Mapping the spatial distribution of soil depth in a grassland ecosystem with the aid of ground penetrating radar and GIS (Northwestern Sichuan, China) | |
Xuelian Zhang; Ligang Dao; Chaosheng Zhang; Liam Morrison; Bing Hong; Hongxuan Zhang; Youmin Gan | |
2018 | |
Source Publication | Grassland Science
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Volume | 64Issue:4Pages:217-225 |
Abstract | Obtaining accurate soil depth information is critical to improving how we assess the health and manage of soil resources that contribute to sustainable management of agricultural lands. While there are many techniques to assess soil characteristics, using ground penetrating radar (GPR) to determine soil depth has received little attention. This study aimed to determine the suitability of GPR for obtaining accurate soil depth information over a 10km intervals grid system in a generally flat grasslands ecosystem in the Sichuan Province of China. Geographic information system (GIS) and geostatistical techniques were used to map the spatial distribution of soil depth across the field site. Images created from GPR were filtered using DC removal and automatic gain control, and log-transformation was used to transform the raw data in order to conform a normal distribution. The soil depth data were spatially interpolated across the field site using the geostatistical techniques of (semi-) variogram and ordinary kriging (OK), then ground-truthed and validated via comparison with traditional methods and previously collected data. A total of 39 random data points (ruler-measured and GPR data) were selected to evaluate the accuracy of the GPR, and results showed that the difference were within 3cm of the actual soil depth in 93% of all samples, and within 5cm in all samples (R-2=0.914). Results confirmed that this GPR reflection technique has the potential to precisely and quickly measure soil depth over large areas and under variable topography, contributing to the body of technical information that can help inform soil management policy for sustainable agriculture. The spatial distribution map of soil depth produced with the aid of OK demonstrated the accuracy and non-destructive features of GPR, which is able to provide a more detailed map of soil depth than methods used in previous grassland soil depth studies. |
Keyword | Gis Ground Penetrating Radar Soil Depth Spatial Distribution |
Indexed By | SCI |
Language | 英语 |
Document Type | 期刊论文 |
Identifier | http://ir.gyig.ac.cn/handle/42920512-1/8894 |
Collection | 环境地球化学国家重点实验室 |
Affiliation | 1.Sichuan Agricultural University, Chengdu, China 2.Management Center of Education Infrastructure Equipment and Asset, Minhang District, China 3.GIS Centre, Sichuan Academy of Grassland Science, Chengdu, China 4.School of Geography and Archaeology, National University of Ireland, Galway, Ireland 5.Earth and Ocean Sciences, School of Natural Sciences and Ryan Institute, National University of Ireland, Galway, Ireland 6.State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang, China |
Recommended Citation GB/T 7714 | Xuelian Zhang;Ligang Dao;Chaosheng Zhang;Liam Morrison;Bing Hong;Hongxuan Zhang;Youmin Gan. Mapping the spatial distribution of soil depth in a grassland ecosystem with the aid of ground penetrating radar and GIS (Northwestern Sichuan, China)[J]. Grassland Science,2018,64(4):217-225. |
APA | Xuelian Zhang;Ligang Dao;Chaosheng Zhang;Liam Morrison;Bing Hong;Hongxuan Zhang;Youmin Gan.(2018).Mapping the spatial distribution of soil depth in a grassland ecosystem with the aid of ground penetrating radar and GIS (Northwestern Sichuan, China).Grassland Science,64(4),217-225. |
MLA | Xuelian Zhang;Ligang Dao;Chaosheng Zhang;Liam Morrison;Bing Hong;Hongxuan Zhang;Youmin Gan."Mapping the spatial distribution of soil depth in a grassland ecosystem with the aid of ground penetrating radar and GIS (Northwestern Sichuan, China)".Grassland Science 64.4(2018):217-225. |
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