In the Field

Discover how GPSSample is supporting public health around the world

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August 2026 Newsletter

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Use Case Overview

UseCases

Do you want to add your use case? Email us at gpssample23@gmail.com and we can add the use case, description, and any photos you'd like to share.

Use Case Stories

Edgewood Neighborhood Plan, Atlanta, US

In September–October 2025, the Edgewood community in Atlanta partnered with GPSSample to conduct a comprehensive, parcel-level field assessment as part of its 2026 Neighborhood Plan update. Volunteer teams mapped every parcel in the neighborhood, documenting existing zoning classifications, land use patterns, housing types (single-family, duplex, multifamily, mixed-use), vacant properties, and redevelopment activity.

In addition to parcel data, teams conducted real-time field documentation of sidewalk gaps, ADA barriers, curb ramp conditions, lighting deficiencies, speeding hotspots, flooding areas, and other safety hazards - providing firsthand data that directly informed recommendations in the plan.

Because Edgewood had already divided the neighborhood into geographic sections, each technical team member was able to systematically cover their assigned area. The GPSSample platform allowed volunteers to upload geolocated photos, tag issues by category, and generate consistent data across teams - creating a neighborhood-wide technical dataset in just a few weeks.

“The app made it easy to collect consistent, real-time data across multiple teams. We were able to move quickly, see patterns emerge immediately, and turn community observations into actionable planning recommendations.” Stephanie Salyer, Edgewood President

The results directly shaped plan elements including:

Updated future land use recommendations
Sidewalk and ADA priority maps
Greenspace and flood mitigation strategies
Housing typology and missing middle analysis
Safety and traffic calming priorities

Next Up? Edgewood is now moving into the formal review and adoption phase. The draft Neighborhood Plan is being finalized for submission to the City of Atlanta, with anticipated review by the applicable Neighborhood Planning Unit (NPU), the Department of City Planning, and ultimately the Atlanta City Council for adoption by summer 2026. Once adopted, the plan will be incorporated into Atlanta’s Comprehensive Development Plan, giving the community’s data-driven recommendations official policy standing.

The technical mapping approach has also generated regional interest. One neighboring community and two Neighborhood Planning Units have already expressed interest in learning more about Edgewood’s parcel-level mapping and field documentation methods to strengthen their own planning efforts.

Reach out to learn more: Neighborhood Plan Update! | ONE

Feasibility and Acceptability Piloting in Meru County, Kenya

In April 2024, the SMART Initiative and Action Against Hunger piloted the U.S. Centers for Disease Control and Prevention’s GPSSample application. The purpose of this pilot was to examine the feasibility and acceptability of GPSSample to facilitate statistical sampling and household selection during a SMART[1] survey. The pilot was completed in the Northern sub-counties of Meru County, Kenya during an Integrated SMART survey that assessed the prevalence of malnutrition among children (6-59 months) and women of reproductive age (15-49 years).

Survey teams work with local Community Health Promoters to map cluster boundaries and list households during the Meru North SMART Survey.

The SMART survey featured a cross-sectional design with a two-stage sampling approach based on probability proportional to population size. The sampling procedure featured the lowest administrative level as the primary sampling unit, while households represented the basic sampling unit. GPSSample was used to generate the sampling frame and randomly select households for inclusion in the survey. Fifty-five clusters were mapped, and 3779 households were listed using GPSSample. Using the criteria outlined in the study configuration, n=3618/3779 households were eligible for selection. From the 660 households selected for inclusion, n=596 households consented and n=286 children were assessed for malnutrition.

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“First, it’s a game changer, it has enabled the reduction of selection bias because now it’s an app doing it. As colleagues have said, ‘Why aren’t we choosing the households with children?’, if left to humans to choose, we would have conveniently chosen the households that have children…”

– Survey Supervisor

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Overall, focus group discussions revealed that survey staff enjoyed using GPSSample and felt that it had great potential for use in future SMART surveys. The process of mapping and listing all households within a cluster, rather than relying exclusively on a village guide to provide a paper list of households, helped to improve the quality of the collected data and reduce sampling bias. Improvements in data quality are further facilitated by not only removing the responsibility of sampling from the field survey teams but also the proximity warnings that ensure surveys are not launched from households that were not selected. Survey staff felt the application would be well integrated into contexts where community-based partners already keep track of, and map, public health activities. Leveraging existing systems that allow cluster mapping and household listing to be completed before the survey will be key to GPSSample’s use and success in future SMART surveys.