Document Type

Conference Paper

Rights

Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence

Disciplines

1.5 EARTH AND RELATED ENVIRONMENTAL SCIENCES, 2.7 ENVIRONMENTAL ENGINEERING

Abstract

High resolution topographic maps 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 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. The objective of this research is to use UAV technology to create topographical and vegetation mapping of coastal dune complexes with particular reference to the Brittas-Buckroney dune complex in Co. Wicklow. As the area of study site was about 60 hectares, it was divided into three sections, North, Centre and South. This paper presents the five steps to achieve the objective, setting ground control points, making an autonomous flight plan, flying the UAV for data collection, data processing and result analysis via ArcGIS. The final result, processed by specific software PIX4D, was a topographical map of the study site in the Irish Transverse Mercator coordinate system, with a resolution of 0.125 m and Root-Mean-Square (RMS) error 0.050 m. In conclusion, UAV technology provides new possibilities for mapping as it maximizes improvement of the data quality while reducing the investment in time and labour.

DOI

http://dx.doi.org/10.3846/enviro.2017.245

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