Location Analysis for Outdoor Recycling Bin Placement

Prepared for:

Final Results

Recycling

• Reduces greenhouse gas emissions• Reduces other pollutants• Reduces the need for landfills• Conserves resources• Produces economic benefit

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

Problem Statement

• Analyze location of existing bins to determine the efficiency of their placement

• Determine optimal locations for unplaced bins

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

Scope

Project duration: January 2014 – May 2014

DataData Source

Campus Base Map – sidewalks, buildings, current outdoor recycling bins

Bob Stafford, Facilities Planning, Design, and Construction Department at Texas State University

Foot Traffic Network Created by Dynamic GeoSolutions

Campus Building Populations Dr. 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 Courts Created by Dynamic GeoSolutions

Data Points for Bus Stops Created by Dynamic GeoSolutions

Software

ArcMap Adobe Illustrator

Network Analyst Extension

Microsoft Office

Microsoft PowerPoint

Methodology for Network Creation

• 23 buildings• 253 routes consisting of multiple

segments

Methodology for Student Population Change Spreadsheet Creation

• 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

Methodology for Analysis

• Weights were dissolved to the segments• Classified foot traffic

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

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

Methodology for Analysis

Foot traffic with the influence of bus stops and food courts

Methodology for Recommendations

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

Results

Discussion

• Major assumption• Even redistribution of student

population between buildings• Does not account for clustering

• Limitations• Data• Time

Conclusions

• Many tasks involved in a GIS project

• Conceptualization is key

• Organization is crucial

• Teamwork is essential