Application of Ordinary Kriging and Regression Kriging Method for Soil Properties Mapping in Hilly Region of Central Vietnam

Abstract

Soil property maps are essential resources for agricultural land use. However, soil properties mapping is costly and time-consuming, especially in the regions with complicated topographic conditions. This study was conducted in a hilly region of Central Vietnam with the following objectives: (i) to evaluate the best environmental variables to estimate soil organic carbon (SOC), total nitrogen (TN), and soil reaction (pH) with a regression kriging (RK) model, and (ii) to compare the accuracy of the ordinary kriging (OK) and RK methods. SOC, TN, and soil pH data were measured at 155 locations within the research area with a sampling grid of 2 km × 2 km for a soil layer from 0 to 30 cm depth. From these samples, 117 were used for interpolation, and the 38 randomly remaining samples were used for evaluating accuracy. The chosen environmental variables are land use type (LUT), topographic wetness index (TWI), and transformed soil adjusted vegetation index (TSAVI). The results indicate that the LUT variable is more effective than TWI and TSAVI for determining TN and pH when using the RK method, with a variance of 7.00% and 18.40%, respectively. In contrast, a combination of the LUT and TWI variables is the best for SOC mapping with the RK method, with a variance of 14.98%. The OK method seemed more accurate than the RK method for SOC mapping by 3.33% and for TN mapping by 10% but the RK method was found more precise than the OK method for soil pH mapping by 1.81%. Further selection of auxiliary variables and higher sampling density should be considered to improve the accuracy of the RK method.

Multi-Criteria Decision Analysis for the Land Evaluation of Potential Agricultural Land Use Types in a Hilly Area of Central Vietnam

“…The use of a Geographic Information System proved to be highly useful in the context of land suitability evaluation, as it facilitates the geographic assignment of criteria to land units. For physical criteria, random sampling and interpolation proved to be an adequate approach to represent the physical conditions in the area [42]. However, the Boolean approach still has limitations on the ability to express the transitional or continuous variation in geographical features [64].…”

Statistical analysis of the best GIS interpolation method for bearing capacity estimation in An-Najaf City, Iraq

“…where:k i : The weights. l is the lag range constant; and (× 0 _ xi) is the semivariogram value of the distance between × 0 and xi (Gia Pham et al 2019;Mohammadi et al 2019;Zeng et al 2020). A semivariogram is expressed as follows:…”

Áp Dụng Phương Pháp Nội Suy Hồi Quy Kriging Xây Dựng Bản Đồ Hàm Lượng Cacbon Hữu Cơ Trong Đất Tại Xã Hương Lâm, Huyện a Lưới, Tỉnh Thừa Thiên Huế

“…Cùng với sự phát triển của hệ thống thông tin địa lý (GIS), nhiều phương pháp đã được tích hợp trong các phần mềm GIS và ứng dụng để nội suy bản đồ tính chất đất như phương pháp nội suy thông thường (Ordinary Kriging) và phương pháp nghịch đảo khoảng cách (IDW) [3]; [15]. Sự phổ biến của các phương pháp này đã được chứng minh [19]; [18]), nhưng chúng thường chỉ mang tính cơ học, tức là chỉ dựa vào mối quan hệ không gian giữa các điểm nội suy chứ chưa chú ý đến các đặc điểm môi trường.…”