15Structure-from-Motion Multi View Stereo (SfM-MVS) photogrammetry is a technique 16 by which volumetric data can be derived from overlapping image sets, using changes of an 17 objects position between images to determine its height and spatial structure. Whilst SfM-MVS 18 has fast become a powerful tool for scientific research, its potential lies beyond the scientific 19 setting, since it can aid in delivering information about habitat structure, biomass, landscape 20 topography, spatial distribution of species in both two and three dimensions, and aid in 21 mapping change over time -both actual and predicted. All of which are of strong relevance for 22 the conservation community, whether from a practical management perspective or 23 understanding and presenting data in new and novel ways from a policy perspective. 24 For practitioners outside of academia wanting to use SfM-MVS there are technical 25 barriers to its application. For example, there are many SfM-MVS software options, but 26 knowing which to choose, or how to get the best results from the software can be difficult for 27 the uninitiated. There are also free and open source software options (FOSS) for processing 28 data through a SfM-MVS pipeline that could benefit those in conservation management and 29 policy, especially in instances where there is limited funding (i.e. commonly within grassroots 30 or community-based projects). This paper signposts the way for the conservation community 31 to understand the choices and options for SfM-MVS implementation, its limitations, current 32 best practice guidelines and introduces applicable FOSS options such as OpenDroneMap, 33MicMac, CloudCompare, QGIS and speciesgeocodeR. It will also highlight why and where 34 this technology has the potential to become an asset for spatial, temporal and volumetric studies 35 of landscape and conservation ecology. 36 37 38 39 Relatively new technologies, such as drones (1,2), advances in computational power 40 (3,4), improvements in digital cameras (5), along with classic remote sensing platforms such 41 as kite aerial photography (KAP) and balloons (6,7), have all combined to help create a new 42 opportunity in remote sensing research utilising SfM-MVS photogrammetry. It is these 43 convergent developments that now position SfM-MVS as a cost-effective and democratic tool 44 for conservation research.45SfM-MVS approaches use parallax (i.e. minor displacements in similar images) in 46 conjunction with computer vision techniques, in order to derive 3D structures from 2D data moving object). Data such as overlapping digital photographs and GPS/GNSS (Global 49 Positioning System/Global Navigation Satellite System) information are stitched together, 50 adding distance (X and Y) and height (Z) values to pixels (points) in the combined data, 51 producing a "point cloud" (Figure 1). From this, SfM-MVS software is able to output two 52 dimensional orthographic images containing detailed geographical location information, 53 alongside 2.5 dimensional reconstruct...