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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Hauptverfasser:	Charles Nickmilder, Anthony Tedde, Isabelle Dufrasne, Françoise Lessire, Bernard Tychon, Yannick Curnel, Jérome Bindelle, Hélène Soyeurt
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	MDPI AG 2021-01-01
Schriftenreihe:	Remote Sensing
Schlagworte:	Sentinel-1 Sentinel-2 machine learning pastures compressed sward height
Online-Zugang:	https://www.mdpi.com/2072-4292/13/3/408
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