Although my results were similar to the current agricultural practices map (with some slight variance), I feel they would have been more accurate had I found a data layer for soils existing in Africa.  The outcome of my project demonstrated areas where conditions were favourable for agricultural production (i.e. where the topsoil wouldn't be blown away), however, an African soils layer would have made the dataset I was using much richer in content.  A drawback to this, however, would be that adding more data to the set I already had would have been almost too constricting.  An example of this type of constraint is observed in Check3.rst already.  Too many factors lead to too many constraints, making the area of land suitable for agricultural production very low.  This is where the fuzzy map (AfricaWLC) helped out a lot by giving more than a "yes or no" answer, but also degrees of suitability based on the weights assigned to each factor.  Compromises were made for each layer (just like in the "real world"), whereby weights were assigned to each factor recognizing some factors as more important than others.  Since we can rarely have all factors at once, we decide which factors are most important, and which ones we could possibly do without.

Another important outcome of this project was the fact that where my final results showed the most variance (compared to the current agricultural practices map), was not in an area that is considered to be the most ideal place to carry out broad-scale farming.  In Africa, there isn't much of a choice in where to farm already, however, there would be massive political outcry if people living in the region began destroying large portions of the rainforest in order to grow food.  The threat of desertification looms near, and should large sections of the rainforest be destroyed, soil, wind and water erosion would increase greatly.  The tall and dense forest canopy protects the soil underneath, and so once it is gone, it can no longer protect against wind and rain.  Also, once a rainforest canopy is destroyed, it never grows back as thick as before, thus it allows more water to penetrate the soil and erode it.  The forest itself will grow back after many years if left untouched, however, it never fully recovers from the shock of mass-exploitation.  Lastly, soils in this region are only productive for a period of about three years, and then they must be abandoned for a much longer period (15-20 years) before the fertility of the soil is allowed to return.  This is why localized farming is the trend that exists in the rainforest.  My data could not account for this trend, so background knowledge of physiographic regions is necessary is order for map interpretation.

Aside from these problems (along with problems collecting data and differing cell sizes discussed in earlier sections), this project was very informative.  The results were educational in that they clearly demonstrated the constant problem faced by Africans when it comes to agricultural production in their continent.  There are many environmental constraints that must be dealt with, making where to farm a great concern and sometimes a difficult task.  The overlaying and multiplying of suitable areas helped me come to the conclusion that water is probably one of the most important factors when it comes to agricultural production anywhere in Africa.  Most places that are currently under agricultural use are seen along the perimeter of the continent where water is abundant.  I learned a lot from this project and hope others can as well.

BACK TO INDEX