Version classiqueVersion mobile
OpenEdition Books

Le projet majeur africain de la Grande Muraille Verte

Abdoulaye Dia
Robin Duponnois

Partie II. Mise en valeur et suivi de la Grande Muraille Verte

Geographic Information Science: Monitoring, Mapping, Modeling, and Decision Making for the Great Green Wall Initiative

John Harrington, Jr. Ndiaye et Ramatoulaye Ndiaye


Geographic Information Science (GIScience or GISci) — using the synergy of global positioning systems (GPS), remote sensing, spatial analysis and statistics, and geographic information systems (GIS) — provides a powerful set of tools and intellectual approaches to address environmental change. Since the advent of satellite remote sensing of Earth resources in the 1970s, new and innovative ways have been developed to map, measure, monitor, model, and provide decision support for the ongoing changes on our planetary surface. Healthy green vegetation has a unique spectral reflectance response due to absorption in the visible red portion of the spectrum and strong reflectance in the near infrared. Indexes derived from combinations of satellite digital data have been documented to provide good indicators of the amount and geographic coverage of green vegetation. Thus, GIScience methods can be very helpful in spatial reasoning and scientific visualization of the success of agroforestry programs designed to combat desertification. Change detection or monitoring of the success of establishing green vegetation can be accomplished in a geographic information system using multiple dates of satellite imagery or aerial photography. In addition, when information about the state of the vegetation cover is combined with other digital data types, such as soils, access to water, transportation routes, the location of human settlements, and/or natural vegetation cover, then strategic decisions regarding development of the Great Green Wall can be made.

Texte intégral


1Development of the Great Green Wall, a proposed belt of vegetative cover that will link Dakar with Djibouti, is an ongoing participatory effort by the people and the governments of the nations that span the Sahel zone across Africa. Designed to promote biodiversity and sustainable rural landscapes, the Great Green Wall has tremendous potential to engage citizens in an ecosystem restoration project that will promote soil conservation and improvement in ecosystem services.

2Applied geography deals with practical or ‘real world’ applications of the concepts and skills that geographers possess. Applied geographers want to use their knowledge and skill set to help make a difference on our planet, especially with regard to improved natural resource management. Due to the nature of environmental problems, applied geographers tend to act locally and hope that the contribution provides a good example that can lead to better informed decisions. Hopefully, a net result of good applied geography will be an improvement in public policy. Frequently, applied geographers advocate for the use of GIScience technology to assist with decision support for management of environmental and natural resource management issues.

3Geographic Information Science (GIScience or GISci) — the synergy of global positioning systems (GPS), remote sensing, spatial analysis and statistics, and geographic information systems (GIS) — provides a powerful set of tools and intellectual approaches to address environmental change. GIScience allows “us to see and interact with the world in new and stimulating ways” (Goodchild, 2006). Dangermond (2007) has suggested that GIS is a tool to enable sustainable development. Since the advent of satellite remote sensing of Earth resources in the 1970s, we have developed new and innovative ways to map, measure, monitor, and model the ongoing changes on our planetary surface. Scientific visualization can be an important scholarly contribution to decision making. Being able to ‘see’ how human activities are changing the world helps in communicating the nature of the problem and its associated spatial extent. Orbiting satellites, with a sensor package that enables assessment of Earth resources, can provide repetitive views and enable monitoring the rates of human-induced change. The rapid developments within remote sensing and GIS have enabled a new generation of resource managers to better visualize and address environmental change and associated management concerns. In thinking about these new capabilities and thought processes, Goodchild (2006) suggested that it is increasingly desirable “that maps, pictures, and spatial data need to rank with numbers, text, and logic as essential ways in which humans function.”

4We live on a dynamic planet, where natural system functioning has now combined with the impact of over 6.6 billion humans to put considerable stress on ecosystems (Steffen et al., 2004) and the ability of those ecosystems to provide the essential services we need (Daly,1997). Human actions can combine with natural variations in climate to degrade environmental conditions. The prolonged drought in the Sahel of Africa placed considerable stress on local ecosystem services and the ability of resident appropriate needed services at sustainable levels. Two significant impacts of the late 20th Century drought were desertification and the migration of many rural residents into urban areas.

