Motivation:
I
am a senior at the University of Vermont studying environmental studies with a
concentration in ecology and conservation.
I am taking the course Ecosystems Ecology and completing an independent
study project as my senior capstone focusing on ecology and environment. The
purpose of this experience, as the final step of my education, is to expose me
to issues and skills required in the environmental field. I am incredibly
passionate about conservation and I am interested in applying my GIS expertise
in a project on this topic.
Project Concept:
My project will look at the
impacts of conservation on carbon storage. I intend to look at changes in land
use and land cover over the last ~30 years.
I propose focusing on the Vermont Land Trust and its influence on Vermont’s
landscape. The following work schedule and results will follow:
1.
Collect land cover and land use change and GIS
data from VLT, VT state agencies and other sources. Download the 30 meter
resolution aboveground carbon map from the Woods Hole Research Center for later
use in the carbon estimates.
2.
I will use the modeling platform Dinamica to
simulate historical land use change across Vermont. I can then run the model
with and without the Vermont Land Trust to see how conversation has influenced
changes in land cover and land use.
3.
I will use a simple carbon model to estimate
carbon storage on VLT areas. I will also estimate carbon storage using the
historical simulation of land use in the absence of the VLT. The difference in
these estimates is the additional carbon stored due to conservation. This can
be modeled for each county and turned into a cartographically pleasing display.
A large percentage of the population will be able to easily interpret the data
in this format.
The
next step is to meet with Vermont Land Trust in order to assess their needs and
receive feedback on this proposal. It will be important to determine the
quality of data and what can be achieved using it. Any questions can be
answered, such as: Is the project interesting? , How can it be changed? , What
land use changes are most important or significant?
BoundaryCounty_CNTYBNDS
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Statewide
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Polygon
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VT State Plane Meters NAD83
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VCGI
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Basic outline of counties
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LandLandcov_LCLU
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Statewide
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Raster
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NAD83
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VCGI
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Breakdown of land use in VT
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ImageryPhotos_NAIP
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Statewide
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Raster
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NAD83
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VCGI
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National Biomass and Carbon Dataset
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Country (state)
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30 m Raster
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Albers conic equal area
NAD83
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Woods Hole
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Use for carbon estimates
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TransRoad_RDSMAJ1
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State
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1500
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NAD83
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VTRANS
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Vermont Roads by class
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To Do
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Get layers downloaded and organized in a folder.
·
Download ArcGIS and Arc Catalog (may need a
code)
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Find papers on land use or some way to justify a
formula.
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Also find and summarize model, provide justification.
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Flowchart of the model and how it may function.
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Identify missing layers and challenging
components.
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Check in with Gillian
Hybrid analytic-heuristic
I think I should probably use 3-4
potential land-use categories: residential, commercial, industrial, other? Some
variables (or primary drivers of land use conversion) to consider are: Distance
to roads, proximity to existing land use (urban, residiential, commercial), proximity
to other protected areas, private vs. public land, proximity to population
centers, finally biophysical components ( soil, slope, vegetation, etc.). “From
1970 to 1980, there was a 35.2% increase in the number of housing units, but
the population grew only by 15%. Likewise, from 1980 to 1990, there was a 21.5%
increase in the number of housing units, while the population increased by only
10% (U.S. Bureau of the Census).” http://www.uvm.edu/rsenr/sal/lumodel/stateof.html
First use WofE method, then put
the results into the GA tool. Set the WofE coefficient to zero for variables
that are spatially dependent (I don’t really understand why). Spatially dependent variables are things like
soils and vegetation. In the example they set crossover to 0.7 and mutation to
0.01. Population size to 100. Generations to 30. Activated convergence stopping
criterion, defined by convergence limit of 0.99 (page 11, https://webmail.uvm.edu/imp/view.php?ajaxui=1&actionID=view_attach&id=2&uid=10933&mailbox=SU5CT1g&uniq=1361378219394)
I believe I should take the output from the GA tool and put it into a two way
similarity test. From there I could even predict how land use may change down
the road. This would utilize an almost identical model. Finally I will have to
calculate the amount of carbon sequestered (above and/or below ground) by VLT.
I am unsure of how to accomplish this last step.
LAND USE
In
Chittenden County the years 1971 to 1990 experienced more growth in Vermont
than from 1950 to 1970 or 1991 to 2010. From 1990 to 2008 the majority of
residential development was on large lots in rural areas. In 1970 there were
just over 20,000 structures in Chittenden County, by 1990 there were over 35,000
and in 2005 there were over 44,000 structures. Roughly a third of the county’s
growth from 1950 until 2005 was in suburban areas. By 2005 24 % of the county’s
structures were in suburban areas. There was an increase in structures in all
sectors of Chittenden County. There was a greater increase of structures in
rural areas than transportation areas. “In 1950, over 55% of structures in
Chittenden County were located in the Metro Planning Area (mostly in Burlington
and Winooski). By 2005, that percentage had fallen to about 35%. In the same
time period, the
percentage of county structures located in the Rural
Planning Area grew from about 18% to almost 29%, and the percentage in the
Suburban Planning Area grew from a little over 7% to almost 24%.”
QUESTIONS
1.
Can the patcher function be set up to capture
the average size of a timber cut in VT? Is this the best way to use the patcher
functor, or what I should be interested in>
2.
How many variables should I use and what are the
most important?
3.
Is the Hybrid-Analytic Heuristic model or
Cellular Automata model a better fit? Is the GA tool necessary?
4.
What parts of the Wood Hole layer do I need?
When I tried to download the file there was a lot of stuff and no good
descriptions or metadata.