Estimating standing biomass of exotic macrophytes using sUAS

摘要

With the advent of sUAS, research scientists and plant managers are capable of obtaining unique, fast, and low-costquantitative data, which delivers many repeatable survey options. Benefits of autonomous sUAS platforms includeminimal training, reduced human safety concerns, and creation of graphic outputs which may be readily viewed by anystakeholder who was not actively involved in the survey or management activity. Research conducted in the WellingtonRegion, New Zealand was used to evaluate consumer-grade sUAS technologies to map and estimate standing biomass ofManchurian Wild Rice (MWR), an exotic semi-aquatic grass which promotes flooding, and displacement of native floraand fauna. The goal of this research was to improve the speed and resolution of current survey strategies used to assessMWR among a lowland pasture site using unmanned systems and photogrammetry techniques. Image collection and dataprocessing was conducted in a manner to provide a theoretic biomass estimation of remaining MWR following seasonalgrowth and herbicide applications. Post-processing methods and theories discussed attempt to identify and quantifyMWR biomass using supervised imaging analysis, plant height modeling, and biomass collected in situ. The use ofunmanned systems to map, monitor, and manage MWR is encouraged for future applications.