Mapping the spatial distribution of soil depth in a grassland ecosystem with the aid of ground penetrating radar and GIS (Northwestern Sichuan, China). (22nd May 2018)

• Record Type: Journal Article
• Authors: Zhang, Xuelian; Dao, Ligang; Zhang, Chaosheng; Morrison, Liam; Hong, Bing; Zhang, Hongxuan; Gan, Youmin
• Is Part Of: Grassland science. Volume 64:Number 4(2018)
• Page Start: 217
• Page End: 225
• Publication Date: 2018-05-22
• Subjects: GIS -- ground penetrating radar -- soil depth -- spatial distribution; Grasslands -- Periodicals; Grasslands -- Management -- Periodicals; 578.74
• DOI: 10.1111/grs.12201
• Languages: English
• ISSNs: 1744-6961

Abstract

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 10 km 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 3 cm of the actual soil depth in 93% of all samples, and within 5 cm 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.