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Regional Soil Mapping Using Multi-Grade Representative Sampling and a Fuzzy Membership-Based Mapping Approach

机译：基于多级代表性抽样和基于模糊隶属度的映射方法的区域土壤图

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摘要

High-resolution and detailed regional soil spatial distribution information is increasingly needed for ecological modeling and land resource management.For areas with no point data,regional soil mapping includes two steps:soil sampling and soil mapping.Because sampling over a large area is costly,efficient sampling strategies are required.A multi-grade representative sampling strategy,which designs a small number of representative samples with different representative grades to depict soil spatial variations at different scales,could be a potentially efficient sampling strategy for regional soil mapping.Additionally,a suitable soil mapping approach is needed to map regional soil variations based on a small number of samples.In this study,the multi-grade representative sampling strategy was applied and a fuzzy membership-weighted soil mapping approach was developed to map soil sand percentage and soil organic carbon (SOC) at 0-20 and 20-40 cm depths in a study area of 5 900 km2 in Anhui Province of China.First,geographical sub-areas were delineated using a parent lithology data layer.Next,fuzzy c-means clustering was applied to two climate and four terrain variables in each stratum.The clustering results (environmental cluster chains) were used to locate representative samples.Evaluations based on an independent validation sample set showed that the addition of samples with lower representativeness generally led to a decrease of root mean square error (RMSE).The declining rates of RMSE with the addition of samples slowed down for 20-40 cm depth,but fluctuated for 0-20 cm depth.The predicted SOC maps based on the representative samples exhibited higher accuracy,especially for soil depth 20-40 cm,as compared to those based on legacy soil data.Multi-grade representative sampling could be an effective sampling strategy at a regional scale.This sampling strategy,combined with the fuzzy membership-based mapping approach,could be an optional effective framework for regional soil property mapping.A more detailed and accurate soil parent material map and the addition of environmental variables representing human activities would improve mapping accuracy.
机译：对于生态建模和土地资源管理，越来越需要高分辨率和详细的区域土壤空间分布信息。对于没有点数据的区域，区域土壤测绘包括两个步骤：土壤采样和土壤测绘。由于在大面积上采样非常昂贵，需要一种有效的采样策略。多级代表性采样策略可以设计出少量具有不同代表​​性等级的代表性样本，以描述不同尺度下的土壤空间变化，这可能是区域土壤测绘的潜在有效采样策略。本研究采用多级代表性采样策略，并建立了模糊隶属加权土壤测绘方法，以绘制土壤含沙量和土壤图。安徽5900 km2研究区中0-20和20-40 cm深度的有机碳（SOC）中国省。首先，使用父岩性数据层划定地理子区域。其次，将模糊c均值聚类应用于每个层的两个气候和四个地形变量。聚类结果（环境聚类链）用于定位代表性样本。基于独立验证样本集的评估表明，代表性较低的样本的添加通常会导致均方根误差（RMSE）的降低.RMSE随样本添加的下降速度在20-深度为40 cm，但在0-20 cm深度处波动。与基于传统土壤数据的SOC图相比，基于代表性样品的预测SOC图显示出更高的准确性，特别是对于20-40 cm的土壤深度。可能是区域范围内有效的抽样策略。该抽样策略与基于模糊隶属度的映射方法相结合，可以成为区域性的可选有效框架。土壤属性制图：更详细，准确的土壤母体材料图以及增加代表人类活动的环境变量将提高制图精度。

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  • 来源
    《土壤圈（英文版）》 |2017年第2期|344-357|共14页
  • 作者

    YANG Lin; A-Xing ZHU; ZHAO Yuguo; LI Decheng; ZHANG Ganlin; ZHANG Shujie; Lawrence E.BAND;

  • 作者单位

    State Key Laboratory of Soil and Sustainable Agriculture,Institute of Soil Science,Chinese Academy of Sciences,Nanjing 210008(China);

    State Key Laboratory of Resources and Environment Information System,Institute of Geographical Sciences and Resources Research,Chinese Academy of Sciences,Beijing 100101(China);

    State Key Laboratory of Resources and Environment Information System,Institute of Geographical Sciences and Resources Research,Chinese Academy of Sciences,Beijing 100101(China);

    Key Laboratory of Virtual Geographic Environment(Nanjing Normal University),Ministry of Education,Nanjing 210023(China);

    Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application,School of Geography,Nanjing Normal University,Nanjing 210023(China);

    State Key Laboratory Cultivation Base of Geographical Environment Evolution(Jiangsu Province),Nanjing 210023(China);

    Department of Geography,University of Wisconsin-Madison,Madison WI 53706(USA);

    State Key Laboratory of Soil and Sustainable Agriculture,Institute of Soil Science,Chinese Academy of Sciences,Nanjing 210008(China);

    State Key Laboratory of Soil and Sustainable Agriculture,Institute of Soil Science,Chinese Academy of Sciences,Nanjing 210008(China);

    State Key Laboratory of Soil and Sustainable Agriculture,Institute of Soil Science,Chinese Academy of Sciences,Nanjing 210008(China);

    China Academy of Urban Planning & Design,Beijing 100037(China);

    Institute for the Environment,University of North Carolina,Chapel Hill,Chapel Hill NC 27599(USA);

  • 收录信息 中国科学引文数据库(CSCD);中国科技论文与引文数据库(CSTPCD);
  • 原文格式 PDF
  • 正文语种 eng
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