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

Wednesday Sep 28   05:00 PM to 07:00 PM (2 hours)
scaling relationshipsfeature morphologyunmanned aerial vehiclesultra-fine resolution imagery
Aside from tone or colour, shape is one of the most readily utilized characteristics to interpret remotely sensed imagery. As the 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. Common features visible on all scenes were subjected to a suite of common shape characterizations and decompositions. Changes in spatial resolution between images were computed to develop scaling relationships 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.
Carleton University
Associate Professor

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