The Chesapeake Bay is the largest estuary in the United States and the
third largest in the world. Over 64,000 square miles, from New York down to
Virginia drain into its tributaries. After a century of decline, a focused
effort over the last four decades has brought this ecosystem back from the
verge of collapse, but we still have a long way to go to a healthy bay. We've
embraced technology as a way to prioritize conservation and restoration
projects, putting the right practices in the right places. Data sets like the
National Land Cover database, have been instrumental in our region's efforts, and
while this data works well for modeling across the entire watershed, there is a
fundamental disconnect between the data that was being used for planning and the
data that we needed to implement specific actions that move us toward our
restoration goals. So we worked with our partners in the Chesapeake Bay Program
over 18 months and in December of 2016, we released a region-wide
ultra-high resolution land cover data set. This data is fundamentally changing
the way that managers think about conservation and restoration. It's
providing us with actionable information and refining the way that we can
evaluate the benefits of individual projects. Our partners are already asking
us when we're going to update this data, but the cost and time of our current
methods are too high for us to do frequent updates. What we needed was a
faster and cheaper way to make new data. ArcGIS Pro is reducing the amount of
time that it takes us to go from raw imagery, to land cover. We're creating a
new, false color image using the NAIP image service which is more than just a
base map and segmenting it. We're training a random trees algorithm on a
subset of our imagery and then we're streamlining our entire classification
workflow into one processing model. We can run this locally and classify just
our study area, or by leveraging image server in the Microsoft Cloud, we
can create a land cover classification for an entire landscape.
In fact we can create a base classification for the entire Chesapeake
Bay Watershed in a little over 150 hours. That's pre processing, segmenting and
classifying over 2 terabytes of the most recent NAIP imagery. If we were to run
this in our offices, it would take us over 2,500 hours, and now that we have
two dates of land cover data, we can begin to dissect the changes that are
happening across the landscape. To better understand how this is impacting our
local streams and rivers. To tell us a little bit more about that, here's Cass.
Thanks Jeff. These processing advances enable us to focus more of our energy on
prioritizing conservation and restoration actions. In the Chesapeake,
we're facing a 2025 deadline to meet our restoration goals. Meanwhile, our
watershed adds 100,000 new residents each year, increasing pressure on our
landscape. Decision-makers need scalable tools to help them balance this growth,
with our environment. To see how this translates across a single County let's
take a look at Albemarle, outside of Charlottesville Virginia. In this county
managers could spend all of their time just assessing these 53,000 parcels and
establishing priorities. This is an overwhelming expensive task and we know
it's likely that only a small percentage require our immediate attention. We can
now find these areas with an on-the-fly process in ArcGIS Pro, that compares two
years of land cover data and show where we have lost tree canopy such as what's
popping out here in orange. This layer is integrated into a countywide analysis to
show a manager where water quality monitoring or restoration could be most
beneficial, here highlighted in yellow. This workflow is easily adapted to allow
managers to see where buildings and roads have been constructed. Once we know
our priorities, we can create customized action maps for our local partners, like
this one for a tributary along the Rivanna River.
These developments seem minor when considered in isolation, but there are
206 counties in the Chesapeake Bay watershed. Most are experiencing growth
and cumulatively the impact on water quality is significant. Our Bay cleanup
deadline 2025 is right around the corner. Together, image server and the processing
capacity of the Cloud are enabling us to spend less time making the data that we
need to meet our goals and more time on conservation. Having this capacity at our
fingertips is incredibly exciting, not just in the Chesapeake but across the
country and potentially across the world. Thank you.