Mapping land suitability for maize (Zea mays L.) production using GIS and AHP technique in Zimbabwe

cg.contactwalter.chivasa@seedcogroup.comen_US
cg.contributor.centerInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.centerUniversity of KwaZulu-Natal - UKZNen_US
cg.contributor.centerSeed Co Group - Seed-COen_US
cg.contributor.funderInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.projectGeoinformatics and Data Management for integrated agroecosystem research, development and outreachen_US
cg.contributor.project-lead-instituteInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.coverage.countryZWen_US
cg.coverage.regionEastern Africaen_US
cg.creator.idBiradar, Chandrashekhar: 0000-0002-9532-9452en_US
cg.identifier.doihttps://dx.doi.org/10.4314/sajg.v8i2.11en_US
cg.isijournalISI Journalen_US
cg.issn2225-8531en_US
cg.issue2en_US
cg.journalSouth African Journal of Geomaticsen_US
cg.subject.agrovoczimbabween_US
cg.volume8en_US
dc.contributorMutanga, Onisimoen_US
dc.contributorBiradar, Chandrashekharen_US
dc.creatorChivasa, Walteren_US
dc.date.accessioned2020-07-17T14:25:09Z
dc.date.available2020-07-17T14:25:09Z
dc.description.abstractThe study integrates geographic information system (GIS) and analytic hierarchy process (AHP) to evaluate land suitability for maize production in Zimbabwe using multi-criteria evaluation (MCE) process. Four thematic maps based on rainfall, temperate, soil type and slope were integrated through overlay technique in a GIS environment to produce maize production suitability map. The resultant maize suitability map was overlaid with constraints map to ‘mask out’ all non-agricultural land. The final maize suitability map shows that 3.20% of the total land is highly suitable, 16.56% is suitable, 25.34% is moderately suitable, 32.33% is marginally suitable and 9.57% is not suitable for maize production in its current form. The maize suitability classification was validated by regression analyses using measured maize grain yield of 5 key maize varieties representing 5 different maturity groups. Grain yield was regressed against suitability index (SI) of each land class. There were significant positive correlations between maize grain yield and land suitability classes (R2 = 0.63 - 0.85). Integrating GIS and AHP with MCE is effective in assessing land suitability for targeting location specific interventions for maize production and the result is a comprehensive suitability map for Zimbabwe, incorporating several critical environmental factors affecting maize adaptation. We recommend the use of this suitability map as a decision support tool in land use planning and policy making.en_US
dc.formatPDFen_US
dc.identifierhttps://mel.cgiar.org/reporting/downloadmelspace/hash/dc45f0a0fec1c97afed9f9f56f5f508b/v/5141c95375923b71eeb3090e8469abe9en_US
dc.identifier.citationWalter Chivasa, Onisimo Mutanga, Chandrashekhar Biradar. (30/9/2019). Mapping land suitability for maize (Zea mays L. ) production using GIS and AHP technique in Zimbabwe. South African Journal of Geomatics, 8 (2), pp. 265-281.en_US
dc.identifier.statusOpen accessen_US
dc.identifier.urihttps://hdl.handle.net/20.500.11766/11253
dc.languageenen_US
dc.publisherConsas Conferenceen_US
dc.rightsCC-BY-4.0en_US
dc.sourceSouth African Journal of Geomatics;8,(2019) Pagination 265-281en_US
dc.subjectmulti-criteria evaluationen_US
dc.subjectgeographical information systemen_US
dc.subjectmapping maize land suitabilityen_US
dc.subjectanalytic hierarchic processen_US
dc.titleMapping land suitability for maize (Zea mays L.) production using GIS and AHP technique in Zimbabween_US
dc.typeJournal Articleen_US
dcterms.available2019-09-30en_US
dcterms.extent265-281en_US
mel.project.openhttp://www.icarda.org/en_US

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