| Research Articles |
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| Soil polygon disaggregation through similarity-based prediction with legacy pedons |
| LIU Feng1*, GENG Xiaoyuan2, ZHU A-xing3,4, Walter FRASER2, SONG Xiaodong1, ZHANG Ganlin1 |
1 State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China;
2 Science and Technology Branch, Agriculture and Agri-Food Canada, Ottawa K1A 0C5, Canada;
3 School of Geography, Nanjing Normal University, Nanjing 210046, China;
4 Department of Geography, University of Wisconsin-Madison, Madison WI 53706, USA |
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Abstract Conventional soil maps generally contain one or more soil types within a single soil polygon. But their geographic locations within the polygon are not specified. This restricts current applications of the maps in site-specific agricultural management and environmental modelling. We examined the utility of legacy pedon data for disaggregating soil polygons and the effectiveness of similarity-based prediction for making use of the under- or over-sampled legacy pedon data for the disaggregation. The method consisted of three steps. First, environmental similarities between the pedon sites and each location were computed based on soil formative environmental factors. Second, according to soil types of the pedon sites, the similarities were aggregated to derive similarity distribution for each soil type. Third, a hardening process was performed on the maps to allocate candidate soil types within the polygons. The study was conducted at the soil subgroup level in a semi-arid area situated in Manitoba, Canada. Based on 186 independent pedon sites, the evaluation of the disaggregated map of soil subgroups showed an overall accuracy of 67% and a Kappa statistic of 0.62. The map represented a better spatial pattern of soil subgroups in both detail and accuracy compared to a dominant soil subgroup map, which was commonly used in practice. Incorrect predictions mainly occurred in the agricultural plain area and the soil subgroups that are very similar in taxonomy, indicating that new environmental covariates need to be developed. We concluded that the combination of legacy pedon data with similarity-based prediction is an effective solution for soil polygon disaggregation.
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Received: 22 January 2016
Published: 15 June 2016
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| Fund: This study was supported by the National Natural Science Foundation of China (41130530, 91325301, 41431177, 41571212, 41401237), the Project of “One-Three-Five” Strategic Planning & Frontier Sciences of the Institute of Soil Science, Chinese Academy of Sciences (ISSASIP1622), the Government Interest Related Program between Canadian Space Agency and Agriculture and Agri-Food, Canada (13MOA01002), and the Natural Science Research Program of Jiangsu Province (14KJA170001). |
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