Deployment of models predicting compressed sward height on Wallonia: confrontation to ground truth
peer reviewed ; Currently, pasture management is of interest for economical or ecological reasons. The use of remote sensed data and the implementation of machine learning algorithms is growing. So, over the past two years, models predicting the available compressed sward height (CSH) in Walloon pastures using Sentinel-1, Sentinel-2, and meteorological data were published. Those models were developed to be integrated in a decision support system (DSS). A platform predicting CSH over Wallonia was therefore developed. The variability of the predicted CSH within parcels ranged from 0 to 287.7% on... Mehr ...
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Dokumenttyp: | conference paper not in proceedings |
Erscheinungsdatum: | 2022 |
Schlagwörter: | machine learning / decision support system / pastures / remote sensing / grassland / Wallonia / Life sciences / Agriculture & agronomy / Sciences du vivant / Agriculture & agronomie |
Sprache: | Englisch |
Permalink: | https://search.fid-benelux.de/Record/base-26902596 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | https://orbi.uliege.be/handle/2268/295831 |