5Those who have examined the pace and scope of global change have also identified critical locations that may be among the first places to transition or ‘tip’ to a new state in response to global climate change, and may make that change very rapidly. These are the so called ‘surprise’ or ‘canary in the coal mine’ regions; the Sahel is one of them (Scheffer et al., 2001, Zeng, 2003, Lenton et al., 2008). In addition, paleo-environmental data indicate that rapid change occurred in the Sahel during the Holocene. The more humid conditions of 6,000 years ago created vegetation cover similar to African savanna in the Sahel-Sahara region (Kröpelin et al., 2008); however, a slight change in Earth-Sun relationships about 5,000 years ago resulted in “an abrupt change in the regional climate … triggering a rapid conversion of the Sahara into its present desert condition” (Steffen et al., 2004).

Spatial Reasoning and Decision Support Systems

6Providing an intellectual context for an event or changing conditions is an important part of knowledge accumulation. That context can include event location, related items within the sphere of influence of the event location, and gradients in phenomena within the relevant region. Location, sphere of influence, gradients, spatial association, geographic analogs, and spatial comparison are all components of spatial reasoning. It is becoming increasingly clear that an ability to do spatial reasoning is as important as reading, writing, and arithmetic (Goodchild, 2006).

7Decision support systems are computer systems that provide decision-makers with an opportunity to assess and solve ill-structured problems. Jensen et al. (2009) identify the additional value of building spatial data into these decision support systems. Advantages of using GIScience for decision support include: “powerful graphic display,” “improved spatial data handling,” and the ability to utilize “specific analytic and modeling capabilities” (Jensen et al., 2009). A committee of the US National Academy of Sciences (NRC, 2002) has discussed the importance of satellite-based Earth observation and the use of geographic information technology for sustainable development in Africa. In addition to discussing the strengths and capabilities of GIScience technology for monitoring change over time, the NRC report recognizes the vital importance integrating social science and natural resource data to inform decision makers.

Examples of the Use of Satellite Data to Monitor Natural Resources in Africa

8Numerous examples of our ability to measure, map, and monitor natural resources in Africa using data from satellite-based sensor systems exist. Tucker et al. (1985) provided a now-classic discussion regarding the use of visible and near infrared satellite imagery to map land cover for the African continent. Later, Tucker et al. (1991) used a decade of satellite data to document the inter-annual changes in the southern boundary of the Sahara, and then related those shifts to changes in high-sun season precipitation amounts. In a special issue of the Journal of Arid Environments that dealt with the greening of the Sahel, Anyamba and Tucker (2005) used over two decades of imagery data for the Sahel to further our understanding of inter-annual variations in vegetative cover in a very dynamic transition zone. They documented that the period 1982-1993 saw below average precipitation and vegetative response (as indicated by NDVI) and that 1994-2003 was a period of vegetative recovery associated with wetter conditions. The authors concluded that “studies of changes on the landscape using high spatial resolution satellite data sets … will provide a detailed spatial quantification and description of the recovery patterns at local scale” (Anyamba and Tucker 2005). Climate variability is an identified driver of variation in the productivity of African agro-pastoral landscapes, and satellite imagery provides a way to document the inter-annual changes; there is concern that on-going global change, including climate change, will negatively impact these integrated social and ecological agro-pastoral systems in Africa (Stige et al., 2006).

Figures 1 and 2

Figures 1 and 2

The village of Galma, Niger in 1975 (left) and 2003 (right).
Source: La transformation silencieuse de l’environnement et des systems de production au Sahel : Impacts des investissements publics et privés dans la gestion des ressources naturelles, Botoni and Reij, 2009.

9GIScience efforts by Gray Tappan and his colleagues to document changes in local and regional vegetation change in the Sahel provide visual evidence of the power of scientific visualization for an area in southern Niger (Figures 1 and 2). They found an increase in tree cover and vegetative density in agricultural zones where local farmers have adjusted their behavior to include agroforestry; tree cover has become five to twenty times more dense than in the 1970s (SIAC 2007). Based on an assessment of nearly four decades of imagery and field work, considerable differences in land cover trends are found at the ecoregion scale within Senegal (Tappan et al., 2004).


