by clicking on the page. A slider will appear, allowing you to adjust your zoom level. Return to the original size by clicking on the page again.
the page around when zoomed in by dragging it.
the zoom using the slider on the top right.
by clicking on the zoomed-in page.
by entering text in the search field and click on "In This Issue" or "All Issues" to search the current issue or the archive of back issues respectively.
by clicking on thumbnails to select pages, and then press the print button.
this publication and page.
displays a table of sections with thumbnails and descriptions.
displays thumbnails of every page in the issue. Click on a page to jump.
allows you to browse through every available issue.
GCN : January and February 2017
case study ANALYTICS BY SUZETTE LOHMEYER In Norfolk, Va., researchers are using drone video from YouTube, a mobile app and GIS software to analyze regional flooding Crowdsourced mapping helps track and predict floods The latest tool in flood predic- tion for low-lying coastal ar- eas in Hampton Roads, Va., is crowdsourced drone footage posted on YouTube. Although regulations and no-fly zones in the Norfolk area (home of Naval Station Norfolk) should prevent drones from be- ing flown, Derek Loftis and his team at the Virginia Institute of Marine Science realized that the regulations don’t seem to stop drone hobbyists. “After Hurricane Matthew hit, people were out there recording with their drones,” Loftis said. “Some of them even attached phones to produce live-stream- ing video.” Loftis realized he could use those videos as a cost-free way to check the accuracy of his pri- mary flood-prediction model, StormSense. The tool uses street-level hydrody- namic modeling to determine types of flooding and the areas at highest risk. It relies on ultrasonic sensors that cost about $5,000 each. Loftis said many towns can’t afford to put the sensors in every spot where there might be flooding. And even though he just received a $75,000 grant from the National Institute of Standards and Technology to buy more sensors, he still can’t cover ev- ery area he wants. But with the videos from the drones, Loftis said he can see “the maximum line of flooding, and we can check if it is the same as we predicted. We can figure out how off we are. Are we 20 feet or are we 5 feet off?” Using drone videos posted on You- Tube sounds less than scientific, and Loftis said, “That’s true. But if you can get hold of the raw footage, you can stitch it into usable data using Esri’s Drone2Map tool, [which] analyzes drone images and converts them into 2-D and 3-D maps.” Using Esri’s tools is a strate- gic part of Loftis’ long-term plan to make his flood-prediction methodology usable anywhere by anyone. “A lot of cities have contracts or site licenses for the Esri GIS program and are filled with people certified to use it,” he added. He is also tracking floods with the Sea Level Rise app, which, like the drone footage, crowd- sources knowledge. Created by the nonprofit Wetlands Watch, the app allows local residents to map flooding during and after an event. “I watched all the spontaneous social networking spring up during Hurricane Sandy,” said Skip Stiles, Wetlands Watch’s executive direc- tor. “I thought, ‘Well, wait a minute, could you use social networking and “Do you know how many cars we lose due to flooding? If an insurance company paid the cost of just one SUV, we could sustain the Sea Level Rise project for a year.” – SKIP STILES, WETLANDS WATCH APIMAGES 26 GCN JANUARY/FEBRUARY 2017 • GCN.COM 0217gcn_026-027.indd 26 1/31/17 1:45 PM
October and November 2016