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EH

Emily Heaston

US Geological Survey
Feature mapping mobile data collection - Tools for tracking streamflow permanence and road-stream crossings in the Pacif
Mobile data collection has become common place in natural resources monitoring. The increased availability of this technology has not only changed how we record data, but how we collect it. Feature mapping is the collection of data based on GPS location using tools that function across many mobile devices to facilitate crowd sourcing data from many organizations to centralized datasets. This data collection method can be conducted across wide spatial and temporal scales and is easily implemented into ongoing fieldwork efforts. We have established two feature mapping mobile data collection tools for characterizing stream flow permanence and road-stream crossings. Our objective with these feature mapping efforts is to create usable and accessible peer reviewed, publicly available datasets to accompany easy to use assessment surveys.
To effectively assess and track changes in the presence of surface flows in streams, we devolved and easily implemented mobile data collection survey tool. FLOwPER is a survey tool that focusses on rapid collection of stream flow permanence observations. This survey provides data to model the location of the transition from intermittent to perennial headwater streams.
Maintaining and inventorying road-stream crossings is a management priority due to how impactful road stream networks are on stream systems. There are a variety of agency datasets inventorying road-stream crossings that facilitate prioritization of where to spend time and money when maintaining or replacing road-stream crossings. RoadStr is a survey tool that effectively characterizes road-stream crossings. This road-stream crossing assessment tool is being beta-tested this summer and edits will be made to the survey this fall along with the publication of a user guide to ensure that we develop a survey protocol that meets management needs while being transferable across existing road-stream crossing datasets.


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