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dc.contributorDe Pauw, Eddyen_US
dc.contributorDeckers, Jozefen_US
dc.creatorHawinkel, P.en_US
dc.date2016-03-01en_US
dc.date.accessioned2021-01-21T22:33:03Z
dc.date.available2021-01-21T22:33:03Z
dc.identifierhttps://mel.cgiar.org/dspace/limiteden_US
dc.identifier.citationP. Hawinkel, Eddy De Pauw, Jozef Deckers. (1/3/2016). Probabilistic soil mapping by Bayesian inference to assess suitability for derocking in northwest Syria. Soil Use and Management, 32 (1), pp. 137-149.en_US
dc.identifier.urihttps://hdl.handle.net/20.500.11766/12384
dc.description.abstractLand reclamation by rock removal has wide potential in areas with shallow or rocky soils. In northwest Syria, this practice is hindered in its implementation by a lack of physical soil suitability data, principally soil rockiness and soil depth to hard rock. These soil properties were surveyed in a limited study area, resulting in a hard-boundary thematic soil map (64-94% accuracy per property). Bayesian inference is proposed as a low-cost upscaling method that yields a set of pixel-based probability maps, providing improved input for spatial decision support models. Whereas the achieved spatial upscaling (from 2510 to 19100ha) outweighed the decrease in overall accuracy (down to 26-57%), probability maps require dedicated validation and manipulation procedures. This research contributes to methods for the creation, validation and interpretation of probabilistic soil property maps for quantitative land evaluation. First, we evaluated three postprocessing and validation methods for probabilistic soil property maps, identifying the use of prediction rates' as the best approach in a spatial planning context. Next, we demonstrated how the maps can support decision-making for land management activities by simulating the expected losses and gains from interventions, in a decision-theoretic approach. Based on the simulations, the investments in large-scale derocking projects in northwest Syria will pay off in terms of increased agricultural productivity in less than 10years.en_US
dc.languageenen_US
dc.publisherWiley (12 months)en_US
dc.rightsCopyrighted; all rights reserveden_US
dc.sourceSoil Use and Management;32,(2015) Pagination 137,149en_US
dc.subjectbayesian inferenceen_US
dc.subjectprobabilistic soil mappingen_US
dc.subjectderockingen_US
dc.titleProbabilistic soil mapping by Bayesian inference to assess suitability for derocking in northwest Syriaen_US
dc.typeJournal Articleen_US
cg.subject.agrovocland reclamationen_US
cg.subject.agrovocsoil suitabilityen_US
cg.contributor.centerInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.centerKU Leuvenen_US
cg.contributor.centerCatholic University Leuven - KULen_US
cg.contributor.funderInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.projectCommunication and Documentation Information Services (CODIS)en_US
cg.contributor.project-lead-instituteInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.date.embargo-end-dateTimelessen_US
cg.coverage.regionWestern Asiaen_US
cg.coverage.countrySYen_US
cg.contactpieterhawinkel@gmail.comen_US
cg.identifier.doihttps://dx.doi.org/10.1111/sum.12240en_US
dc.identifier.statusTimeless limited accessen_US
mel.impact-factor1.69en_US


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