Assessment of habitat for disturbance-dependent species using light detection and ranging and multispectral sensors mounted on a UAV

Recently, technological advances in UAV-mounted sensors, such as light detection and ranging (LiDAR) and multispectral sensors, have expanded the applications of unmanned aerial vehicles (UAVs) in ecosystem monitoring. LiDAR is suitable for analyzing the underlying microtopography of wetlands because it can produce a digital terrain model (DTM) with high spatial resolution. If a multispectral sensor that can also capture near-infrared wavelengths is used, it is possible to calculate the normalized difference vegetation index (NDVI), which is related to the amount of vegetation present, and the normalized difference water index (NDWI), which is related to the dryness and wetness of the soil. The purpose of this study was to understand the distribution of a disturbance-dependent species in wetlands using high spatial resolution images acquired with a consideration of phenology, and to evaluate the habitat of this disturbance-dependent species using data acquired by LiDAR and multispectral sensors. The wetland around the Omimaiko Inland Lake in Minamikomatsu, Otsu City, Shiga Prefecture, Japan, was chosen as the site for this study. I chose to examine the distribution of Euphorbia adenochlora as a disturbance-dependent species growing in the wetlands of the study area. Using high spatial resolution images acquired with a consideration of phenology, we were able to determine the distribution of the disturbance-dependent species E. adenochlora. Using the data obtained using LiDAR and multispectral sensors, we were able to evaluate its habitat and deduce its viability at six growth sites. This study aims to introduce a new way of applying UAVs in monitoring disturbance-dependent species in wetlands.

Automated summary

This study utilizes high-resolution images and data from sensors mounted on UAVs to understand the distribution and habitat of disturbance-dependent species in wetlands, presenting a new method for UAV monitoring.