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Estimation of Soil Cations Based on Visible and Near-Infrared Spectroscopy and Machine Learning

Authors :
Yiping Peng
Ting Wang
Shujuan Xie
Zhenhua Liu
Chenjie Lin
Yueming Hu
Jianfang Wang
Xiaoyun Mao
Source :
Agriculture, Vol 13, Iss 6, p 1237 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

Soil exchange cations are a basic indicator of soil quality and environmental clean-up potential. The accurate and efficient acquisition of information on soil cation content is of great importance for the monitoring of soil quality and pollution prevention. At present, few scholars focus on soil exchangeable cations using remote sensing technology. This study proposes a new method for estimating soil cation content using hyperspectral data. In particular, we introduce Boruta and successive projection (SPA) algorithms to screen feature variables, and we use Guangdong Province, China, as the study area. The backpropagation neural network (BPNN), genetic algorithm–based back propagation neural network (GABP) and random forest (RF) algorithms with 10-fold cross-validation are implemented to determine the most accurate model for soil cation (Ca2+, K+, Mg2+, and Na+) content estimations. The model and hyperspectral images are combined to perform the spatial mapping of soil Mg2+ and to obtain the spatial distribution information of images. The results show that Boruta was the optimal algorithm for determining the characteristic bands of soil Ca2+ and Na+, and SPA was the optimal algorithm for determining the characteristic bands of soil K+ and Mg2+. The most accurate estimation models for soil Ca2+, K+, Mg2+, and Na+ contents were Boruta-RF, SPA-GABP, SPA-RF and Boruta-RF, respectively. The estimation effect of soil Mg2+ (R2 = 0.90, ratio of performance to interquartile range (RPIQ) = 3.84) was significantly better than the other three elements (Ca2+: R2 = 0.83, RPIQ = 2.47; K+: R2 = 0.83, RPIQ = 2.58; Na+: R2 = 0.85, RPIQ = 2.63). Moreover, the SPA-RF method combined with HJ-1A HSI images was selected for the spatial mapping of soil Mg2+ content with an R2 of 0.71 and RPIQ of 2.05. This indicates the ability of the SPA-RF method to retrieve soil Mg2+ content at the regional scale.

Details

Language :
English
ISSN :
20770472
Volume :
13
Issue :
6
Database :
Directory of Open Access Journals
Journal :
Agriculture
Publication Type :
Academic Journal
Accession number :
edsdoj.0f4dc681746a499bb49e65dc7d5da9ad
Document Type :
article
Full Text :
https://doi.org/10.3390/agriculture13061237