Hi, my name is Terry Sohl, I'm a research
physical scientist.
ForeSce model is something we developed here at EROS
and what we wanted to do was move beyond the dates
for which remote sensing data was available.
Where we wanted to be able to take these USGS
produced land cover databases that are
produced from Landsat project them both
backward and forward in time so groups could look
at how weather and climate are impacted by land use
and visa versa. What's happening currently and
then what could potentially happen out into the future.
When you're using a land cover model, and going out
into the future, you don't know what those conditions
are going to do. So the uncertainties are obviously
a lot higher. And so what we do is we use scenario
frameworks. And so we're not weather forecasters, we're
not trying to predict exactly what's going to happen in
the future. What we do is provide a suite of scenarios
that try to cover that uncertainty.
And so in as area like the great plains we can look
at recent trends, look at what's happened with
agricultural land recently, and extrapolate those
trends out in time, and that would provide one scenario
What we can also do is look at alternative scenarios.
Economic scenarios change. Biofuel use changed and
so those are the type of impacts on regional land
use that are very hard to predict. And so what we
try to do is model multiple scenarios try to
represent that uncertainty.
Several years ago I published a paper that looks at
the impacts of projected land use and projected
climate on bird populations across the US. And that's
something that's been done, from a climate aspect, there's
a lot of different climate models that are out there.
There's not a lot of land use models, especially of the
kind that we produce here at EROS. And so we're
providing a unique product that allows somebody like
a biologist to look at not only how projected
changes in climate might impact bird populations
in the future, but how projected changes in
land use might impact bird populations.
The city of Minneapolis gets most of their drinking
water from the Mississippi river. In the last few years
they've noticed things like cyano toxins and
other other products that are an offshoot of enriched
water from agricultural runoff. And the reason for that is land
use change. North of Minneapolis there's a large
tract of forest land that was bought by the largest potato
growing company in the United States and they
converted a lot of this forest land to potato production.
And so what we're doing for this is we're producing scenarios
of land use change in the upper Mississippi river basin
that allows them to potentially plan for what may happen for
their water treatment needs out into the future.
We've completed land cover projections for many scenarios
for the southern great plains and it's a unique area from an
agricultural perspective. So a good example is the panhandle
of Texas where it's one of the United States major cotton
growing regions, and you need irrigation to support
cotton in that pretty dried landscape. And in recent
years the aquifer has declined to the point where that
level of irrigation availability is just not there. And so
you're starting to see some potential shifts in
agricultural patterns. And there are some unknowns with it.
Our scenario based framework that we use allow us to cope
with those unknowns. So as the irrigated water
availability declines there's some question as to wether
they're going to move to dryland crops like wheat,
or whether a lot of that land is going to revert to a grazing
regime with pasture and cattle production.
And what we can do is provide scenarios for both.
And that allows land planners people looking at biodiversity,
water quality and all these other potential impacts
of land use, to look at what are some of these potential
future scenarios and how we may adapt no matter
how the landscape changes.
The ForeSce model was designed to take advantage
the land use products that are produced by USGS.
And so we can look at the past. We can look at landscapes
that were mapped by Landsat and we can look at landscape
patterns. And so when we model things out into the future,
we are tapping into that Landsat database so that
we're representing landscape patterns that are regionally
realistic based on what's happened in the past.
There really are no other models that can model
broad scale land use across broad regions or even at
a national scale that can map the spacial resolution
of what we're doing using actually land management
and ownership boundaries from the USDA to
represent field by field modeling and thematically.
We can all the land cover classes found in the national
land cover database, and that's what makes our model unique.
From a biodiversity standpoint, from a climate perspective,
from a water quality standpoint, just the wide variety of
applications that we're able to support given that we're
trying to produce things that are consistent with the land
cover databases that USGS are already producing.