Freetown Regeneration Use Case Initiative

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The Freetown City Regeneration Project is a collaborative initiative between OpenStreetMap Sierra Leone, the Humanitarian OpenStreetMap Team (HOT), and the Freetown City Council (FCC) to digitize the city’s Central Business District. By leveraging high-resolution drone imagery and open-source mapping technologies, the project successfully created a comprehensive geospatial database. This resource was designed to bridge critical data gaps in urban planning, revenue generation, and environmental management, providing the city with a reliable foundation for informed decision-making.

The project’s technical execution involved a three-month field operation featuring 25 trained mappers from the council and local communities. This team utilized an advanced, integrated tech stack to document over 4,300 buildings, 1,800 commercial entities, and nearly 200 kilometers of road and drainage networks. Notably, the initiative served as a pilot for integrating mobile mapping tools with task management software, capturing thousands of street-level images to provide a ground-level view of Freetown's infrastructure.

Beyond data collection, the project’s outcomes are already being integrated into municipal services, including disaster management and waste optimization. By documenting essential water points and solid waste sites, the initiative supports the FCC’s broader regeneration strategy and taxation platforms. This successful implementation not only revitalizes the city’s property database but also establishes a scalable methodology for future large-scale mapping efforts across the region.

TRAINING and recruitment

The project adopted an inclusive recruitment strategy, selecting 25 field mappers from the local city council, community organizations, and residents of informal settlements within the target area. Training was delivered in two distinct phases to ensure a comprehensive skill set across the entire team.

The first phase focused on technical staff, providing advanced instruction in geographic information software for digitizing roads and drainage networks using high-resolution drone imagery. This also included the use of 360-degree cameras to capture street-level perspectives for comprehensive infrastructure documentation.

The second phase targeted community mappers, offering hands-on training in mobile data collection tools and field management software. This instruction emphasized the practical aspects of mapping properties, commercial points of interest, and water and sanitation facilities, with a strong focus on effective questionnaire administration and strict data quality protocols.

Data Model Development

To ensure the project directly addressed municipal priorities, a collaborative workshop was held with departmental heads from across the council. This engaging session allowed leaders to define their specific data requirements across various sectors, including property, health, education, business, and infrastructure.

Based on these discussions, customized data models were developed for each sector and strictly validated by the relevant departments before being implemented. Additionally, departmental heads identified and recommended dedicated staff members to participate in the data collection process on a full-time basis, ensuring the project benefited from internal expertise.

Remote and Field data collection

The project utilized a sophisticated tech stack that combined high-resolution drone imagery with 360-degree street-level photography to create a detailed digital basemap. Data collection was managed through a phased approach—moving from a small-scale pilot to full implementation—to allow for iterative learning and tool refinement. By integrating mobile mapping software with task management platforms, the team was able to synchronize field data efficiently, though the pilot phase highlighted the critical importance of strict user permissions to protect existing data footprints.

The initiative successfully documented a massive dataset, including over 11,000 properties, 3,000 commercial points of interest, and nearly 200 kilometers of road and drainage infrastructure. To ensure the integrity of this information, a rigorous quality assurance framework was implemented. This included cross-referencing field submissions with aerial imagery and applying advanced statistical analysis to detect outliers or missing values. The result is a highly accurate, validated geodatabase ready to support urban planning and municipal services.

Summary of data collected and analyzed

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