2. Location Analysis for Outdoor Recycling Bin Placement Prepared for: Final Results

3. Recycling Reduces greenhouse gas emissions Reduces other pollutants Reduces the need for landfills Conserves resources Produces economic benefit

4. Recycling and Texas State University Emerging Research University over 35,000 students in 2013 44 outdoor recycling bins on campus 8 purchased that have not been placed

5. Problem Statement Analyze location of existing bins to determine the efficiency of their placement Determine optimal locations for unplaced bins

6. Project Overview Analyzed flow of foot traffic to determine most used paths Determined optimal locations for recycling bins Recommendations also considered bus stops, food courts, and underserved areas

7. Scope Project duration: January 2014 – May 2014

8. Data Source Campus Base Map – sidewalks, buildings, current outdoor recycling bins Bob Stafford, Facilities Planning, Design, and Construction Department at Texas State University Foot Traffic NetworkCreated by Dynamic GeoSolutions Campus Building PopulationsDr. Marc Turner, Office of Institutional Research at Texas State University Outdoor Recycle Containers Hardcopy Map – locations of new bins Mario Garza, Recycling and Waste Management Department at Texas State University GPS Data for New Outdoor Recycling Bins Created by Dynamic GeoSolutions Data Points for Food CourtsCreated by Dynamic GeoSolutions Data Points for Bus StopsCreated by Dynamic GeoSolutions Software ArcMapAdobe Illustrator Network Analyst ExtensionMicrosoft Office Microsoft PowerPoint

9. Methodology for Network Creation 23 buildings 253 routes consisting of multiple segments

10. Methodology for Student Population Change Spreadsheet Creation

11. Weights represent the number of students using each route Calculations resulted in 4 23x23 matrices of route weights The matrices were summed to create weights for the entire day

12. Methodology for Analysis Weights were dissolved to the segments Classified foot traffic

13. Methodology for Analysis Bus stop buffers equal to the average distance between bus stops and nearest buildings Weight of buffers represents additional foot traffic from bus stops

14. Methodology for Analysis Food court buffers equal to the average distance food courts and nearest buildings Weight of buffers represents additional foot traffic from food courts

15. Methodology for Analysis Foot traffic with the influence of bus stops and food courts

16. Methodology for Recommendations On average people will walk 12 m (39.37 ft) to dispose of refuse in a public place.

17. Results

18. Discussion Major assumption Even redistribution of student population between buildings Does not account for clustering Limitations Data Time

19. Conclusions Many tasks involved in a GIS project Conceptualization is key Organization is crucial Teamwork is essential