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Rachel Cavin, Manager James Dodds, Assistant Manager Taylor Dorn, GIS Analyst Kyler McNew, GIS Analyst Cartographic Modeling of Sidewalk Location Selection.

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Presentation on theme: "Rachel Cavin, Manager James Dodds, Assistant Manager Taylor Dorn, GIS Analyst Kyler McNew, GIS Analyst Cartographic Modeling of Sidewalk Location Selection."— Presentation transcript:

1 Rachel Cavin, Manager James Dodds, Assistant Manager Taylor Dorn, GIS Analyst Kyler McNew, GIS Analyst Cartographic Modeling of Sidewalk Location Selection for The City of San Marcos, Texas

2  San Marcos, Texas is a diverse and growing community.  The city boasts numerous landmarks, including the river, outlet malls, and university.  Providing adequate access for all members of the community represents a challenge.

3  Residents have expressed desire for improved pedestrian infrastructure.  Currently, no formal system for siting sidewalks exists.  To effectively meet citizen needs, a process for determining potential sidewalk locations is to be developed.

4  Develop a model that hierarchically ranks potential locations for sidewalks based on criteria that are determined to generate pedestrian traffic.  Locate areas that are in need of sidewalks within the San Marcos City Limits.  Ensure this model can be used for future projects.

5 DataSource City Facilities The City of San Marcos Schools Pedestrian CIP Railroads Sidewalk Inventory Streets Trails Parks Texas State University Zoning Projection: Lambert Conformal Conic

6 DataSource San Marcos City LimitsThe City of San Marcos Low Income & Student HousingCensus Bureau Medical & Pharmacy Facilities Google Earth Grocery Stores Retail Centers Public Transit Stops Projection: Lambert Conformal Conic

7 Limits Data may not be current. Data is not survey grade. Google Maps and Earth may not be accurate. Errors may be present.

8 Data Preparation Create necessary data layers for additional traffic generators. Create a layer that shows gaps in the sidewalk inventory by placing center points in the gaps of the present sidewalk inventory.

9 Data Processing Begin model development by editing data to fit our scope. Finalize factor ratings and weights for each criteria. Use buffers to associate gap center points with the factors. Transform associated data layers into raster format for analysis.

10 CriteriaFactorFactor RatingWeight Value City Facilities Activity Center9 1 Public Library9 City Hall7 Municipal Building10 Greenhouse Interpretive Center4 Dunbar Recreation7 Downtown Police Patrol2 Conference Center7 Schools Elementary Schools10 2 Middle Schools10 High Schools8 Private/Other Schools8 Trails/Parks Parks10 1 Greenspace4 Trailheads7 Transit Texas State University-San Marcos Trams8 1 C.A.R.T.S.8 University Texas State University-San Marcos7 1 Medical Hospital10 2 Pharmacy10 Physicians/Other Medical Offices10 Retail Grocery10 1 Retail Centers6 Low Income Low Income Housing8 1 Student Living Areas8 All ratings and weights are tentative.

11 Data Analysis Continue model development, input all factor ratings and weights. Run all the factors through a weighted sum function, this will calculate location scores.  We will also run average factors through a weighted sum function to compare outcome. Locations with the highest scores will have the greatest need for access to pedestrian traffic generators.

12 Model Certainty Check To assess our model’s sensitivity, we will run it multiple times, each using different buffer radius lengths.  Buffers with 50, 100, and 200 meter radius lengths. Adjustments will be made to the model to correct any uncertainty.

13  Quantitative ranking systems are common in sidewalk locating (Pérez 2010, Zipf 2010)  It is difficult to determine how sidewalks should be sited, as access needs are hard to quantify.  The relative importance of factors to be ranked is always subjective, but tailoring the ranking to the local needs is crucial.

14  Result of our project will be a model the City of San Marcos can use to plan potential sidewalk development.  Our model will not be suitable for the actual locating of sidewalks, only as a conceptual guide to scout sites for surveying.

15  At the conclusion of our project, The City of San Marcos will receive the following: Detailed Final Report (two copies) Project Website CD, two copies containing:  All data  Metadata  Proposal, Progress Report, and Final Report  Poster  PowerPoint Presentations  Instructions on how to use the CD (readme file)  A poster will be produced for the Texas State Geography Department.

16  Phase 1: Data Collection February 5 th - February 20 th Reviewing available literature & collecting data  Phase 2: Data Processing February 21 st - March 25 th Data will be converted into proper format Metadata will be checked to ensure accuracy  Phase 3: Data Analysis March 26 th - April 25 th Criteria ranking & weights will be integrated into our model  Phase 4: Data Interpretation April 26 th – May 3 rd Develop visualizations for results Key Dates February 20 th - Proposal Presentation March 25 th - Progress Presentation May 3 rd – Final Product Delivered Key Dates February 20 th - Proposal Presentation March 25 th - Progress Presentation May 3 rd – Final Product Delivered

17  Our project will develop a model to rank sidewalk development locations based on criteria such as schools and medical facilities.  We will produce maps using our model results that will illustrate locations within the San Marcos city limits in need of sidewalks.  Our model concept is based on research done by others, as well as GIS suitability modeling.

18  Our hope is that our project will provide a valuable resource for the City of San Marcos as pedestrian infrastructure developments are planned.  Allocating funds to the areas most in need of development is critical. We will endeavor to create as accurate and sensitive a model as possible.

19 Thank you.


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