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Down to Earth: Geographical Information for Sustainable Development in Africa (2002)
Board on Earth Sciences and Resources (BESR)

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Down to Earth: Geographic Information for Sustainable Development in Africa
5. A Community-Based Example—Natural Resource Man agement in Namibia

The quality of local involvement in natural resource decision support may be more important than the level of technical sophistication. In Namibia communities are experimenting with the use of paper maps generated from a GIS to manage natural resources at a community level (Figure 7-1). This work demonstrates the creation of long-term self-sustaining applications of geographic information to sustainable development.

The principal applications of geographic data in the Community Based Natural Resource Management (CBNRM) program are for mapping conservancy boundaries, land-use planning, monitoring, and communication.

  • Accurately defined boundaries are a legal requirement for registration in the conservancy. Neighbors must agree upon boundaries. Although these discussions can be contentious, displaying the proposed boundaries in a GIS map has proven to be an effective decision-support tool.

  • Land-use decisions include evaluating competing activities within conservancies such as farming, settlement, mining, tourism, and wildlife management. To aid in this process staff at the central office in Windhoek gather and integrate pertinent geographic data within a GIS and disseminate the resultant paper map products to the conservancies. Through an iterative process of participatory mapping, members of the conservancies converge on solutions.

  • Geographic information assists in annual game counts, monitoring poaching or problem animals, assessing drought risk, and monitoring trends in animal populations. Maps are central in all three stages of the monitoring process: planning, implementing, and reporting.

  • Communication within conservancies and externally to neighbors, partners, donors, and potential investors

FIGURE 7-1 Paper maps used in decision support in Namibia (Source: Jo Tagg, Namibia Nature Foundation).

  • is aided by geographic information. Maps with icons (rather than words or numbers) are effective in over-coming communication challenges. And well-organized land-use plans attract potential investors who use maps of game distribution and land-use zones in their deliberations about the placement of tourist lodges that provide income and jobs for local people.

The program operates on a needs-driven approach, and promotes sharing of data and tools. Sharing has resulted in considerable cost savings, and is promoted by not charging for data; adopting standardized software, data formats, and file directory structure; and developing a metadata database. The needs-driven approach has built credibility with field users, led to a strong feeling of ownership by rural people and field-based support staff, fostered a culture of sensitivity to community needs among technical institutions that are partners in the program, generated trust and a common vision among partners (communities, government, donors), and built a critical mass to enhance sustainability of the program (Jo Tagg and Greg Stuart-Hill, Namibia Nature Foundation, personal communication, 2002).

IMPEDIMENTS TO IMPLEMENTING SPATIAL DECISION-SUPPORT SYSTEMS IN AFRICA

EIS-Africa (2001) concluded from a review of information initiatives in Ghana, Mozambique, Senegal, Uganda, and Zimbabwe that few application-oriented examples demonstrated advanced analysis of geographic information. Information systems were still insignificant in environmental decision-making. The following reasons were cited:

  • the decision-support process has not been planned, and clear objectives, goals, and responsibilities of local agencies have not been set;

  • projects are orientated toward data production and updating rather than usage or application (most organizations do not consider analysis to be part of their mission);

  • there is a focus on technical issues instead of data management in support of the decision-making process;

  • many databases are still under construction—hence many organizations have not had time to consider analysis;

  • poor communication between technical staff and those involved in environmental science;

  • lack of inclusion of universities in the environmental network in several of the countries (reducing the chance for ongoing research projects to be a driving force for analysis and data combination);

  • lack of demand and user awareness; and

  • difficulty measuring the impact of technological advances on the decision-making process.

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