Degraded Minnesota Forestland and Carbon Offset Project
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Transcript Degraded Minnesota Forestland and Carbon Offset Project
USING GIS TO TARGET DEGRADED
FORESTLAND FOR UST CARBON
OFFSET PROJECTS
Renee Huset
University of Saint Thomas
Presentation Outline
Background
Research Question
Study Area
Methodology
Preliminary Findings
Further Analysis
Sources
Acknowledgements
BACKGROUND
Why worry about Carbon?
Intergovernmental Panel on Climate Change (IPCC) 99% sure
humans are responsible for global climate change
Source: http://www.daviesand.com/Choices/Precautionary_Planning/New_Data/
Global Concentrations of CO2
Basics of Carbon Offsetting
Carbon Offsetting
Make a mess, Clean it up
Offset Carbon we add by subtracting it
elsewhere
Going Carbon Neutral
Carbon Offset Projects:
Energy
Efficiency
Fund Renewable Energies
Store Carbon: Afforestation, Reforestation, Peatland
restoration
Green Intentions…
How Coldplay's
green hopes
died in the arid
soil of India
29/04/2006
Why UST?
Presidents’ Climate Commitment
Must
include “…actions to make climate neutrality and
sustainability a part of the curriculum and other
educational experience for all students”
UST’s Impact
UST’s Carbon footprint:
72,273
metric tonnes
If UST is going Carbon neutral, why not go neutral here in
the state?
“Hands-on” Carbon neutral
Co-benefits: Larger Islands of habitat for wildlife, better water
quality
Lab for students
Tangible symbol of commitment
Project Goal
Target degraded forestland next to Carbon-dense
areas
Buy and restore enough of this land to offset UST’s
Carbon emissions
RESEARCH QUESTION
Research Questions
Where is the greatest concentration of
aboveground biomass in Minnesota?
Target potentially suitable private lands
How much land required to take UST Carbon
neutral?
Dependent
on tree types and corresponding Carbon
sequestration rates
STUDY AREA
Imperviousness
Unpaved land only
State Protection Levels
Level of Protection
GAP Data from MN DNR
Land ownership
Lakes and Rivers
Includes wetlands
GAP Stewardship
Data
Study Area Detail
Potentially suitable
land
Unpaved
Unprotected
No Lakes or
Rivers
Study Area Model
METHODOLOGY
Processes
Polygon to Raster
Raster Calculator
Neighborhood Statistics
Polygon to Raster Conversion
Changed polygon datasets to raster data sets for
further processing
Example: Converted vector data with private lands
to combine it with imperviousness for a final study
area
Raster Calculator
Add and multiply data within and between data
sets
Example: Raster calculator used to find exact
Carbon figures from total biomass:
[(Digital
900
Number/10)*900)/2] = Carbon in kg/m2
= 30 m. grid cell*30 m. grid cell
Divided by two (2) because Carbon is roughly half of total
aboveground biomass
Neighborhood Statistics
Creates new grid with SUM of Carbon in
surrounding area
More gradual increases in concentrations with
larger analysis windows
The
larger the window, the more generalized the data
13x13 Window:
30
meter grid cell resolution
169 grid cells
152,100 meters2
PRELIMINARY FINDINGS
Findings
Two parts:
Densest
Carbon/ Deepest forests
Southern
Offsetting
Potential
Itasca County
UST’s Carbon footprint
locations:
Northeastern Washington County
Southeastern Chisago County
Deepest Forest
Southern Itasca County
Itasca County
13x13 Window
1,397 tons Carbon
= Window SUM
Window Size:
152,100 m² =
0.1521 km²
Landscape-scale
Carbon trends
Itasca County Neutral
UST generates 72,273 tons of Carbon per year
Restoring 7.84 km2 of degraded, high
quality forestland would eventually offset 1
year of UST Carbon emissions
UST Carbon Neutral
Southeastern Chisago County
Northeastern Washington County
Washington County
Northern Washington County
1,086 tons Carbon =
Window SUM
Washington County: Google Earth
Chisago County
Chisago County
1,242 tons Carbon =
Window SUM
Chisago County: Google Earth
Possible Locations
Near State Forests
Large concentrations of Carbon in proximity to
existing state forests
Extend state forest habitats
Analysis:
5
kilometers around state forests
Southern Itasca County
FURTHER ANALYSIS
Spatial Filter
Displays high variability of Carbon levels
High and low edges of Carbon sinks
Why use it?
