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首页> 外文期刊>Scientia Agricola >Decision trees for digital soil mapping on subtropical basaltic steeplands
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Decision trees for digital soil mapping on subtropical basaltic steeplands

机译:亚热带玄武质陡地数字土壤测绘的决策树

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When soil surveys are not available for land use planning activities, digital soil mapping techniques can be of assistance. Soil surveyors can process spatial information faster, to assist in the execution of traditional soil survey or predict the occurrence of soil classes across landscapes. Decision tree techniques were evaluated as tools for predicting the ocurrence of soil classes in basaltic steeplands in South Brazil. Several combinations of types of decicion tree algorithms and number of elements on terminal nodes of trees were compared using soil maps with both original and simplified legends. In general, decision tree analysis was useful for predicting occurrence of soil mapping units. Decision trees with fewer elements on terminal nodes yield higher accuracies, and legend simplification (aggregation) reduced the precision of predictions. Algorithm J48 had better performance than BF Tree, RepTree, Random Tree, and Simple Chart.
机译:如果无法进行土地使用计划活动的土壤调查,则数字土壤测绘技术可能会有所帮助。土壤测量师可以更快地处理空间信息,以帮助执行传统的土壤测量或预测整个景观中土壤分类的发生。决策树技术被评估为预测巴西南部玄武陡坡土壤类型发生的工具。使用带有原始图例和简化图例的土壤图,比较了决策树算法的类型和树的末端节点上元素数量的几种组合。通常,决策树分析可用于预测土壤测绘单元的出现。终端节点上元素较少的决策树具有较高的准确性,图例简化(聚合)会降低预测的精度。算法J48的性能优于BF树,RepTree,随机树和简单图表。

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