Abstract
Accurate estimates of the spatial distribution of total nitrogen (TN) in soil are fundamental for soil quality assessment, decision making in land management, and global nitrogen cycle modeling. In China, current maps are limited to individual regions or are of coarse resolution. In this study, we compiled a new 90-m resolution map of soil TN in China by the weighted summation of random forest and extreme gradient boosting. After harmonizing soil data from 4022 soil profiles into a fixed soil depth (0–20 cm) by equal area spline, 18 environmental covariates were employed to characterize the spatial pattern of soil TN in topsoil across China. The accuracy assessments from independent validation data showed that the weighted model averaging gave the best predictions with an acceptable R2 (0.41). The prediction map showed that high-value areas of soil TN were mainly distributed in the eastern Tibetan Plateau, central Qilian Mountains and the north of the Greater Khingan Range. Climate factors had a considerable influence on the variation of the soil TN, and land-use types played a pivotal part in each climate zone. This high-resolution and high-quality soil TN data set in China can be very useful for future inventories of soil nitrogen, assessments of soil nutrient status, and management of arable land.
Highlights
Soil nitrogen is a common macronutrient needed by plants for vegetation growth [1]
An explicit understanding of soil nitrogen content and its spatial variation are of great importance for soil quality assessment, decision making in land management, and global nitrogen cycle modeling, which have grave impacts on various global issues
The objectives of this study were to: (1) construct soil total nitrogen (TN) prediction models by different machine-learning approaches and combine them by weighted model averaging; (2) compare and select the most robust model to map the national distribution of topsoil TN content at a spatial resolution of 90 m and estimate its prediction uncertainty; (3) identify the controlling factors of the spatial distribution patterns of soil TN
Summary
Soil nitrogen is a common macronutrient needed by plants for vegetation growth [1]. Changes in the soil nitrogen, an important part of the nitrogen cycle, can affect the stability and sustainability of global ecosystems [2,3]. Via the biological processes of nitrification and denitrification, excessive soil nitrogen can diffuse into the atmosphere as a greenhouse gas (N2 O and NO) [4,5]. Dissolved nitrogen may seep into water bodies where it may contribute to eutrophication and trigger other ecosystem changes and responses [6]. An explicit understanding of soil nitrogen content and its spatial variation are of great importance for soil quality assessment, decision making in land management, and global nitrogen cycle modeling, which have grave impacts on various global issues. The procedure is laborious, time-consuming, expensive, Remote Sens. 2020, 12, 85; doi:10.3390/rs12010085 www.mdpi.com/journal/remotesensing
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