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Bridging the African Divide with GIS
Ancient Africa, a cradle of civilization, has known kings with great perception and understanding, insightful scientists, and visionary architects. It has also known, over time, the slave trade, debilitating disease of staggering proportions, and genocide. It is a land of sharp contrasts, hanging in the balance as it does with some regions rich in natural and man-made resources while others teeter on the precipice of starvation, disease, and death.
GIS technology has proven itself to be a great equalizer throughout the world in the acquisition, management, and distribution of information. In many cases, this technology can be applied to humanitarian and sustainable development efforts, which are in great need in Africa. Here are two examples of how GIS is being used.
Balancing Conservation Goals and Agricultural Needs in Cameroon
Striking a balance between conservation goals and agricultural needs is no easy task, particularly in the Republic of Cameroon, located in Central Africa.
While the country has benefited economically in recent years from oil and agricultural exports, subsistence farming remains a way of life, with some of the best farmland lying in the Baleng Forestry Reserve located in the country's West Province. Water in the region is plentiful and the soil rich. These favorable conditions allow a double cropping scenario with short growth cycle crops, such as corn, beans, and vegetables, harvested twice annually.
The residents of the six villages (Diounkou 2, Diounkou 3, Fampie 2, Konti 1, Konti 2, and Ngonle) bordering the reserve began encroaching on the forest approximately 10 years ago with the compliance of village elders but without official permission from the constituted authority.
Farms are allocated by the village chiefs, and individuals with greater means and more powerful relationships can garner farmlands in different village blocks from different village chiefs, giving them control over different farms throughout the entire reserve.
Ngwa Christopher Ambe, GIS officer of the GIS/Remote Sensing Unit of Limbe Botanic Garden-Cameroon, under the coordination of the Provincial Delegate for Forestry and Wildlife for the West Province Madam Mbah Grace Nyieh, began developing methodologies for farmland management within the reserve using ArcView in 2004. As the database was updated, he became aware of this unique landownership distribution.
With the use of GIS and GPS technologies, Ambe helped develop the Participatory Management Contract Plan that established a framework allowing farmers to continue their cultivation for a fixed period of time while preserving the trees within their croplands. This was accomplished by accurately defining the borders of the Baleng Forestry Reserve, identifying those individuals and families farming within it, and documenting the trees coexisting within the cultivated areas.
Describing the project, Ambe says, "Minimum farm sizes of 30 m x 30 m (900 m2) were identified within each block and used to estimate the areas of larger farm holdings by assigning code numbers. GPS waypoints were then taken for all farms and downloaded into a computer to produce a database. Field data sheets were used to collect other attribute information and manually added to the database. The database thus contained information on the number of trees per farm and per block, farm owners' identities, block codes, villages of origin, chiefs' names, and types of crops. The database was later used with ArcView to produce thematic maps that depicted the forest reserve layout and individual farm holdings. The maps educated everyone involved in the reserve. Reserve and village block management committees were then set up to sustain tree nurseries and replanting under the supervision of forestry technicians and local day and night watchmen. The signing of participatory management contracts ensures the safety and maintenance of nurseries and replanted trees and the subsequent regeneration of the destroyed reserve, while guaranteeing continuous cultivation for a transitional period of 10 years (after which all the farmers must quit the reserve), thereby halting further deforestation and ensuring food security for the villagers."
Penalties for removing trees within the reserve include both incarceration and fines ranging from $400 (U.S.) to $2,000 (U.S.), as stipulated by national laws. In addition, the value of the felled trees is calculated and added to the court fines.
Concludes Ambe, "Since our maps of the reserve are completely georeferenced, the individual farms within the reserve are all coded and the trees within the farms documented, providing us with very good information regarding the trees within the cultivated land that are the responsibility of the farmers to protect. If we discover a felled tree, we simply take its GPS point and can easily determine whether or not the tree is within the reserve, and if so, we can bring the culprit to justice."
For more information, contact Ngwa Christopher Ambe, Limbe Botanic Garden- Cameroon (e-mail: email@example.com).
Modeling Potential Malaria Hotspots in Ethiopia
Nearly a million deaths occur annually in sub-Saharan Africa as a result of malaria. It kills an African child every 30 seconds, and those who are fortunate enough to survive a severe episode of the disease may suffer lasting learning impairments or brain damage. In Ethiopia, more than 65 percent of the country's 70 million people are exposed to malaria, and more than five million cases of the disease are diagnosed each year.
Ethiopia's Ministry of Health summarizes the impact of malaria on the country, "The socioeconomic burden resulting from malaria is immense. The high morbidity and mortality rate in the adult population significantly reduces production activities. The prevalence of malaria in many productive parts of the country prevents the movement and settlement of people in resource-rich low-lying river valleys, while the concentration of population in nonmalaria risk highland areas has resulted in a massive environmental and ecological degradation and loss of productivity that exposes a large population to repeated droughts, famine, and overall abject poverty. The increased school absenteeism during malaria epidemics significantly reduces the education of students. In addition, coping with malaria epidemics overwhelms the capacity of health services in Ethiopia and, thus, substantially increases public health expenditures."
According to Gabriel Senay, a senior scientist at the National Center for Earth Resources Observation and Science (EROS), "Malaria in Ethiopia is not only a health issue, it is also a food security and environmental issue."
To help counter this scourge, a Malaria Early Warning System is being developed for deployment throughout Africa. Several studies have been made to connect malaria epidemics and weather variables. Rainfall, temperature, humidity, and soil moisture are factors known to affect the transmission rate of malaria.
Efforts to predict malaria epidemics focus on the role weather anomalies can play in epidemic prediction. In addition to weather monitoring and seasonal climate forecasts, epidemiological, social, and environmental factors can play a role in predicting the timing and severity of malaria epidemics. Basically, certain conditions can produce a surge in numbers of both the parasite that causes the disease and the host mosquito that spreads it. The data related to the various factors that lead to the increase of both the malaria parasite and mosquito can be incorporated into a GIS to develop predictive models for malaria epidemic forecasting.
EROS uses satellite imagery in conjunction with ArcGIS Desktop software ArcView and ArcInfo to develop such models. The data is analyzed and overlaid on a topographical map to determine the likely time and location of pending malaria outbreaks.
"What we have determined," comments Senay, "is that the presence of a lag time between peak malaria transmission and seasonal rainfall events is very important for forecasting malaria outbreaks using observed weather data. Once the main rainy season declines in intensity and frequency in September, the increasing average daily temperature and progressive dryness beginning in mid-September create a conducive environment for mosquito breeding in areas where water has been accumulating from the main rainy season. The lag time between the end of the main rainy season and peak malaria transmission can be explained by the inherent lag time in mosquito breeding and parasite life cycle inside the mosquito, which are dependent on air temperature and humidity."
By highlighting potential malaria hotspots identified with GIS-based predictive modeling, affected communities can be mobilized to perform preventive or mitigating activities to help minimize the severity of the pending outbreak.
For more information, contact Gabriel Senay, senior scientist, USGS, EROS (e-mail: firstname.lastname@example.org, tel.: 605-594-2758).