Regional Soil Mapping Using Multi-Grade Representative Sampling and a Fuzzy Membership-Based Mapping Approach
文献类型：期刊论文
| 作者 | Yang Lin2,3; Zhu, A-Xing3,4,5,6,7; Zhao Yuguo2; Li Decheng2; Zhang Ganlin2; Zhang Shujie8; Band, Lawrence E.1 |
| 刊名 | PEDOSPHERE
 |
| 出版日期 | 2017-04-01 |
| 卷号 | 27期号:2页码:344-357 |
| 关键词 | fuzzy clustering parent lithology representative grade sampling strategy soil spatial variations |
| ISSN号 | 1002-0160 |
| DOI | 10.1016/S1002-0160(17)60322-9 |
| 通讯作者 | Zhu, A-Xing(axing@lreis.ac.cn) |
| 英文摘要 | 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 km(2) 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. |
| WOS关键词 | GEOGRAPHICALLY WEIGHTED REGRESSION ; ORGANIC-CARBON STOCKS ; FOREST SOILS ; INFORMATION ; SCALE ; OPTIMIZATION ; ALGORITHM ; MODELS ; GIS |
| 资助项目 | National Natural Science Foundation of China[41471178] ; National Natural Science Foundation of China[41530749] ; National Natural Science Foundation of China[41431177] ; State Key Laboratory of Soil and Sustainable Agriculture, China[Y052010002] ; Natural Science Research Program of Jiangsu, China[14KJA170001] ; National Key Technology Innovation Project for Water Pollution Control and Remediation, China[2013ZX07103006] ; National Basic Research Program (973 Program) of China[2015CB954102] ; Vilas Associate Award ; Hammel Faculty Fellow Award ; Manasse Chair Professorship through the University of Wisconsin Madison ; One-Thousand Talents Program of China |
| WOS研究方向 | Agriculture |
| 语种 | 英语 |
| WOS记录号 | WOS:000399261800015 |
| 出版者 | SCIENCE PRESS |
| 资助机构 | National Natural Science Foundation of China ; State Key Laboratory of Soil and Sustainable Agriculture, China ; Natural Science Research Program of Jiangsu, China ; National Key Technology Innovation Project for Water Pollution Control and Remediation, China ; National Basic Research Program (973 Program) of China ; Vilas Associate Award ; Hammel Faculty Fellow Award ; Manasse Chair Professorship through the University of Wisconsin Madison ; One-Thousand Talents Program of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/64556]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Zhu, A-Xing |
| 作者单位 | 1.Univ N Carolina, Inst Environm, Chapel Hill, NC 27599 USA 2.Chinese Acad Sci, Inst Soil Sci, State Key Lab Soil & Sustainable Agr, Nanjing 210008, Peoples R China 3.Chinese Acad Sci, Inst Geog Sci & Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 4.Nanjing Normal Univ, Minist Educ, Key Lab Virtual Geog Environm, Nanjing 210023, Jiangsu, Peoples R China 5.Nanjing Normal Univ, Sch Geog, Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210023, Jiangsu, Peoples R China 6.State Key Lab Cultivat Base Geog Environm Evolut, Nanjing 210023, Jiangsu, Peoples R China 7.Univ Wisconsin, Dept Geog, Madison, WI 53706 USA 8.China Acad Urban Planning & Design, Beijing 100037, Peoples R China |
| 推荐引用方式 GB/T 7714 | Yang Lin,Zhu, A-Xing,Zhao Yuguo,et al. Regional Soil Mapping Using Multi-Grade Representative Sampling and a Fuzzy Membership-Based Mapping Approach[J]. PEDOSPHERE,2017,27(2):344-357. |
| APA | Yang Lin.,Zhu, A-Xing.,Zhao Yuguo.,Li Decheng.,Zhang Ganlin.,...&Band, Lawrence E..(2017).Regional Soil Mapping Using Multi-Grade Representative Sampling and a Fuzzy Membership-Based Mapping Approach.PEDOSPHERE,27(2),344-357. |
| MLA | Yang Lin,et al."Regional Soil Mapping Using Multi-Grade Representative Sampling and a Fuzzy Membership-Based Mapping Approach".PEDOSPHERE 27.2(2017):344-357. |
入库方式： OAI收割
来源：地理科学与资源研究所
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