RT Journal Article
SR Electronic
T1 Species and habitat mapping in two dimensions and beyond. Structure-from-Motion Multi-View Stereo photogrammetry for the Conservation Community
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2019.12.16.878033
DO 10.1101/2019.12.16.878033
A1 DeBell, Leon
A1 Duffy, James P.
A1 McKinley, Trevelyan J.
A1 Anderson, Karen
YR 2019
UL http://biorxiv.org/content/early/2019/12/16/2019.12.16.878033.abstract
AB Structure-from-Motion Multi View Stereo (SfM-MVS) photogrammetry is a technique by which volumetric data can be derived from overlapping image sets, using changes of an objects position between images to determine its height and spatial structure. Whilst SfM-MVS has fast become a powerful tool for scientific research, its potential lies beyond the scientific setting, since it can aid in delivering information about habitat structure, biomass, landscape topography, spatial distribution of species in both two and three dimensions, and aid in mapping change over time – both actual and predicted. All of which are of strong relevance for the conservation community, whether from a practical management perspective or understanding and presenting data in new and novel ways from a policy perspective.For practitioners outside of academia wanting to use SfM-MVS there are technical barriers to its application. For example, there are many SfM-MVS software options, but knowing which to choose, or how to get the best results from the software can be difficult for the uninitiated. There are also free and open source software options (FOSS) for processing data through a SfM-MVS pipeline that could benefit those in conservation management and policy, especially in instances where there is limited funding (i.e. commonly within grassroots or community-based projects). This paper signposts the way for the conservation community to understand the choices and options for SfM-MVS implementation, its limitations, current best practice guidelines and introduces applicable FOSS options such as OpenDroneMap, MicMac, CloudCompare, QGIS and speciesgeocodeR. It will also highlight why and where this technology has the potential to become an asset for spatial, temporal and volumetric studies of landscape and conservation ecology.