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GIScience 2016 Short Paper Proceedings Shape and resolution: quantifying feature morphology change due to coarsening spatial resolution using UAV- based images from vertical transects S. W. Mitchell 1 , T. K. Remmel 2 Department of Geography & Environmental Studies, Carleton University, 1125 Colonel By Drive, Ottawa, Ontario, K1S 5B6 Email: Scott.Mitchell@carleton.ca Department of Geography, York University, 4700 Keele Street, Toronto, Ontario, M3J 1P3 Email: remmelt@yorku.ca Abstract Aside from tone or colour, shape is one of the most readily utilized characteristics to interpret remotely sensed imagery. As spatial resolution is coarsened, the level of observable spatial detail diminishes, thus the shapes of features become less distinct. This study controlled the observation platform, a Tetracam ADC snap multispectral camera mounted on a Phantom 2 quad-copter, to collect images along vertical transects. This design simulates continuously coarsening spatial resolution as the aircraft ascends, while maintaining consistent imaging parameters. Vegetation visible on all scenes was analysed using common shape characterizations. Scaling relationships were assessed between original shape complexity and spatial resolution (a proxy for scale). Initial results show strong scaling relationships at ultra- fine scales but an interesting area of stability which, if repeatable, could have important implications for the use of UAVs in environmental research. 1. Introduction The characterization and comparison of spatial pattern characteristics or landscape morphological elements are sectors of GIScience that intersect with mathematics and landscape ecology, and have been developing for several decades (Gardner et al. 1987; Haines-Young and Chopping 1996; Uuemaa 2009). Numerous studies span the breadth of such inquiries, ranging from studies of land cover change (Linke et al. 2009) to assessing habitat suitability (McAlpine and Eyre 2002). While computing a suite of metrics is facilitated by readily accessible software (Baker and Cai 1992; McGarigal and Marks 1995; Vogt et al. 2007), many redundancies have been identified (Riitters et al. 1995) and limitations explicitly characterized that limit the inference that can be drawn from such metrics (Remmel and Csillag 2003). Scale effects have been tested by manipulating landscape extent and spatial resolution, but these generally rely on resampling or the use of multiple platforms of data (e.g. Saura 2002; Baldwin et al. 2004). This study focuses on the characterization of planar shape, a single aspect of the broader collection of pattern metrics, with respect to scale. Shape provides the ability to characterize and discriminate individual landscape elements (Zhang and Atkinson 2016), rather than summarize landscape-wide patterns. Scaling analysis was applied to data obtained from a consistent platform, such that resampling or sensor substitution did not introduce spurious relationships and uncertainty that make interpretation more complex. By manipulating a single variable (spatial resolution) of a digital image while maintaining all camera, timing, and environmental conditions constant, we explored the effect of spatial resolution on the quantification of patch shape directly. This differs from Saura and Carballal (2004) where

Shape and resolution: quantifying feature morphology change due to coarsening spatial resolution using UAV-based images from vertical transects