Sammendrag
Pastures are botanically diverse and difficult to characterize. Digital modeling of
pasture biomass and quality by non-destructive methods can provide highly valuable support for
decision-making. This study aimed to evaluate aerial and on-ground methods to characterize grass
ley fields, estimating plant height, biomass and volume, using digital grass models. Two fields were
sampled, one timothy-dominant and the other ryegrass-dominant. Both sensing systems allowed
estimation of biomass, volume and plant height, which were compared with ground truth, also taking
into consideration basic economical aspects. To obtain ground-truth data for validation, 10 plots of
1 m2 were manually and destructively sampled on each field. The studied systems differed in data
resolution, thus in estimation capability. There was a reasonably good agreement between the UAV-based,
the RGB-D-based estimates and the manual height measurements on both fields. RGB-D-based estimation
correlated well with ground truth of plant height (R
2 > 0.80) for both fields, and with dry biomass
(R
2 = 0.88), only for the timothy field. RGB-D-based estimation of plant volume for ryegrass showed a
high agreement (R
2 = 0.87). The UAV-based system showed a weaker estimation capability for plant
height and dry biomass (R
2
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