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A dual-method approach toward measuring the built environment - sampling optimization, validity, and efficiency of
Weimin Li1, Patricia L Winter2, Lee-Anne Milburn1
1California State Polytechnic University at Pomona, United States.
Health & Place
|January 1, 2021
Summary
Combining Geographic Information Systems (GIS) with Google Street View Auditing (GSVA) offers a cost-effective way to measure urban environments. This dual-method approach optimizes sampling and enhances efficiency for built environment research.
Area of Science:
- Urban Planning
- Environmental Science
- Geographic Information Systems
Background:
- Geographic Information Systems (GIS) and virtual auditing are established methods for built environment assessment.
- Each method has distinct advantages and limitations.
- Optimizing measurement quality, cost-effectiveness, and efficiency necessitates exploring combined-method strategies.
Purpose of the Study:
- To assess GIS-based sampling optimization for virtual auditing.
- To compare the validity of GIS measures against Google Street View Auditing (GSVA).
- To evaluate the efficiency of a dual GIS and GSVA approach.
Main Methods:
- GIS was used to generate sampling scenarios and assess measurement validity across different sample sizes.
- Human raters conducted Google Street View Auditing (GSVA) to measure environmental attributes.
- The efficiency and validity of individual GIS and GSVA methods were compared to a combined dual-method approach.
Main Results:
- GIS measures provide valuable sampling guidance for GSVA, suggesting optimal sample sizes of 5%-20% in diverse neighborhoods.
- GSVA excels in capturing subjective environmental characteristics, while GIS is validated for objective attributes.
- The combined GIS and GSVA approach demonstrated reduced financial and time costs compared to GSVA alone.
Conclusions:
- A dual-method strategy integrating GIS and GSVA is recommended for comprehensive and efficient objective built environment measurement in urban settings.
- This integrated approach enhances measurement quality and optimizes resource allocation.
- Findings support tailored sampling strategies based on community characteristics and specific environmental features.
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