Brazzaville, Republic of the Congo

With a population of 4.4 million, 64 percent of which lives in urban areas, the Republic of Congo is one of the most urbanized countries in Africa. Efforts to manage, regulate and facilitate productive and inclusive urbanization have been inhibited by lack of effective urban planning, limited investment, and inadequate institutional capacity of key stakeholders at the national and local levels. This has resulted in a gradual deterioration of the living and working environment in the country’s main urban areas, with urban sprawl and land speculation displacing poor urban residents to areas unsuitable for settlement. In addition, Government’s failure to implement proper land use planning and titling procedures has pushed the poorest to settle in flood and erosion-prone areas thus exacerbating not only their vulnerability to climate related hazards, but also contributing to their economic, social and spatial exclusion. The objective of this project is to integrate urban resilience in the design and implementation of an Urban Development and Poor Neighborhood Upgrading project (DURQuaP), and build capacities/develop tools for central and local governments to be better prepared to disaster risks. Issues the project will address. Tools would include a GIS-based disaster risk management system to support basic early warning system for flooding; OpenStreetMap data to enable flood risk exposure mapping and social economic vulnerability mapping; and, associated community participatory mapping tools to enable Local Governments, in very close coordination with communities, to produce a more robust municipal basemaps.

Mapping Progress to Date

This section provides an overview of mapping activities in the selected city geographic extent. The Before/After widget below allows comparing current density and distribution of map features with snapshots from previous years. The time chart of OSM editing activity over time offers insights on how many features have been contributed to the map over a specified period.

Data Quality

While OSM coverage keeps increasing, it's important to also understand quality of the data created. The tools available in this section allow for comparing OSM data with other "reference" datasets. These could be, for example, official datasets from government agencies showing distribution of features with those available OSM. The "Gap Detection" widget provides a visual representation of potential gaps in data, by comparing the latest OSM buildings with built-up areas automatically detected from satellite imagery.

OSM Community Dynamics

Understanding mapping progress and data quality also requires looking at the local OSM community and how mappers have contributed over time. Embedded widgets in this sections allow e.g. exploring the list of top mappers who contributed to features within the city extent, with links to their OSM user profile page. A time chart of number of user contributions over pre-defined time periods (daily, weekly, monthly), also provides a picture of how consistent the mapping activity in the area is.

Date Range

users made contributions