Open Access Open Access  Restricted Access Subscription Access

Copyright © 2024 ISEIS. All rights reserved

Spatial Data Infrastructures in Africa: A Gap Analysis

Y. Guigoz1,2,*, G. Giuliani1,2, A. Nonguierma3, A. Lehmann2,4, A. Mlisa5 and N. Ray1,2

  1. United Nations Environment Programme, Division of Early Warning and Assessment, Global Resource Information Database-Geneva, International Environment House, 11 chemin des Anémones, Châtelaine CH-1219, Switzerland
  2. University of Geneva, Institute for Environmental Sciences/enviroSPACE, 66 Boulevard Carl-Vogt, Geneva CH-1205, Switzerland
  3. United Nations Economic Commission for Africa, Information, Science & Technology Division, Menelik II Ave., Addis Abeba, Ethiopia
  4. University of Geneva, Forel Institute, Uni Carl-Vogt, Geneva CH-1211, Switzerland
  5. GEO Secretariat, 7 bis avenue de la Paix, Geneva CH-1211, Switzerland

*Corresponding author. Tel.: +41 22 917 83 98; fax: +41 22 917 80 29. E-mail address: (Y. Guigoz).


The need for spatially explicit thematic data is currently increasing in parallel to the development of observing, storing and processing capabilities. This requires an integrated data management structure in which human and institutional aspects play a key role as part of a Spatial Data Infrastructure (SDI). We focus in this study on the African continent to evaluate the status of its SDI implementation. Because assessing SDI at a continental scale in a traditional way (i.e. following methods developed for national assessments) requires financial resources and mechanisms only affordable to developed countries (e.g. European Union), alternative ways have been explored based on fourteen key SDI indicators that were validated by SDI experts in a previous study. Data was collected for each African country through the African leading SDI institution (UN Economic Commission for Africa) and through Internet searches. We found relatively weak scores of the fourteen SDI indicators for African countries compared to the rest of the World, but with notable differences within Africa. We discuss the implication of the lack of information available on the Internet to assess SDI status in Africa. We conclude that it is necessary to improve statistical information in most African countries. This requires an agreed-on geospatial data structure and organization between concerned institutions that is only achievable through a shared global vision on geospatial data governance. To this end, we suggest a few quick wins and several new mechanisms that would enhance the flow of SDI statistical information and improve data management structure in Africa.

Keywords: SDI, Africa, Gap Analysis, monitoring, brokering

Full Text:


Supplementary Files:


  • There are currently no refbacks.