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Getting accurate predictions from large and diverse spectral libraries

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Logo of OpenGeoHub FoundationOpenGeoHub Foundation
 Ramirez-Lopez, Leonardo

Formal Metadata

Title
Getting accurate predictions from large and diverse spectral libraries
Subtitle
Think globally, fit locally (Saul and Roweis, 2003)
Title of Series
Number of Parts
4
Author
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License
CC Attribution - NonCommercial 3.0 Germany:
You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal and non-commercial purpose as long as the work is attributed to the author in the manner specified by the author or licensor.
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Publisher
Release Date2021
LanguageEnglish
Producer
Production Year2021
Production PlaceWoodwell Climate Research Centre

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Abstract
Leo Ramirez-Lopez is the head of Data Science at BÜCHI Labortechnik AG. He is the author of multiple soil spectroscopy R packages and has extensive experience with fitting calibration models with diversity of soil spectroscopy systems. In this talk he addresses complexity of global vs local models for operational use of soil spectroscopy data.
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