Import Nigeria eHealth Africa Residential Areas

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The goal of this import is to incorporate, state by state, the residential areas from the eHealth Africa data for 8 states of North Nigeria: Kebbi, Sokoto, Kano, Katsina, Zamfara, Jigawa, Yobe and Borno. These residential areas are of good quality for OSM standards, and bearing in mind that we have few landuse=residential areas in the OSM database, merging them won't be difficult either.

The majority of these residential areas (some simple polygons and some multipolygons) have the name of the settlement, but we won't get the corresponding node for this import, but rather for another independent import, because merging those nodes with the ones already in the database is not so easy task.


  1. Preparation, discussion - 12th to 15th April 2014
  2. Import - expected to start in 16th of May 2014. Expected to be finished by 17th of May 2014.

Import Data

Data description

The datasets are drawn and generated by eHealth Africa in the course of their mapping activities in northern Nigeria. The organisation has performed data collections in the entire area and remote tracing using aerial imagery. Residential areas were drawn for what in eHealth Africa call build-up areas, towns and cities.

The residential areas datasets are made topologically correct, so that there are not gaps between features or overlaps of features present.

The dataset consists of residential areas for 8 states of the North of Nigeria: Kano, Borno, Yobe, Sokoto, Zamfara, Katsina, Jigawa and Kebbi.

The dataset contains several field attributes, that aren't of interest for this import, so they will be deleted and substituted by the landuse=residential and source=* tags.

You can have a look at the original field attributes and some screenshots in this hackpad, under the section Residential areas (cities.shp and towns.shp).


ODbL Compliance verified: YES
eHealth Africa has given full authorization for their data with the standard authorization document of the HOT. A scan of the document can be found here

Import Type

The import will be split by state, so it will be done in 8 changesets, one for each state. In each changeset, we will assess the data already in the OSM database against the eHealth Africa one, and choose the best shape in each case.

Data Preparation

Data Reduction & Simplification

The data will be reduced only to the keys listed further down.

Tagging Plans

Each residential area of every simple polygon will have the following tags:

OSM tag

As for the relations, tags for the members of the relation will be:

OSM tag

And for the relation proper will be:

OSM tag

Changeset Tags

We will use the following changeset tags.

Data Transformation

Data is in shapefiles. For each state we have two shapefiles, one for cities and another for towns and build-up areas. For each state we'll open those two files in JOSM with the OpenData plugin and we'll merge them in one. We save that layer as an .osm file. We then convert it with an ad-hoc script, that tags the ways and relations (and their members) accordingly. We will then look carefully for possible errors (this will at least include the JOSM validator). After that, we download the data with the OSM Mirror JOSM plugin, and we carefully compare the residential areas we have in the OSM database against the eHealth ones, deleting which we consider of less quality using Bing imagery. Once this is finished, we merge both layers (eHealth and OSM residential areas) and we upload.

Data Merge Workflow

Team Approach

Import will be undertaken by GIS eHealth Africa personnel with the eHealthAfrica_imports OSM user account.


The import will be discussed in the import list, in the Talk-Ng list and in the HOT list.


Already explained.

Reverse plan

In case of any trouble, JOSM reverter will be used.


Already explained.