Geographically distributed parameters are easiest to interpret and understand when they are graphically represented (in the form of maps). When they are handled in terms of raw numbers, on the other hand, they are much more difficult to assimilate or comprehend.

Take, for example, the hypothetical distribution of mosquitoes in IIT, Bombay. The first thing that strikes one is that there are high, localised concentrations in some areas and a relatively low distribution elsewhere. Then one notices that the area bordering the lake has a high concentration, and this leads to the inference that the stagnant water there is the cause. The other high concentrations do not have obvious explanations, and further study may be needed to identify their causes. A few may turn out to be the result of open rubbish dumps; others may be due to a thick growth of bushes.

Thus maps, besides giving an idea of the nature of a distribution, can also give insight into the causes of various phenomena. This would not be possible (except for an expert) if the data were represented purely in the form of numbers and coordinates. Maps are therefore ideally suited for use as a decision-making tool, particularly in situations that involve the analysis or understanding of geographically distributed parameters.