Review of Effective Vegetation Mapping Using the UAV (Unmanned Aerial Vehicle) Method

Abstract

We tried more precise mapping of vegetation using UAV (unmanned aerial vehicle), as a new method of creating vegetation maps, and we objected to be clearly the efficient mapping of vegetation using the UAV method by comparing vegetation maps created by analysing aerial photographs taken by a UAV and an aircraft (manned flight). The aerial photography using UAV was conducted in the Niida River estuary (the secondary river flowing into Minamisoma City in Fukushima Prefecture, Japan). The photography period was in August 2013. We analysed the aerial photographs using ArcGis 9 (Esri Japan Corporation, Tokyo, Japan). The aerial photographs of the main plant communities (Phragmites australis, Typha domingensis, and Miscanthus sacchariflorus) taken by the UAV could clearly discriminate each plant community at the 1/50 scale. Moreover, it could clearly discriminate the shape of a plant at the 1/10 scale. We compared the vegetation maps by analysing the aerial photos taken by a UAV (2013 shooting) and an aircraft (2011 shooting). As a result, the vegetation map created by the UAV method could clearly discriminate community distributions. We conclude that vegetation surveys using UAV are possible and are capable of a highly precise community division in places where field reconnaissance is difficult. The UAV method is effective and will contribute to the improvement of research methods in the future; this method may reduce research costs associated with a reduction in field survey days and manpower.

Monitoring the colonization of alluvial deposits using multitemporal UAV RGB‐imagery

“…Vegetation cover maps were highly accurate (Table ), indicating the potentialities of UAV RGB images to distinguish vegetation from bare soil. The high accuracy of vegetation maps we produced agrees with the results of Kaneko and Nohara (), who mapped herbaceous communities with the same UAV and camera. This result is also in accordance with those of Corenblit et al.…”

“…, indicating the potentialities of UAV RGB images to distinguish vegetation from bare soil. The high accuracy of vegetation maps we produced agrees with the results ofKaneko and Nohara (2014), who mapped herbaceous communities with the same UAV and camera. This result is also in accordance with those ofCorenblit et al (2010) andHervouet et al (2011) who mapped pioneer vegetation patches with RGB images (aerial and UAV images, respectively).…”

Automated Identification of River Hydromorphological Features Using UAV High Resolution Aerial Imagery

“…This also holds true for vision based classification techniques for both geomorphic and aquatic habitat features [28] and is consistent with the excellent results shown for the characterisation of fluvial environments [29,30]. Recent studies have attempted to improve the results of existing classification methods by using Unmanned Aerial Vehicle (UAV) high resolution RGB aerial imagery.…”

Optimizing the Timing of Unmanned Aerial Vehicle Image Acquisition for Applied Mapping of Woody Vegetation Species Using Feature Selection

“…Yet, in recent years there has been a significant advance in exploiting the capabilities of small unmanned aircraft vehicles (UAV) as part of vegetation research [24][25][26][27]. UAVs, and to some extent also appropriate future satellite missions [28], hold great potential for phenological based mapping, due to flexibility in image acquisition timing and relatively low costs [6,29].…”