中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Estimation and mapping of soil organic matter content at a national scale based on grid soil samples, a soil map and DEM data

文献类型:期刊论文

作者Yuan, Yecheng2; Li, Baolin1,2; Yu, Wanli1,2; Gao, Xizhang2
刊名ECOLOGICAL INFORMATICS
出版日期2021-12-01
卷号66页码:11
关键词Combination method Grid soil sample Continental and national scale Linkage method Extended inverse distance weighted interpolation Soil organic matter content
ISSN号1574-9541
DOI10.1016/j.ecoinf.2021.101487
通讯作者Li, Baolin(libl@lreis.ac.cn)
英文摘要Soil property maps at continental and national scales provide important input for research on biogeochemical and hydrological cycles. This paper develops a methodology for producing soil property maps at a continental or national scale based on soil samples from continental or national soil surveys (especially geochemical baseline surveys) with a 2-70 km grid, soil maps, and Digital Elevation Model data. The proposed method consists of four major steps: 1) determining the overall trend of soil property distribution using the linkage method; 2) estimating the variation inside each polygon through an extended Inverse Distance Weighted interpolation based on both the environmental similarity and spatial autocorrelation with stratification; 3) integrating variations in the soil property with its overall trend; 4) re-estimating soil properties in transition zones by using a weighted average of soil properties estimated from soil samples from different neighboring soils to produce a continuous soil property map across soil boundaries. A case study using Soil Organic Matter content as an example was conducted in Jilin Province (190,000 km(2)) in China based on soil samples from a 8-32 km grid from the China Soil Pollution Survey, the 1:1 million soil map of China and Shutter Radar Topographic Mission Digital Elevation Model data. Independent validation indicated that the proposed method decreased the mean error, the mean absolute error and the root mean square error by 10-30% compared with two commonly used soil mapping methods, the linkage method and Inverse Distance Weighted interpolation. The SOM map produced by the proposed method improved defects in the maps produced through Inverse Distance Weighted interpolation and the linkage method such as "bull's eye" patterns, abrupt change across soil boundaries and the ignored variation inside polygons on the maps. The proposed approach generates more accurate soil property maps at a continental or national scale based on grid soil samples from continental or national soil surveys than those produced through commonly used methods.
WOS关键词INFRARED REFLECTANCE SPECTROSCOPY ; CARBON STOCKS ; SIMULATION ; PREDICTION ; NITROGEN ; SYSTEM ; GROWTH ; SOTER
资助项目National Key Research and Development Plan of China[2016YFC0500205] ; National Natural Science Foundation of China[41701475]
WOS研究方向Environmental Sciences & Ecology
语种英语
WOS记录号WOS:000722195100002
出版者ELSEVIER
资助机构National Key Research and Development Plan of China ; National Natural Science Foundation of China
源URL[http://ir.igsnrr.ac.cn/handle/311030/168012]  
专题中国科学院地理科学与资源研究所
通讯作者Li, Baolin
作者单位1.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
推荐引用方式
GB/T 7714
Yuan, Yecheng,Li, Baolin,Yu, Wanli,et al. Estimation and mapping of soil organic matter content at a national scale based on grid soil samples, a soil map and DEM data[J]. ECOLOGICAL INFORMATICS,2021,66:11.
APA Yuan, Yecheng,Li, Baolin,Yu, Wanli,&Gao, Xizhang.(2021).Estimation and mapping of soil organic matter content at a national scale based on grid soil samples, a soil map and DEM data.ECOLOGICAL INFORMATICS,66,11.
MLA Yuan, Yecheng,et al."Estimation and mapping of soil organic matter content at a national scale based on grid soil samples, a soil map and DEM data".ECOLOGICAL INFORMATICS 66(2021):11.

入库方式: OAI收割

来源:地理科学与资源研究所

浏览0
下载0
收藏0
其他版本

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。