Tuesday, December 6, 2016

High Resolution Landscape Data Now Available In Chesapeake Bay Watershed, Webinars Set

The U.S. EPA Chesapeake Bay Program Tuesday announced the completion of the Chesapeake Bay High-Resolution Land Cover Project. The dataset will be introduced at a series of three webinars on December 8, 12 and 14.
The project is a critical needed to improve information about the natural and human-made features that exist on the landscape of the Chesapeake Bay watershed, such as buildings, tree canopy and water.
CBP will use this dataset in 2017 as the foundation of its effort to evaluate stakeholder progress toward meeting reduction targets for Bay pollution loads.
“The power of data behind the Chesapeake Bay High-resolution Land Cover Project cannot be overstated. This is a technological snapshot, the likes of which we’ve never had before, of exactly how the land is being used across the entire watershed. Now restoration and conservation decisions can be made that more closely and accurately reflect real-world conditions,” said Nick DiPasquale, Director, Chesapeake Bay Program
The Chesapeake Conservancy, offered an innovative solution to help CBP improve available data about the Bay watershed.
The Chesapeake Conservancy’s Conservation Innovation Center spearheaded a partnership with the University of Vermont and Worldview Solutions, Inc. to complete the Chesapeake Bay High-resolution Land Cover Project, one of the largest high-resolution land cover datasets in the nation.
“This truly is what I call a ‘watershed moment,’ a new era for the conservation movement. Think of this innovative technology as an MRI for the landscape, the results of which are being harnessed, focused and deployed to practice precision conservation, helping to make the struggling Chesapeake Bay healthier. This is a foundation for all organizations, agencies, corporations and individuals to work more effectively together,” Joel Dunn, President and CEO, Chesapeake Conservancy
For ten months, the teams of geospatial analysts worked to produce one-meter by one-meter resolution land cover data for nearly 100,000 square miles comprising the Chesapeake Bay watershed and surrounding counties.  
This new land cover classification has a high degree of accuracy and provides 900 times the amount of information over the existing watershed-wide dataset. Most importantly, this data will be publicly available and updated periodically, at no cost for anyone to use.
The CBP will use the high-resolution land cover data to improve and refine its current suite of modeling tools.
This improved level of detail will enhance the evaluation of progress in support of the 2017 Chesapeake Bay Total Maximum Daily Load Mid-Point Assessment (Bay TMDL).
In addition, the high-resolution land cover data will provide the following specific benefits, as examples:
-- Characterizing, mapping and tracking of wetlands, riparian forest buffers, forests and impervious surfaces;
-- Prioritizing and targeting restoration, conservation, education and public access efforts; and
-- Verifying riparian buffer and urban tree canopy best management practices.
The Chesapeake Conservancy has scheduled 3 webinars to introduce the dataset on these dates—
— December 8 from 1:00 to 2:00 p.m.
— December 12 from 10:00 to 11:00 a.m.
— December 14 from 10:00 to 11:00 a.m.
The presentation will cover where and how to download the data, context and methodology behind the creation of the dataset, and present user cases and sample analyses that demonstrate the capabilities of the dataset.
The presentation will cover the same material each time slot, and will be recorded and hosted on our webpage afterwards.
The presentation will run for approximately 30 minutes with time at the end for questions that can be submitted via a chatbox.
Click Here to R.S.V.P. for this webinar.  Questions should be directed to Margaret Markham by calling 443-321-3610 or send email to: mmarkham@chesapeakeconservancy.org.
For more information on the landscape data, visit the Chesapeake Bay Program’s Chesapeake Bay High-Resolution Land Cover Project webpage.

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