symposium 2008, November 3 to 7, Rhodes, Greece                                         hans.lievens@ugent.beOutline Possibilistic soil moisture retrieval Application to study sites Study sites Field measurements Retrieval method Results ConclusionsPossibilistic soil moisture retrievalSAR backscatter over bare fields function of: SAR properties: frequency, polarization Incidence angle Soil moisture (dielectric constant) Soil roughnessUnknown, though very important in retrieval process Parameters: RMS height, Correlation length, autocorrelation functionMeasurements reveal large variability for one type of tillageDifficult to specify a single value for each parameterBut: If we would know the tillage state of a field (GIS/crop calendar/expert knowledge), could we then assign a roughness class to this field, having an interval for RMS height and correlation length?*Verhoest et al. (2007). A possibilistic approach to soil moisture retrieval from ERS synthetic aperture radar backscattering under soil roughness uncertainty. Water Resour. Res., 43, W07435. Possibilistic soil moisture retrievalRoughness parameter01minmaxvery likelyPossibilityA Roughness class can be defined by parameters having: A minimum value below parameter values are not possible  An interval in which parameters values are unsurprising, normal or usual  A maximum value above parameter values are not possibleA possibility distribution reflects the knowledge of an agent about a quantity and its rangingPossibilistic soil moisture retrievalRMS heightPossibility01Possibility01ααIEM-1Possibility01αMinimumMaximumMoisture contentCorrelation lengthBackscattering valueIncidence angleFrequencyPolarizationACFPossibilistic soil moisture retrievalPignistic transformation converts a possibility distribution into a probability distribution function (pdf), or vice versaThis pdf can then be used to estimate the mean soil moisture content (dielectric constant) and a standard deviation as a measure for the prediction accuracyExperiment - Study area 3 study fields in Zwalm catchment: W03 W05 W10 2 study fields in Alzette catchment: Cruchten BibeschbachExperiment - Field measurements Alzette: 2 PALSAR HH acquisitions on 19.02.08 and 19.03.08 Zwalm: 3 PALSAR HH acquisitions on 11.06.07, 10.07.07 and 27.07.07 Intensive field campaigns were organized, measuring: Soil moisture Soil roughness (only on bare fields of the Alzette) Bulk density Wheat vegetation: fresh biomassWheat field W05                                  gravimetric soil moisture sampling       measuring surface roughness with 4-m meshboardExperiment - Field measurements Sensitivity of backscattering to wheat fresh biomass (Zwalm) L-band more or less insensitive to wheat vegetationPossibilistic retrieval technique applicable to all fieldsExperiment - Field measurements-14-12-10-8-6-4-203 4 5 6 7Fresh biomass (kg/m²)BackscatterExperiment - Retrieval methodFlow chartExperiment - Retrieval method Selection of ‘roughness possibility distributions’ by calibrating IEM, given soil moisture and backscattering measurements: average absolute error (dB)Bibeschbach Cruchten ZwalmExperiment - Retrieval methodBibeschbach Cruchten Zwalmsupportcore Selection of ‘roughness possibility distributions’ by calibrating IEM, given soil moisture and backscattering measurements: average absolute error (dB)Roughness parameter01supportPossibility coreExperiment - Retrieval methodBibeschbach Cruchten Zwalmsupportcore Comparison of support and core with in situ measurements of RMS height and correlation length:Experiment - Retrieval methodBibeschbach Cruchten ZwalmsupportcoreMeasurements Comparison of support and core with in situ measurements of RMS height and correlation length: No perfect match with defined possibility distributions In good agreement with roughness parameters that result in lowest error with IEM Possibility distributions could be improved by considering a relationship between RMS height and correlation lengthExperiment - Results Soil moisture possibility distributions for the Zwalm catchment on 27.07.07: Field W05Field W10Experiment - Results102030405010.00 20.00 30.00 40.00 50.00Observed soil moisture (vol%)Retrieved soil moisture (vol%) Retrieved vs. observed soil moisture for Zwalm and Alzette Overall RMSE = 5.36 vol% Standard deviations give an idea about uncertainty on soil moisture Underestimations for wet soil conditions due to cut-off at 45 vol% Overestimations at intermediately wet conditions due to neglecting  relationship between RMS height and correlation length, causing unlikely parameter combinations that result in very high soil moisture contentsConclusions At L-band, backscattering is more or less insensitive to wheat vegetation, even for relatively high fresh biomass Parameterization of roughness is uncertain; assignment of possibility distributions for one tillage, enabling retrieval of soil moisture and an uncertainty measure Soil moisture retrieval using the presented possibilistic approach results in an overall RMSE of 5.36 vol% It is expected that the retrieval results (mean soil moisture content and its uncertainty) will improve when considering a relationshipbetween RMS height and correlation length

Soil moisture retrieval from co-polarized ALOS PALSAR backscattering in the Zwalm and Alzette catchments

https://biblio.ugent.be/publication/2036598/file/2076429

Soil moisture retrieval from co-polarized ALOS PALSAR backscattering in the Zwalm and Alzette catchments

Abstract

Similar works

Full text

Available Versions

Ghent University Academic Bibliography