Comparing mobile and static assessment of biomass in heterogeneous grassland with a multi-sensor system
The present study aimed to test a mobile device equipped with ultrasonic and spectral sensors for the assessment of biomass from diverse pastures and to compare its prediction accuracy to that from static measurements. Prediction of biomass by mobile application of sensors explained >&th...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2016-08-01
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| Series: | Journal of Sensors and Sensor Systems |
| Online Access: | http://www.j-sens-sens-syst.net/5/301/2016/jsss-5-301-2016.pdf |
| Summary: | The present study aimed to test a mobile device equipped
with ultrasonic and spectral sensors for the assessment of biomass from
diverse pastures and to compare its prediction accuracy to that from static
measurements. Prediction of biomass by mobile application of sensors
explained > 63 % of the variation in manually determined
reference plots representing the biomass range of each paddock. Accuracy of
biomass prediction improved with increasing grazing intensity. A slight
overestimation of the true values was observed at low levels of biomass,
whereas an underestimation occurred at high values, irrespective of stocking
rate and years. Prediction accuracy with a mobile application of sensors was
always lower than when sensors were applied statically. Differences between
mobile and static measurements may be caused by position errors, which
accounted for 8.5 cm on average. Beside GPS errors (±1–2 cm
horizontal accuracy and twice that vertically), position inaccuracy
predominantly originated from undirected vehicle movements due to heaps and
hollows on the ground surface. However, the mobile sensor system in
connection with biomass prediction models may provide acceptable prediction
accuracies for practical application, such as mapping. The findings also
show the limits even sophisticated sensor combinations have in the
assessment of biomass of extremely heterogeneous grasslands, which is
typical for very leniently stocked pastures. Thus, further research is
needed to develop improved sensor systems for supporting practical grassland
farming. |
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| ISSN: | 2194-8771 2194-878X |