All the files that were used in the project were seen as constraints in order to produce the final image MCE.

In this image the green parts represent the most suitable areas to grow the coffee trees.  All the constraints are satisfied in these areas and these places are the perfect places to grow the crop arabica.  However, the elevation image was not placed within this spatial analysis because its columns and rows do not fit in with the other images.  Therefore, it was not possible to overlay or include it into the MCE function for spatial analysis.

    However, with the help of the vector files that show the coastline and country borders in Africa, one can see that the most suitable place when elevation is included into the MCE image is in northern Angola.  This is because the biggest patch of land from the MCE image is located in northern Angola.  Angola is also suitable in the elevation levels in which almost all of the country is green, making it suitable.

    MCE Boolean approach is a more conservative way of locating a place to grow arabica.  It takes into account all the factors or constraints and will only produce an image where the area shown is where all the factors or constraints equals to one.  This is in a sense less riskier to the company or investor who wants to invest money in this area since the area is bound by so many constraints.  Hence, the MCE Boolean approach is a good way to find the most suitable place to grow the crop if the investors do not want a lot of risk when choosing the best area to grow the crop.

    Being the more conservative investor, I would stay with the less riskier approach in finding the most suitable area to grow the crops.  However, other more risk taking investor might want to look into the riskier approach as in the MCE Weight Linear Combination approach.  This is the method were it allows the trade off between the factors or constraints.  Since I favor the Boolean "conservative" approach in investing hence, I only used the MCE Boolean approach to locate the most suitable place.

    I also used the image calculator to produce an image using the function OR.  This image shows the area in which at least one criteria is met.  That is, one constraint is used in determining the image.

    As one can see in the above Boolean OR function, the green parts are the suitable areas.  However, this image proves to be of no use because the whole continent is suitable except for areas where lakes were.  This image is used to show how risk taking it is to use the Boolean OR function.  This image also shows the extremes between the two functions.  Hence it is best to use the MCE Boolean image in order to determine the best location to plant arabica.