integration of fire location, area burned, vegetation type, and fuel loads enables a near-real-time prediction of fire risk and active fire. Decision-makers use these maps, which are available on the Internet, to target limited resources to areas of greatest need. In 1997 the Miombo Network produced a CD that includes a Web-based interface, GIS software, and geographic data archived in a standard format (Arcinfo export format). This CD was distributed widely and freely in Africa to overcome data access problems.

In the committee’s opinion, the Miombo Network is successful and self-sustaining because it is local need-driven, African-directed, and relevant to the missions of its participating agencies.

Food security and famine in East Africa are related to weather variation, expanding human populations, political instability, and changing patterns of land use and land tenure. The Livestock Early Warning System (LEWS) project, which is funded by USAID and is being implemented by Texas A&M University, demonstrates the application of integrated remotely sensed weather data, point-based biophysical modeling, and geographic data on animal and vegetation distribution to serve decision-makers concerned with the welfare of pastoral communities in East Africa.

Typically, early warning systems (e.g., FEWS [Chapter 6]) provide predictive data on rainfall and vegetation condition, whereas the on-ground monitoring programs of markets, human conditions, and animal herd situations provide a “post-effect” appraisal system. However, many of the problems affecting livestock (e.g., weight loss, loss of condition) occur before the response is visible, irrespective of personal experience. This problem necessitates an early warning system that works at the local level (LEWS, 2001).

In response to this challenge LEWS applies technologies capable of (1) predicting the current nutritional status of free-ranging animals, (2) assessing the impact of weather on forage supply and crop production, and (3) linking these data with local, household-level data. Currently, there are six operational monitoring zones in East Africa (southern Ethiopia, northern Kenya, southern Kenya, central and southwestern Uganda, northern Tanzania, and central Tanzania), with two other zones under development in northeastern Ethiopia and northeastern Uganda. Each zone is comprised of 30 LEWS monitoring points. A network of households in each zone provides monthly fecal samples from cattle, sheep, and goats. Nutritional well-being of free-ranging livestock is then assessed in laboratories through fecal profiling using a technology called near-infrared spectroscopy. The fecal profiles are geographically referenced and integrated into the GIS, along with livestock population surveys, continuous 10-day weather data sets, and vegetation data (NDVI [Chapter 6]) from the FEWS program. This combination of data sources provides a foundation dataset for a linked series of predictive models involving

• a grazing land production model;

• a livestock nutritional balance analysis model;

• a mixed farming crop model; and

• a modified El Niño/Southern Oscillation model calibrated for East Africa.

Every 10 days a small data file containing the output of the predictive models is packaged for broadcasting to teams equipped with World Space Satellite radios (Chapter 4) linked to laptop computers. This process is managed by the Association for Strengthening Agricultural Research in Eastern and Central Africa’s (ASARECA) Crisis Mitigation Office in Nairobi and distributed on the African Learning Channel with help from the Arid Lands Information Network.

Over the past two years LEWS has cultivated partnerships with the Intergovernmental Authority on Development Drought Monitoring Center and the Regional Center for Mapping of Resources for Development (RCMRD [Chapters 3 and 8]), both in Nairobi. Currently LEWS is in the process of improving computer server and analytical capacity at these organizations and providing training in the use of Arcview GIS software. Texas A&M University’s Center for Natural Resource Information Technology provides staffing and server capacity to support the system.

A final component of the LEWS activity is community outreach to pastoralists. LEWS is testing early warning communication techniques in pastoral villages, with the aim of more effectively influencing decision-making at the local level.

Front Matter (R1-R14)

Executive Summary (1-10)

1 Introduction (11-17)

2 Agenda 21 Implementation: Progress, Challenges, and the Role of Geographic Information (18-28)

3 Geographic Information Activities in Africa (29-36)

4 Facilitating the Use of Geographic Data: Spatial Data and Telecommunications Infrastructures (37-51)

5 Geographic Data for Sustainable Development I: Framework Data (52-78)

6 Geographic Data for Sustainable Development II: Other Thematic Data (79-103)

7 GIS-Based Decision Support Systems in Africa (104-113)

8 Building Capacity to Apply Geographic Information to Sustainable Development in Africa (114-127)

9 Lessons Learned and Recommendations (128-136)

Appendix A: Biographical Sketches of Committee Members (137-141)

Appendix B: Oral and Written Contributors (142-145)

Appendix C: FGDC Statement (146-147)

Appendix D: Acronyms (148-152)

Appendix E: Glossary (153-155)