Visible, near-infrared, and shortwave-infrared spectra as an input variable for digital mapping of soil organic carbon

IF 7.3 1区 农林科学 Q1 ENVIRONMENTAL SCIENCES
Vahid Khosravi , Asa Gholizadeh , Radka Kodešová , Prince Chapman Agyeman , Mohammadmehdi Saberioon , Luboš Borůvka
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引用次数: 0

Abstract

This study proposes a novel methodology to employ discrete point spectra as input variable for digital mapping of soil organic carbon (SOC). Accordingly, two SOC modeling approaches were used in three agricultural sites in Czech Republic: i) machine learning (ML) including partial least squares regression (PLSR), cubist, random forest (RF), and support vector regression (SVR), and ii) regression kriging (RK) by the combination of ordinary kriging (OK) and PLSR (PLSR-K), cubist (cubist-K), RF (RF-K), and SVR (SVR-K). Models were developed on environmental predictor covariates (EPCs) and thirty genetic algorithms (GA)-selected visible, near-infrared, and shortwave-infrared (VNIR–SWIR) wavelengths spectra, individually and combined. Thirty rasters were then created using interpolation of the selected spectra and served as the input variables – with and without EPCs – to test and compare the developed models and SOC predictive maps with each other and with those retrieved from the third approach: iii) kriging using OK of the measured and ML-predicted SOC. The impact of employing selected wavelengths’ spectra and EPCs on models' performance was investigated using independent test samples and the uncertainty associated with the produced maps. Using interpolated spectra as the only input variable yielded a relatively acceptable accuracy (Nová Ves: RMSE = 0.19%, Údrnice: RMSE = 0.12%, Klučov: RMSE = 0.13%). In comparison, the interpolated spectra coupled with EPCs enhanced the results. Regarding the uncertainty, however, the ML-based SOC maps were more reliable, than RK-based ones. Furthermore, maps produced using both spectra and EPCs showed less uncertainty than those constructed on the individual datasets.
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来源期刊
International Soil and Water Conservation Research
International Soil and Water Conservation Research Agricultural and Biological Sciences-Agronomy and Crop Science
CiteScore
12.00
自引率
3.10%
发文量
171
审稿时长
49 days
期刊介绍: The International Soil and Water Conservation Research (ISWCR), the official journal of World Association of Soil and Water Conservation (WASWAC) http://www.waswac.org, is a multidisciplinary journal of soil and water conservation research, practice, policy, and perspectives. It aims to disseminate new knowledge and promote the practice of soil and water conservation. The scope of International Soil and Water Conservation Research includes research, strategies, and technologies for prediction, prevention, and protection of soil and water resources. It deals with identification, characterization, and modeling; dynamic monitoring and evaluation; assessment and management of conservation practice and creation and implementation of quality standards. Examples of appropriate topical areas include (but are not limited to): • Conservation models, tools, and technologies • Conservation agricultural • Soil health resources, indicators, assessment, and management • Land degradation • Sustainable development • Soil erosion and its control • Soil erosion processes • Water resources assessment and management • Watershed management • Soil erosion models • Literature review on topics related soil and water conservation research
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