Development and evaluation of mire vegetation survey method using UAV equipped with omnidirectional video camera.

Abstract

Mires are regarded as one of the most fragile ecosystems, and active vegetation monitoring is required for their conservation. By using unmanned aerial vehicles (UAVs) equipped with omnidirectional video cameras, it may be possible to obtain information inside vegetation easily through close-up super-wide-angle aerial views of vegetation communities. Although this approach may allow for non-invasive vegetation monitoring in mires, there is little knowledge about the advantages and disadvantages of vegetation surveying using such UAVs. In this study, we set 27 quadrats in the Bekanbeushi mire and conducted surveys using UAV aerial views from an omnidirectional video camera on the community surface, still cameras 2 and 5 m above the community, as well as using conventional field vegetation survey methods. Using these views, we examined species appearances and coverages on a PC monitor and evaluated species detection rates, coverage errors, and statistical vegetation classification via two-way indicator species analysis (TWINSPAN). From this data, we discussed the prospect of vegetation surveying by UAV aerial views. The mean values in species detection rate and coverage error were not clearly different between the omnidirectional movie and the still images. In the omnidirectional movie, the detection rates of small to medium species growing inside the community were higher than those in the still images, which contributed to more accurate vegetation classification in TWINSPAN. In contrast, in the omnidirectional movie, the detection rates of narrow-leaf and low-coverage species decreased owing to the wind generated by the UAV and the narrowing of the cameraʼs field of view upon approaching the community surface. Furthermore, species with plant heights of less than 10 cm were hardly detected, even in the omnidirectional movie. Therefore, to perform vegetation surveys using UAV aerial views, it will be necessary to first further improve the detection rate of small species.