Ushahidi and Sahana Eden Open-Source Platforms to Assist Disaster Relief: Geospatial Components and Capabilities

  • Khanh Ngo Duc
  • Tuong-Thuy VuEmail author
  • Yifang Ban
Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC)


In responses to recent large-scale disaster events, huge amount of ground information have been collected in addition to the synoptic views from satellite images. Different platforms have been in place to facilitate the collection and management of such critical location-based information from the crowd. This study investigated the current implementation of geospatial components and their capabilities in open-source platforms, particularly Ushahidi and Sahana Eden. Using the 2011 Christchurch earthquake data and following the four main functions of a geo-info system: Data input, Geospatial analysis, Data management, and Visualization, the performance of geospatial-components were evaluated by a group of users. The result showed that with rich visualization on interactive map both Sahana Eden and Ushahidi enable emergency managers to track the needs of disaster-affected people. While Ushahidi can only filter incidents records by time or category, geospatial data management of Sahana Eden is proven to be more powerful, allowing emergency managers input different geospatial data such as incidents, organizations, human resource, warehouses, hospitals, shelters, assets, and projects and visualizing all of these features on a map. It also helps to simplify the coordination among aids agencies. However, geospatial analysis is the limitation of both platforms. The findings recommended that data input with more variety of formats and more geospatial analysis functions should be added. Further research will expand to more case studies taking into account the requirements of disaster management practitioners and emergency responders.


Disaster Management Disaster Relief Geospatial Data Indian Ocean Tsunami Geospatial Analysis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This research was inspired by the continually significant contributions of Ushahidi and Sahana Eden developers and users in development and deployment these great platforms to assist the disaster relief efforts. The authors appreciate the useful comments by two anonymous reviewers that help to improve the manuscript.


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Department of Urban Planning and EnvironmentRoyal Institute of TechnologyStockholmSweden
  2. 2.School of GeographyUniversity of NottinghamSemenyihMalaysia

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