Preharvest Monitoring of Biomass Production - Engineering and Science of Biomass Feedstock Production and Provision - page 78

Fig. 4.16 Large-scale biomass yield prediction potential with growth pattern recognition

4.9.3 Conclusion

An automatic UAV-based remote sensing system and data collection system with
fl yover waypoint planning function for bioenergy crop growth condition monitor-
ing was established. The image geo-referencing method associated with the
integrated navigation system has been successfully demonstrated in this research.
The resulting navigation system, using low cost inertial sensors, magnetometer,
GPS, and a single board computer, has been fi eld-tested in both ground-based and
UAV platforms. This UAV-based remote sensing system was proved to be suffi cient
for many of the intended biomass preharvest monitoring and precision biomass
production application.

4.10 S ummary

Remote sensing-based preharvest crop monitoring is important to predict yield,
assess stress, understand growth patterns, and achieve SSCM. Biomass preharvest
monitoring is suitable for data acquisition of either high plants and short plants or
different plants in all growing seasons. This is an important part of engineering
solution of BFP and can provide an essential data to the tasks of harvesting,
transporting, storage, and conversion through the established high-throughput
phenotyping sensing and mapping system by the use of near-real-time remote sens-
ing. However, traditional remote sensing technologies such as satellite imaginary
and airborne imaginary have several critical drawbacks for biomass yield