{"title":"基于GIS辅助AHP的印度拉贾斯坦邦西部干旱区农用地适宜性分类与评价","authors":"Sonia ., Sunita ., Rakesh Kumar Verma, Tathagata Ghosh, Rajarshi Kumar Gaur","doi":"10.18805/ijare.a-6085","DOIUrl":null,"url":null,"abstract":"Background: Agricultural Land Suitability Analysis is one of the dependable method through which crop specific land suitability can be analyzed. Agricultural land suitability analysis for the pearl millet in the Arid Western Plain Zone of Rajasthan was the major focus of the present study. Methods: Nine criteria viz. mean temperature in the growing season (°C), total rainfall (mm), soil phosphorus (kg/h), soil texture, soil pH, soil organic carbon (%), salinity (dS/m), slope of the land (%) and landuse-landcover and their corresponding sub-criteria were selected. Analytic Hierarchical Process (AHP) was performed on the selected criteria through pair-wise comparison matrix and individual weights were determined and represented through Weighted Overlay Analysis (WOA). Result: Temperature in the growing season (20.68%), total rainfall (15.90%) and landuse/ landcover (14.39%) depicted relatively higher weightage with consistency ratio of 0.087. Results obtained from WOA in GIS environment depicted four suitability category namely Highly suitable (S1), Moderately suitable (S2), Marginally suitable (S3) and Restricted (N). Significant percentage of area was categorized under S2 category while S3 category was associated with least area with limitations like relatively higher slope and higher salinity. The proposed model validation was performed with overall accuracy of 88.10% using confusion matrix.","PeriodicalId":13398,"journal":{"name":"Indian Journal Of Agricultural Research","volume":"67 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Agricultural Land Suitability Categorization and Evaluation using GIS Assisted AHP in the Arid Western Plain Zone of Rajasthan, India\",\"authors\":\"Sonia ., Sunita ., Rakesh Kumar Verma, Tathagata Ghosh, Rajarshi Kumar Gaur\",\"doi\":\"10.18805/ijare.a-6085\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Background: Agricultural Land Suitability Analysis is one of the dependable method through which crop specific land suitability can be analyzed. Agricultural land suitability analysis for the pearl millet in the Arid Western Plain Zone of Rajasthan was the major focus of the present study. Methods: Nine criteria viz. mean temperature in the growing season (°C), total rainfall (mm), soil phosphorus (kg/h), soil texture, soil pH, soil organic carbon (%), salinity (dS/m), slope of the land (%) and landuse-landcover and their corresponding sub-criteria were selected. Analytic Hierarchical Process (AHP) was performed on the selected criteria through pair-wise comparison matrix and individual weights were determined and represented through Weighted Overlay Analysis (WOA). Result: Temperature in the growing season (20.68%), total rainfall (15.90%) and landuse/ landcover (14.39%) depicted relatively higher weightage with consistency ratio of 0.087. Results obtained from WOA in GIS environment depicted four suitability category namely Highly suitable (S1), Moderately suitable (S2), Marginally suitable (S3) and Restricted (N). Significant percentage of area was categorized under S2 category while S3 category was associated with least area with limitations like relatively higher slope and higher salinity. The proposed model validation was performed with overall accuracy of 88.10% using confusion matrix.\",\"PeriodicalId\":13398,\"journal\":{\"name\":\"Indian Journal Of Agricultural Research\",\"volume\":\"67 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Indian Journal Of Agricultural Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.18805/ijare.a-6085\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Agricultural and Biological Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Indian Journal Of Agricultural Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18805/ijare.a-6085","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Agricultural and Biological Sciences","Score":null,"Total":0}
Agricultural Land Suitability Categorization and Evaluation using GIS Assisted AHP in the Arid Western Plain Zone of Rajasthan, India
Background: Agricultural Land Suitability Analysis is one of the dependable method through which crop specific land suitability can be analyzed. Agricultural land suitability analysis for the pearl millet in the Arid Western Plain Zone of Rajasthan was the major focus of the present study. Methods: Nine criteria viz. mean temperature in the growing season (°C), total rainfall (mm), soil phosphorus (kg/h), soil texture, soil pH, soil organic carbon (%), salinity (dS/m), slope of the land (%) and landuse-landcover and their corresponding sub-criteria were selected. Analytic Hierarchical Process (AHP) was performed on the selected criteria through pair-wise comparison matrix and individual weights were determined and represented through Weighted Overlay Analysis (WOA). Result: Temperature in the growing season (20.68%), total rainfall (15.90%) and landuse/ landcover (14.39%) depicted relatively higher weightage with consistency ratio of 0.087. Results obtained from WOA in GIS environment depicted four suitability category namely Highly suitable (S1), Moderately suitable (S2), Marginally suitable (S3) and Restricted (N). Significant percentage of area was categorized under S2 category while S3 category was associated with least area with limitations like relatively higher slope and higher salinity. The proposed model validation was performed with overall accuracy of 88.10% using confusion matrix.