[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2056":3},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":24,"tags":26,"view_count":32,"doi":33,"paper":34,"created_at":57},2056,"Land suitability assessment for irrigated lentil cultivation in Southwest Shewa Zone, Ethiopia using remote sensing, GIS, and the analytic hierarchy process","https:\u002F\u002Fdoi.org\u002F10.1038\u002Fs41598-026-70025-3","Sustainable expansion of irrigated agriculture requires accurate identification of suitable land areas based on biophysical conditions. This study evaluates land suitability for irrigated lentils cultivation in Southwest Shewa Zone, Ethiopia, using an integrated Remote Sensing (RS), Geographic Information System (GIS), and Analytical Hierarchy Process (AHP) approach. Nine suitability criteria, including temperature, land use\u002Fland cover, slope, elevation, soil type, soil texture, soil pH, soil drainage, and distance to water sources, were analyzed to develop a spatial suitability map. The AHP approach was applied to determine the relative importance of each criterion, with distance to water (32.5%) and slope (28.2%) identified as the most influential factors. The results classified the study area into four suitability categories: highly suitable (10.47%), moderately suitable (30.47%), marginally suitable (38.88%), and not suitable (20.18%). Model performance was evaluated using Receiver Operating Characteristic (ROC) analysis, producing an Area Under the Curve (AUC) value of 0.766, indicating good predictive performance of the suitability model. The findings reveal that 40.94% of the area has high to moderate potential for irrigated lentils production, while limitations are mainly associated with soil conditions, slope, and water accessibility. The study provides a spatial decision-support framework for identifying suitable areas, prioritizing irrigation development, and promoting sustainable land resource management and climate-resilient lentils production in Ethiopia.","灌溉农业的可持续扩展需要基于生物物理条件准确识别适宜土地区域。本研究采用遥感（RS）、地理信息系统（GIS）与层次分析法（AHP）相结合的方法，评估埃塞俄比亚西南绍阿区灌溉小扁豆种植的土地适宜性。研究分析了九个适宜性指标，包括温度、土地利用\u002F土地覆盖、坡度、海拔、土壤类型、土壤质地、土壤pH值、土壤排水和距水源距离，以绘制空间适宜性图。采用层次分析法确定各指标的相对重要性，其中距水源距离（32.5%）和坡度（28.2%）被识别为影响最大的因素。结果将研究区划分为四个适宜性等级：高度适宜（10.47%）、中度适宜（30.47%）、勉强适宜（38.88%）和不适宜（20.18%）。采用受试者工作特征（ROC）分析评估模型性能，得到曲线下面积（AUC）值为0.766，表明适宜性模型具有良好的预测性能。研究结果表明，40.94%的区域具有灌溉小扁豆生产的高度至中度潜力，而限制因素主要与土壤条件、坡度和水源可及性有关。本研究提供了一个空间决策支持框架，用于识别适宜区域、优先安排灌溉开发，并促进埃塞俄比亚土地资源的可持续管理和气候适应型小扁豆生产。",null,"Scientific Reports","2026-09-09T00:00:00Z","论文",10,false,72,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},12,21,17,14,8,1,"方法集成规范、结论有数据支撑，但属埃塞俄比亚区域案例，对国内三农实践的直接参考价值有限，适合作为农业遥感方法类资讯收录。",[25],{"name":10,"url":6},[27,28,29,30,31],"遥感","GIS","智慧灌溉","土地适宜性","小扁豆",0,"10.1038\u002Fs41598-026-70025-3",{"doi":33,"openalex_id":35,"authors":36,"venue":10,"cited_by_count":32,"oa_url":6,"card":50,"direction":54,"ingested_from":56},"W7211993031",[37,40,42,44,47],{"name":38,"orcid":39},"Kanenus Fufa Dararo","https:\u002F\u002Forcid.org\u002F0009-0007-5747-1558",{"name":41,"orcid":9},"Diro Lenjisa Geleto",{"name":43,"orcid":9},"Aster Chalchisa Eggi",{"name":45,"orcid":46},"Firdissa Sadeta Tiye","https:\u002F\u002Forcid.org\u002F0000-0002-9233-1741",{"name":48,"orcid":49},"Bekele Bedada Damtie","https:\u002F\u002Forcid.org\u002F0000-0003-3673-8560",{"tldr":51,"method":52,"finding":53,"direction":54,"opportunity":55},"用遥感、GIS与AHP评估埃塞俄比亚西南绍阿区灌溉扁豆种植土地适宜性并制图。","遥感、GIS与层次分析法（AHP），分析9项生物物理与水源距离指标，ROC验证。","高至中度适宜区占40.94%，距水源与坡度影响最大，模型AUC为0.766。","农业遥感与作物表型","可引入多时相遥感与气候情景，动态评估灌溉适宜性并耦合作物模型优化布局。","openalex","2026-09-10T23:30:27.675890Z"]