High resolution spatial data are critical for the development of rigorous and quantitative numerical simulation landscape models. These models can inform targeted land management actions that maintain biodiversity and ecological functions. Mapping topography and functional vegetation communities to obtain accurate distribution and population estimates is an important element of landscape models and is a challenging task which requires a considerable investment in time and resources. A recent development in surveying technologies, Unmanned Aerial Vehicles (UAV’s), also known as drones, has enabled high resolution and high accuracy ground-based data to be gathered quickly and easily on-site. The application of UAV’s represents a new opportunity to survey relatively large areas in significantly less time compared to other on-site surveying methods, including GPS, robotic total stations and terrestrial laser scanners. This paper presents the methodology and outcomes from using UAV’s to create topographical and vegetation mapping of a coastal sand dune complex on the East coast of Ireland. The study site of 60 hectares was divided into three sections for operational reasons, approximately 10 GCP's (Ground Control Points) were created in each section and their coordinates were determined by Network RTK GPS. An autonomous flight plan was created using Sense Fly software with 60% overlap along line and 70% overlap between lines and a flying height of 110 m~120 m. This arrangement kept flight time below 20 min in each sector optimizing the resolution of the imagery given the limitations of battery life. The collected raw data was stored on the UAV and subsequently downloaded for processing. With these setting condition, a total flight time of only 50 min was required to collected topographic data for the 60 hectares study area. The outcomes, processed by PIX4D software, included a point cloud of the study area, in the ITM (Irish Transverse Mercator) grid coordinate system, with a spatial resolution of 0.5 m - 2 m and a Root-Mean-Square (RMS) error on the GCP's of 0.001 m - 0.035 m. In conclusion, UAV technology represents a new possibility for mapping as it can provide high data quality while reducing the investment in time and labour.

DOI: https://doi.org/10.3846/enviro.2017.245