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Streamline: A GIS Toolkit for River Ecological Evaluation That Uses Drone Data Products

Authors: Alexandra Evans*, University of New Hampshire, Scott Greenwood, University of New Hampshire, Kevin Gardner, University of New Hampshire
Topics: Environmental Science, Geographic Information Science and Systems, Drones
Keywords: sUAS, UAV, toolbox, GIS, drones, restoration, river restoration, ecology, aquatic ecosystems, evaluation, monitoring, streams, rivers, remote sensing, method development, tools, assessment, riparian vegetation, geomorphology, fluvial, management, SfM, structure-from-motion, DSM, topography, digital surface model, orthomosaic, image analysis, mapping, classification
Session Type: Paper
Presentation File: No File Uploaded


Many stream restoration projects’ success is not evaluated (Bernhardt et al. 2005; Roni & Beechie 2013; Nilsson et al. 2016), despite having conventional ecological assessment methods available. Stream restoration professionals need ecological assessment approaches that are affordable, repeatable, objective, and efficient to develop science-based restoration techniques and better understand how to improve the ecological health of our waterways. This work develops stream ecological assessment approaches using small unmanned aerial systems and structure-from-motion photogrammetry to increase our understanding of restoration impacts and improve the stream professional’s toolkit. Specifically, this research is creating a suite of models in GIS for analyzing drone orthomosaics and digital surface models for various stream ecological indicator metrics. The GIS toolbox will use drone data products as input and semi-automatically calculate ecological metrics such as vegetation quantity, vegetation quality, channel condition, habitat complexity, canopy cover, and other metrics analogous to those used in conventional stream ecological assessment protocols. This toolbox will provide stream ecologists, restoration practitioners, and other stream professionals an approach to assessing the ecological condition of their sites in an efficient, repeatable, objective, quantitative, and transparent way.

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