- Author: Missing Maps / British Red Cross
- Requesting organization: Red Cross
- Priority: High
- Imagery: Digital Globe
An escalation of violence in South Sudan since July 2016 has lead to a large population movement into the north of neighboring Uganda. One of the area’s first camps, Bidibidi, was originally anticipated to hold 40,000 persons, however now holds 270,000 people, making it one of the largest refugee camps in the world. Elsewhere, the camps at Palorinya and Rhino are similarly growing, and a new camp at Imvepi is under development.
An estimated rate of between 2,000 and 3,000 displaced persons cross the border into Uganda each day, and based on the expected and actual number of persons housed in the adjacent camps, it is anticipated that the geographic extent and population housed in the Imvepi camp will increase dramatically in the immediate future. As of 10 April Imvepi camp hosts 55,778 people
The British Red Cross have deployed an Emergency Response Unit (ERU) to the area to set up sanitation facilities and hygiene promotion. In a rapidly developing situation such as this, it is vital that accurate and up-to-date mapping information is available to allow the ERU to respond more effectively and efficiently.
The maps that you create in this task will enable sanitation facilities - including latrines, hand washing points and hygiene promotion activities - to be effectively provisioned for the people living there.
Through the MapGive project, the Humanitarian Information Unit (HIU) of the U.S. Department of State is providing the OpenStreetMap community access to updated satellite imagery services to help assist with humanitarian mapping.
Created by PaulKnight - Updated - Priority: low
- Entities to Map
- buildings, road network
- Changeset Comment
- #hotosm-project-2819 #Mvepi #RedCross #Uganda #MSM #MSM20 #MapGive Source=WorldView-3, DigitalGlobe, NextView, 10 April 2017 When saving your work, please leave the default comment but add what you actually mapped, for example "added buildings and a residential road".
[imagery url available only after accepting the license]
Access to this imagery is limited by the NextView license agreement.
You need to review and acknowledge the agreement.
For this task, mappers are being asked to map buildings and the road network across the area of the camp.
The imagery will show buildings as a mixture of ‘formal’ constructions, tents and other structures; the road network will also be a mixture of ‘formal’ tracks (laid out in a grid system), and less paths.
To help you in your mapping, please look at these images. The photos shows examples of what some of the structures and roads may look like.
You will need to map 2 different kind of shelters, please see here.
In the ID editor: label the area as “Building”, then correct for right angles with the “S” key
In JOSM: from the Tags/Memberships window, click “Add” and use the tag “building=yes”; then correct for right angles using the “Q” key
Roads should be identified with respect to their economic and social role, not in terms of their visibility/viability. The best way to approach this is to use the existing road network and its connections to towns and villages.
Inside of the camp please use highway=residential (with the exception of major roads) (in ID : choose "Residential road")
Outside of the camp please use highway=unclassified : or "Minor routes" : for those roads connecting villages and hamlets
You should not have to use :
highway=primary, highway=secondary or highway=tertiary : these are the main roads that connect towns. You shouldn’t need to create them for this project.
highway=track (roads or paths which connect fields only) and “highway=path”(roads too narrow for a 4-wheel drive vehicle to pass)
The most important thing is to maintain consistency in the network. Every road should connect to another of greater importance and not to isolated roads.
This imagery is from DigitalGlobe’s WorldView 3. The imagery has been orthorectified for terrain corrected geographic precision. Additionally, the imagery has been contrast stretched using a custom stretch and processed into a Tiled Map Service (TMS) for performance. The image you are using was taken on 10 April 2017.