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dc.contributorZiadat, Feras M.en_US
dc.creatorSultan, K Aen_US
dc.date2012-12-01en_US
dc.date.accessioned2018-03-11T07:16:19Z
dc.date.available2018-03-11T07:16:19Z
dc.identifierhttp://www.sid.ir/En/Journal/ViewPaper.aspx?ID=283853en_US
dc.identifierhttp://jast-old.modares.ac.ir/article_4909_b8996839ad820cccff3e9f37a666e8a1.pdfen_US
dc.identifierhttps://www.researchgate.net/publication/269336210_Comparing_Two_Methods_of_Soil_Data_Interpretation_to_Improve_the_Reliability_of_Land_Suitability_Evaluationen_US
dc.identifierhttps://mel.cgiar.org/reporting/download/hash/W1N0nrfsen_US
dc.identifier.citationK A Sultan, Feras M. Ziadat. (1/12/2012). Comparing Two Methods of Soil Data Interpretation to Improve the Reliability of Land Suitability Evaluation. Journal of agricultural science and technology: JAST, 14 (6), pp. 1425-1438.en_US
dc.identifier.urihttps://hdl.handle.net/20.500.11766/8041
dc.description.abstractSustainable management of limited land and water resources is urgently needed to meet the increasing demand for food and to protect the environment. Land suitability analysis is a prerequisite in assessing and proposing sustainable land use alternatives for an area. Soil data are usually available at different levels of detail and stored in various forms, usually soil maps and/or soil observations. Soil data interpretation methods control the reliability of land suitability evaluation results. This has a serious effect on the reliability of the suitability maps, the subsequent land use decisions, and environmental modeling. This study examines the reliability of land suitability mapping using different methods of soil data interpretation – the average of land characteristics for field observations within soil map units (point-in-polygon) and spatial interpolation using field observations only (proximity to points). The degree of agreement between the two methods depends on the type of land utilization – rainfed barley (86%), open range (85%), improved range (75%), drip irrigated vegetables (69%), and drip irrigated trees (59%). This results from the difference in the limiting land characteristic that determines the suitability of each land utilization type and the pattern of spatial variation of each land characteristic in the field. Suitability maps for adaptable (indigenous) crops (such as barley and range crops), which require minimum farming inputs, are generally more accurate because they tolerate a wider range of variability. The interpolation method was more efficient in detecting the spatial distribution and extreme values of limiting land characteristics, resulting in more accurate suitability maps. Therefore, when detailed soil maps are not available, field observations could be used to derive suitability maps using an exact interpolation method.en_US
dc.formatPDFen_US
dc.languageenen_US
dc.publisherTarbiat Modares Universityen_US
dc.rightsCC-BY-NC-4.0en_US
dc.sourceJournal of agricultural science and technology : JAST;14,(2012) Pagination 1425,1438en_US
dc.subjectindigenous cropsen_US
dc.subjectland characteristicsen_US
dc.subjectthiessen polygonsen_US
dc.subjectinterpolationen_US
dc.titleComparing Two Methods of Soil Data Interpretation to Improve the Reliability of Land Suitability Evaluationen_US
dc.typeJournal Articleen_US
cg.subject.agrovocspatial distributionen_US
cg.contributor.centerGeneral Commission for Scientific Agricultural Research - GCSARen_US
cg.contributor.centerInternational Center for Agricultural Research in the Dry Areas - ICARDAen_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.coverage.regionGlobalen_US
cg.contactferas.ziadat@fao.orgen_US
dc.identifier.statusOpen accessen_US
mel.impact-factor0.813en_US


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