Using soil library hyperspectral reflectance and machine learning to predict soil organic carbon: Assessing potential of airborne and spaceborne optical soil sensing

Title
Using soil library hyperspectral reflectance and machine learning to predict soil organic carbon: Assessing potential of airborne and spaceborne optical soil sensing
Authors
Keywords
Spectroscopy, Soil organic carbon, Hyperspectral reflectance, Radiative transfer modeling, Machine learning, Long short-term memory, SBG
Journal
REMOTE SENSING OF ENVIRONMENT
Volume 271, Issue -, Pages 112914
Publisher
Elsevier BV
Online
2022-02-02
DOI
10.1016/j.rse.2022.112914

Ask authors/readers for more resources

Reprint

Contact the author

Create your own webinar

Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.

Create Now

Become a Peeref-certified reviewer

The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.

Get Started