Spatial Prediction of Total Nitrogen in Soil Surface Layer Based on Machine Learning

Zunfang Liu, Haochuan Lei (), Lei Lei and Haiyan Sheng
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Zunfang Liu: Department of Geological Engineering, Qinghai University, Xining 810016, China
Haochuan Lei: Department of Geological Engineering, Qinghai University, Xining 810016, China
Lei Lei: Department of Geological Engineering, Qinghai University, Xining 810016, China
Haiyan Sheng: College of Agriculture and Animal Husbandry, Qinghai University, Xining 810016, China

Sustainability, 2022, vol. 14, issue 19, 1-14

Abstract: In order to satisfy the basic requirements of sustainable agricultural development, it is important to understand the spatial distribution characteristics of soil total nitrogen (TN) content to better guide accurate fertilization to increase grain yield. To this end, this paper constructs three inversion models of partial least squares regression (PLSR), back propagation neural network (BPNN) and support vector machines (SVM) with remote sensing data to predict the TN content in Datong County, Xining City, Qinghai Province, China. The results showed that the average TN content was 1.864 g/kg, and the coefficient of variation (CV) was 30.596%. The prediction accuracy of the SVM model (R 2 = 0.676, RMSE = 0.296) among the three inversion models was higher than that of the BPNN model (R 2 = 0.560, RMSE = 0.305) and the PLSR model (R 2 = 0.374, RMSE = 0.334). The model with the highest accuracy predicted the spatial distribution of TN, and TN content showed a spatial distribution trend which was high in the northwest and low in the southeast, and gradually decreased from north to south. This study provides reference basis and support for soil fertility evaluations and sustainable agricultural development.

Keywords: soil total nitrogen; BP neural network; support vector machines; spatial distribution; remote sensing (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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