Multi-scale digital terrain analysis and feature selection for digital soil mapping
文献类型：SCI/SSCI论文
| 作者 | Behrens T. ; Zhu A. X. ; Schmidt K. ; Scholten T. |
| 发表日期 | 2010 |
| 关键词 | Multi-scale digital terrain analysis Feature selection Spatial data mining Digital soil mapping ANOVA Principal components analysis Random subsets Decision trees scale-dependent correlation random subspace method dem resolution fuzzy-logic map scale model landscapes areas silty size |
| 英文摘要 | Terrain attributes are the most widely used predictors in digital soil mapping. Nevertheless, discussion of techniques for addressing scale issues and feature selection has been limited. Therefore, we provide a framework for incorporating multi-scale concepts into digital soil mapping and for evaluating these scale effects. Furthermore, soil formation and soil-forming factors vary and respond at different scales. The spatial data mining approach presented here helps to identify both the scale which is important for mapping soil classes and the predictive power of different terrain attributes at different scales. The multi-scale digital terrain analysis approach is based on multiple local average filters with filter sizes ranging from 3 x 3 up to 31 x 31 pixels. We used a 20-m DEM and a 1:50 000 soil map for this study. The feature space is extended to include the terrain conditions measured at different scales, which results in highly correlated features (terrain attributes). Techniques to condense the feature space are therefore used in order to extract the relevant soil forming features and scales. The prediction results, which are based on a robust classification tree (CRUISE) show that the spatial pattern of particular soil classes varies at characteristic scales in response to particular terrain attributes. It is shown that some soil classes are more prevalent at one scale than at other scales and more related to some terrain attributes than to others. Furthermore, the Most computationally efficient ANOVA-based feature selection approach is competitive in terms of prediction accuracy and the interpretation of the condensed datasets. Finally, we conclude that multi-scale as well as feature selection approaches deserve more research so that digital soil mapping techniques are applied in a proper spatial context and better prediction accuracy can be achieved. (C) 2009 Published by Elsevier B.V. |
| 出处 | Geoderma |
| 卷 | 155 |
| 期 | 3-4 |
| 页 | 175-185 |
| 收录类别 | SCI |
| 语种 | 英语 |
| ISSN号 | 0016-7061 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/24300]  |
| 专题 | 地理科学与资源研究所_历年回溯文献 |
| 推荐引用方式 GB/T 7714 | Behrens T.,Zhu A. X.,Schmidt K.,et al. Multi-scale digital terrain analysis and feature selection for digital soil mapping. 2010. |
入库方式： OAI收割
来源：地理科学与资源研究所
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