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 initiatives and is proving to be a critical component in a variety of development efforts throughout Africa.
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 laying 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 other vegetables harvested twice annually.
The residents of the six villages (Ngonle, Konti 1, Konti 2, Diounkou 2, Diounkou 3 and Fampie 2) bordering the reserve began encroaching on the forest about 10 years ago with the compliance of village elders, but without official permission from the constituted authority (see Figure 1).The allocation of the farms comes from the village chiefs such that individuals with greater means and more powerful relationships can garner farmlands in different village blocks from different village chiefs, resulting in individuals controlling different farms throughout the entire reserve.
With the use of GIS and GPS technologies, Ngwa 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 by documenting the trees co-existing within the cultivated areas.
Describing the project Ngwa said, "Minimum farm sizes of 30m x 30m (900m2) were identified within each block and used to estimate the areas of larger farm holdings with code numbers attributed.Waypoints were then taken for all of them and downloaded into a computer to produce a database.Field data sheets were also used to collect other attribute information that was manually added to the database generated.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 in producing thematic maps that depicted the forest reserve layout and individual farm holdings (see Figure 2).The map served for educational purposes to all those 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."
Concludes Ngwa, "Since our map of the reserve is 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."
Modeling Potential Malarial 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% of the country's 70 million people are exposed to malaria and more than 5 million cases are diagnosed with the disease each year.
Ethiopia's Ministry of Health summarizes the impact of malaria on the country in this way."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 non-malaria risk highland areas has resulted in a massive environmental and ecological degradation and loss of productivity that exposes a large population of the country to repeated droughts, famine and overall abject poverty. The increased school absenteeism during malaria epidemics significantly reduces the learning capacity of students.In addition, coping up with malaria epidemics overwhelms the capacity of the 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 & 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 (MEWS) 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 (see Figure 3).
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 malarial parasite and mosquito can be incorporated into a GIS to develop predictive models for malarial epidemic forecasting (see Figure 4).
EROS uses satellite imagery in conjunction with ESRI's ArcGIS components ArcView and ArcInfo Grid to develop such models.The data is analyzed and overlaid on a topographical map to determine the likely time and location of pending malarial outbreaks.
"What we have determined," commented 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 mid-September creates a conducive environment for mosquito breeding in areas where water has been accumulating from the main 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 malarial hotspots identified with GIS-based predictive modeling, affected communities can be mobilized to perform preventive or mitigating activities such as setting up or re-energizing community clean-up programs, ordering mosquito nets, stocking medication in proportion to the expected severity of the malaria outbreak and staging awareness campaigns on the transmission and prevention of malaria to help minimize the severity of the pending outbreak.