Shows
high Carbon concentrations next to very low
concentrations
Clear-cuts
Where
More
Carbon will likely return in high numbers
accurately pinpoint locations optimal for
rehabilitation
Washington County
Carbon variability
relative to edges
Red:
Less Carbon
Blue: More Carbon
Standard Deviation
Much like Spatial Filter
Not high Carbon levels, but differences in Carbon
levels
Relative
variation
Example: Used oftentimes for steepness; not
elevation, but relative elevation differences
Final Output
Locate areas on edges of Carbon sinks that can be
rehabilitated to offset UST’s Carbon footprint
Possibly
near State Forests or State Parks
Dependent upon further analysis of land values and
tree types
DATA SOURCES AND
REFERENCES
Data Sources
Cities: Municipal Boundaries, Minnesota Department of Transportation
(Mn/DOT), 01/01/2001, http://rocky.dot.state.mn.us/BaseMap .
City Streets: City Streets, Minnesota Department of Transportation, Survey
and Mapping, 01/01/2001 , http://deli.dnr.state.mn.us/ .
County Boundary: Minnesota County Boundaries, Minnesota DNR Minerals Division/Section of Wildlife, http://deli.dnr.state.mn.us/.
GAP_Stewardship: GAP Stewardship 2008 - All Ownership Types,
Minnesota DNR - Division of Fish & Wildlife - Wildlife Unit, 1976 to 2007,
http://deli.dnr.state.mn.us/.
Imperviousness: National Land Cover Database Zone 41 Imperviousness
Layer, U.S. Geological Survey, 2003, <http://www.mrlc.gov>.
Land Cover: National Land Cover Database Zone 41 Land Cover Layer,
U.S. Geological Survey, 2003, <http://www.mrlc.gov>.
Data Sources (continued)
Major Roads: Major Roads, Minnesota Department of Transportation,
Survey and Mapping, 01/01/2001 , http://deli.dnr.state.mn.us/ .
Populated Places: Populated Places, DNR-MIS,
http://deli.dnr.state.mn.us/.
State Forests: State Forest Boundaries, DNR Forestry - Forest Resource
Assessment, 2005, http://deli.dnr.state.mn.us/ .
State Outline: Minnesota State Boundary, Minnesota DNR - MIS Bureau,
2007. http://deli.dnr.state.mn.us/ .
The National Biomass and Carbon Dataset for the year 2000 (NBCD
2000): Kellndorfer, J., Walker, W., Kirsch, K., Fiske, G., Bishop, J., LaPoint,
L., Hoppus, M., and Westfall, J. 2007-2009. The National Biomass and
Carbon Dataset 2000 (NBCD 2000). The Woods Hole Research Center,
Falmouth, MA.
References
Davies & Company, Forest Management Resources, “Climate
Change: New Antarctic Ice Core Data,” May 30, 2000,
http://www.daviesand.com/Choices/Precautionary_Planning/
New_Data/.
Google Earth Images
Lennon, Megan J. and Edward A. Nater. “Biophysical Aspects
of Terrestrial Carbon Sequestration in Minnesota.” University
of Minnesota, Minnesota Terrestrial Carbon Sequestration
Project. 2006. http://wrc.umn.edu/outreach/carbon/.
ACKNOWLEDGEMENTS
Many Thanks
Dr. Paul Lorah, Faculty Research mentor
Mr. Bob Douglas, UST Sustainability Committee