Development of Machine Learning Models to Predict Compressed Sward Height in Walloon Pastures Based on Sentinel-1, Sentinel-2 and Meteorological Data Using Multiple Data Transformations

Development of Machine Learning Models to Predict Compressed Sward Height in Walloon Pastures Based on Sentinel-1, Sentinel-2 and Meteorological Data Using Multiple Data Transformations

Accurate information about the available standing biomass on pastures is critical for the adequate management of grazing and its promotion to farmers. In this paper, machine learning models are developed to predict available biomass expressed as compressed sward height (CSH) from readily accessible...

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Bibliographic Details
Main Authors: Charles Nickmilder, Anthony Tedde, Isabelle Dufrasne, Françoise Lessire, Bernard Tychon, Yannick Curnel, Jérome Bindelle, Hélène Soyeurt
Format: Article
Language:English
Published: MDPI AG 2021-01-01
Series:Remote Sensing
Subjects:
Sentinel-1
Sentinel-2
machine learning
pastures
compressed sward height
Online Access:https://www.mdpi.com/2072-4292/13/3/408

Internet

https://www.mdpi.com/2072-4292/13/3/408

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