Improving soil organic carbon mapping with a field‐specific calibration approach through diffuse reflectance spectroscopy and machine learning algorithms-Reference-Cited by-同舟云学术

Improving soil organic carbon mapping with a field‐specific calibration approach through diffuse reflectance spectroscopy and machine learning algorithms

Published:2021-11-05 Issue:1 Volume:38 Page:292-303
ISSN:0266-0032
Container-title:Soil Use and Management
language:en
Short-container-title:Soil Use and Management

Author:

Camargo Livia Arantes¹^ORCID,Amaral Lucas Rios²^ORCID,Reis Aliny Aparecida¹^ORCID,Brasco Thiago Luis²^ORCID,Magalhães Paulo Sergio Graziano¹²^ORCID

Affiliation:

1. Interdisciplinary Centre for Energy Planning (NIPE/UNICAMP) University of Campinas Campinas Brazil

2. School of Agricultural Engineering (FEAGRI/UNICAMP) University of Campinas Campinas Brazil

Funder

Fundação de Amparo à Pesquisa do Estado de São Paulo

Publisher

Wiley

Subject

Pollution,Soil Science,Agronomy and Crop Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/sum.12775

Reference48 articles.

1. Unsupervised random forest: a tutorial with case studies

2. Standard Normal Variate Transformation and De-Trending of Near-Infrared Diffuse Reflectance Spectra

3. Reflectance measurements of soils in the laboratory: Standards and protocols

4. Field-Scale Variability of Soil Properties in Central Iowa Soils

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Temporal evaluation of soil chemical quality using VNIR and XRF spectroscopies;Soil and Tillage Research;2024-08

2. Best performances of visible–near-infrared models in soils with little carbonate – a field study in Switzerland;SOIL;2024-04-10

3. Near‐infrared spectroscopy as an alternative tool for predicting soil erodibility in a watershed under desertification;Land Degradation & Development;2023-12-26

4. Improved three‐dimensional mapping of soil chromium pollution with sparse borehole data: Incorporating multisource auxiliary data into IDW‐based interpolation;Soil Use and Management;2023-03-17

5. Mapping soil arsenic pollution at a brownfield site using satellite hyperspectral imagery and machine learning;Science of The Total Environment;2023-01