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Socio-Economic Benefits of Austin’s Tree Canopy. Progress report presented by:. Kyle Fuchshuber (Project Manager) Jerad Laxson (Asst. Project Manager) Megan Thomas (Editor & Researcher) Eric Tijerina (Graphic Designer & Researcher) Zachary Dye (GIS Specialist & Researcher). Purpose.
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Socio-Economic Benefits of Austin’s Tree Canopy Progress report presented by: • Kyle Fuchshuber (Project Manager) • JeradLaxson (Asst. Project Manager) • Megan Thomas (Editor & Researcher) • Eric Tijerina (Graphic Designer & Researcher) • Zachary Dye (GIS Specialist & Researcher)
Purpose • Progress update for following tasks: • Effects of tree cover on property values • Effects of tree cover on pavement costs • Effects of tree cover on crime rates • Scope: • Heavy tree canopy – very limited tree canopy • Adjusted focus areas to fit specific tasks in project
Effect of Tree Canopy on Property Values • Work Completed • Research and data collection complete • Density analysis • Tree canopy • Market price of single family home parcels
Density of single family homes with darker values representing higher market price Density of tree canopies
Effect of Tree Canopy on Property Values • Problems • Focus areas amended to fit task specifically
Effect of Tree Canopy on Property Values • Work Scheduled • Analyze independent variables • Viewshed • Distance from businesses and universities • Distance from natural areas • Acreage of parcels • Apply GWR (Geographically Weighted Regression) model • Analyzes spatial distributions and general trends
Effect of Tree Canopy on Pavement Costs • Work Completed • Exploring what data is obtained • Buffer of major roadways • Variable for pavement cost
Effect of Tree Canopy on Pavement Costs • Problems • Need more data • Pavement material, age, typical traffic conditions • Solution • Other variables will be analyzed: • UV damage based on viewshed analysis • Condition of road based on type • Highway – Heavy damage • Street – Moderate damage • Road – Least damage
Effect of Tree Canopy on Pavement Costs • Work Scheduled • Deciding what data to include • Analysis of data using GWR
Effect of Tree Canopy on Crime • Work Completed • Data collection • Dot map from the APD incidence report • Manually entered income data for neighborhoods • Used a model to calculate percentage of tree cover and number of incidence in each census block • Created a map representing income, percentage of tree cover, and number of crimes in each census block.
Effect of Tree Canopy on Crime • Work in Progress • Locate target neighborhoods • Compare these neighborhoods to one another to determine the effect of tree cover on crime
Effect of Tree Canopy on Crime • Work Scheduled • Create a series of maps of focus areas • Calculate statistic significance of tree cover on crime rates • Construct final report
Conclusion • Tree canopy’s relationship to crime rates has progressed most • Focus will now be given to other two tasks • Progress is on track and going well • Limited future issues
Questions or concerns?