Full name: Detection and monitoring of invasive species using unmanned aircraft
The project will establish new methodology for early detection and monitoring of selected invasive species using remote sensing (RS) methods. Application of unmanned aircraft (UAV) will be tested for detection of model species: giant hogweed (Heracleum mantegazzianum), knotweed (Fallopia japonica; F. sachalinensis; and F. bohemica), tree of heaven (Ailanthus altissima), and black locust (Robinia pseudoacacia). All selected species belong to the hundred most aggressive invaders according to the European database of invasive species DAISIE. They pose significant risk for our society because they threaten health (giant hogweed, tree of heaven) as well as landscape, ecosystems and biodiversity (all selected species).
The project results will include methodology for invasive species mapping using RS approach, and UAV optimized for flexible data acquisition. Methodology is verified in several areas of interest, and resulting maps of invasion status will be used by land management authorities to support expert decisions in landscape and nature protection. Developed methodology will be applicable in both monitoring of existing invasions and early detection of invasion onset, i.e. in a phase when eradication measures are significantly more effective and less expensive compared to later stages of invasion. Monitoring must be effective in view of both cost and detection precision. Resulting combination of UAV and processing methods will serve as a base of a new service bringing the monitoring results to customers in fast and effective manner.
- GISAT Ltd. – Tomáš Bartaloš
- Brno University of Technology – Petr Dvořák
Principal investigator: Jana Müllerová
Members from LabGIS: Josef Brůna, Matěj Man, Zdeňka Konopová
Main project web: http://www.invaznirostliny.cz/
Contact: Jana Müllerová