{"title":"利用GIS和AHP技术绘制津巴布韦玉米生产土地适宜性图","authors":"W. Chivasa, O. Mutanga, Ç. Biradar","doi":"10.4314/sajg.v8i2.11","DOIUrl":null,"url":null,"abstract":"The 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.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":null,"pages":null},"PeriodicalIF":0.3000,"publicationDate":"2019-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Mapping land suitability for maize (Zea mays L.) production using GIS and AHP technique in Zimbabwe\",\"authors\":\"W. Chivasa, O. Mutanga, Ç. Biradar\",\"doi\":\"10.4314/sajg.v8i2.11\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The 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.\",\"PeriodicalId\":43854,\"journal\":{\"name\":\"South African Journal of Geomatics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.3000,\"publicationDate\":\"2019-10-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"South African Journal of Geomatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4314/sajg.v8i2.11\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"REMOTE SENSING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"South African Journal of Geomatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4314/sajg.v8i2.11","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"REMOTE SENSING","Score":null,"Total":0}
Mapping land suitability for maize (Zea mays L.) production using GIS and AHP technique in Zimbabwe
The 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.