10This paper advocates for the use of GIScience (the integration of the use of global positioning, remote sensing, and geographic information system technologies) to provide the needed scientific visualization and spatial knowledge for assessing relative success in establishing the Great Green Wall. The capabilities provided by GIScience are a resource for addressing scientific questions about the status of the Great Green Wall, and will provide an ability to visualize existing conditions and how those conditions have changed over time. Given that the Great Green Wall initiative involves the complexity associated with coupled human and natural systems integration (Liu et al., 2007, Seaquist et al., 2008), GIScience is advantageous because it provides an ability to incorporate real world complexity into decision making.

11Establishment of a multi-national GIScience Center that will serve the entire Great Green Wall effort, from Dakar to Dijibouti, is needed. Dangermond (2007) has noted that GIS enables the kinds of problem solving needed for the transition to sustainability. It is clear that the Great Green Wall effort is aimed toward establishment of a sustainable relationship between local citizens and their biotic resources. An advantage of GIScience technology is that it is a digital resource that grows and improves with time and effort, as more and better data become available. The dynamic nature of a technology system that improves over time and provides scientific visualization capabilities will increase trust among decision makers, especially as spatial data are shared across international boundaries.


Anyamba, A., and C.J. Tucker, 2005. “Analysis of Sahelian vegetation dynamics using NOAA-AVHRR NDVI data from 1981–2003,” J. Arid Environments, 63(3): 596-614.

Botoni, E., and C. Reij, 2009. La transformation silencieuse de l’environnement et des systems de production au Sahel : Impacts des investissements publics et privés dans la gestion des ressources naturelles. Center for International Cooperation, Vrije Universiteit, Amsterdam.

Daly, G., Editor, 1997. Nature’s Services. Island Press, Washington, D.C.

Dangermond, J., 2007. “GIS—The Geographic Approach: A Framework for Understanding, Managing, and Improving Our World,” ArcNews, 29(3):1, 3-6.

Goodchild, M., 2006. “The Fourth R? Rethinking GIS Education,” ArcNews, Fall 2006, available on-line at:

Jensen, J., et al., 2009. “Development of a Remote Sensing-Assisted Decision Support System for Technological Hazardous Waste Sites,” Photogrammetric Engineering & Remote Sensing, 75(2): 169-177.

Kröpelin, S., et al., 2008. “Climate-Driven Ecosystem Succession in the Sahara: The Past 6,000 Years,” Science, 320: 765-768.

Liu, J., et al., 2007. “Complexity of Coupled Human and Natural Systems,” Science, 317(5844): 1513-1516.

National Research Council, 2002.

Down to Earth: Geographic Information for Sustainable Development in Africa. National Academies Press, Washington, D.C.

Scheffer, M., et al.,2001. “Catastrophic Shifts in Ecosystems,” Nature, 413: 591-596.

Seaquist, J., et al., 2008. “Disentangling the Effects of Climate and People on Sahel Vegetation Dynamics,” Biogeosciences Discussions, 5: 3045-3067.

SIAC, 2007. “SAIC Employee’s Research in Niger Yields Optimism for Africa,” SIAC Magazine, Summer/Fall 2007, available on-line at:

Steffen, W., et al., 2004. Executive Summary: Global Change and the Earth System: A Planet Under Pressure.

IGBP, available on-line at:

Stige, L., et al., 2006.“The effect of climate variation of agro-pastoral production in Africa,” PNAS,103(9): 3049-3053.

Tappan, G., et al., 2004. “Ecoregions and Land Cover Trends in Senegal,” J. Arid Environments,

Tucker, C.J., et al., 1985. “African Land Cover Classification with Satellite Data,” Science, 227(4685): 369-375.

Tucker, C.J., et al., 1991. “Expansion and Contraction of the Sahara Desert from 1980 to 1990,” Science, 253(5017): 299-301.

Table des illustrations

Titre Figures 1 and 2
Légende The village of Galma, Niger in 1975 (left) and 2003 (right).Source: La transformation silencieuse de l’environnement et des systems de production au Sahel : Impacts des investissements publics et privés dans la gestion des ressources naturelles, Botoni and Reij, 2009.
Fichier image/jpeg, 233k


Department of Geography, Kansas State University, Manhattan, KS 66506

Department of Geography, Kansas State University, Manhattan, KS 66506

Department of Geography, Kansas State University, Manhattan, KS 66506

© IRD Éditions, 2010

Conditions d’utilisation :