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Slide 2 USING GIS TO TARGET DEGRADED FORESTLAND FOR UST CARBON OFFSET PROJECTS Renee Huset University of Saint Thomas Slide 3 Presentation Outline Background Research Question Study Area Methodology Preliminary Findings Further Analysis Sources Acknowledgements Slide 4 BACKGROUND Slide 5 Why worry about Carbon? Source: http://www.daviesand.com/Choices/Precautionary_Planning/New_Data/ Intergovernmental Panel on Climate Change (IPCC) 99% sure humans are responsible for global climate change Slide 6 Global Concentrations of CO 2 Slide 7 Basics of Carbon Offsetting Slide 8 Carbon Offsetting Make a mess, Clean it up Offset Carbon we add by subtracting it elsewhere Slide 9 Going Carbon Neutral Carbon Offset Projects: Energy Efficiency Fund Renewable Energies Store Carbon: Afforestation, Reforestation, Peatland restoration Slide 10 Green Intentions 29/04/2006 How Coldplay's green hopes died in the arid soil of India Slide 11 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 Slide 12 USTs Impact USTs 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 Slide 13 Project Goal Target degraded forestland next to Carbon-dense areas Buy and restore enough of this land to offset USTs Carbon emissions Slide 14 RESEARCH QUESTION Slide 15 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 Slide 16 STUDY AREA Slide 17 Imperviousness Unpaved land only Slide 18 State Protection Levels Level of Protection GAP Data from MN DNR Land ownership Slide 19 Includes wetlands GAP Stewardship Data Lakes and Rivers Slide 20 Potentially suitable land Unpaved Unprotected No Lakes or Rivers Study Area Detail Slide 21 Study Area Model Slide 22 METHODOLOGY Slide 23 Processes Polygon to Raster Raster Calculator Neighborhood Statistics Slide 24 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 Slide 25 Raster Calculator Add and multiply data within and between data sets Example: Raster calculator used to find exact Carbon figures from total biomass: [(Digital Number/10)*900)/2] = Carbon in kg/m 2 900 = 30 m. grid cell*30 m. grid cell Divided by two (2) because Carbon is roughly half of total aboveground biomass Slide 26 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 meters 2 Slide 27 PRELIMINARY FINDINGS Slide 28 Findings Two parts: Densest Carbon/ Deepest forests Southern Itasca County Offsetting USTs Carbon footprint Potential locations: Northeastern Washington County Southeastern Chisago County Slide 29 Deepest Forest Southern Itasca County Slide 30 Itasca County Slide 31 13x13 Window 1,397 tons Carbon = Window SUM Window Size: 152,100 m = 0.1521 km Landscape-scale Carbon trends Slide 32 Itasca County Neutral UST generates 72,273 tons of Carbon per year Restoring 7.84 km 2 of degraded, high quality forestland would eventually offset 1 year of UST Carbon emissions Slide 33 Southeastern Chisago County Northeastern Washington County UST Carbon Neutral Slide 34 Washington County Slide 35 Northern Washington County 1,086 tons Carbon = Window SUM Slide 36 Washington County: Google Earth Slide 37 Chisago County Slide 38 1,242 tons Carbon = Window SUM Slide 39 Chisago County: Google Earth Slide 40 Possible Locations Slide 41 Near State Forests Large concentrations of Carbon in proximity to existing state forests Extend state forest habitats Analysis: 5 kilometers around state forests Slide 42 Southern Itasca County Slide 43 FURTHER ANALYSIS Slide 44 Spatial Filter Displays high variability of Carbon levels High and low edges of Carbon sinks Slide 45 Why use it? Shows high Carbon concentrations next to very low concentrations Clear-cuts Where Carbon will likely return in high numbers More accurately pinpoint locations optimal for rehabilitation Slide 46 Washington County Carbon variability relative to edges Red: Less Carbon Blue: More Carbon Slide 47 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 Slide 48 Final Output Locate areas on edges of Carbon sinks that can be rehabilitated to offset USTs Carbon footprint Possibly near State Forests or State Parks Dependent upon further analysis of land values and tree types Slide 49 DATA SOURCES AND REFERENCES Slide 50 Data Sources Cities: Municipal Boundaries, Minnesota Department of Transportation (Mn/DOT), 01/01/2001, http://rocky.dot.state.mn.us/BaseMap.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/.http://deli.dnr.state.mn.us/ County Boundary: Minnesota County Boundaries, Minnesota DNR - Minerals Division/Section of Wildlife, http://deli.dnr.state.mn.us/.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/. http://deli.dnr.state.mn.us/ Imperviousness: National Land Cover Database Zone 41 Imperviousness Layer, U.S. Geological Survey, 2003,. Land Cover: National Land Cover Database Zone 41 Land Cover Layer, U.S. Geological Survey, 2003,. Slide 51 Data Sources (continued) Major Roads: Major Roads, Minnesota Department of Transportation, Survey and Mapping, 01/01/2001, http://deli.dnr.state.mn.us/.http://deli.dnr.state.mn.us/ Populated Places: Populated Places, DNR-MIS, http://deli.dnr.state.mn.us/. http://deli.dnr.state.mn.us/ State Forests: State Forest Boundaries, DNR Forestry - Forest Resource Assessment, 2005, http://deli.dnr.state.mn.us/.http://deli.dnr.state.mn.us/ State Outline: Minnesota State Boundary, Minnesota DNR - MIS Bureau, 2007. http://deli.dnr.state.mn.us/. 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. Slide 52 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/. 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/.http://wrc.umn.edu/outreach/carbon/ Slide 53 ACKNOWLEDGEMENTS Slide 54 Many Thanks Dr. Paul Lorah, Faculty Research mentor Mr. Bob Douglas, UST Sustainability Committee