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A GIS-based modeling of environmental health risks in populated areas of Port-au-prince, Haiti

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par Myrtho Joseph
University of Arizona - Master in Natural Resources Information System 1987
  

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4.1.2 The Maximum Weighting Scheme

The maximum weighting scheme so far was not taken into consideration in the previous discussions since it has a different connotation and could not bear a reasonable comparison with the other approaches. This function tends to maximize risk. Because of this a high percentage, 92.5%, of the area was found exposed at high and very high risks for all the hazards combined, which is a huge contrast to the results above. In this approach, since no weight was allocated, the cell with the biggest value rules over the others. Simply put, the result signifies that for this specific cell, there is at least one health hazard whose risk level corresponds to this maximum value. This method was chosen intentionally so as to bring forth the diversity of high risks prevailing in almost the entire area (Figure 6). This situation also reveals the lessening of individual factors' significance in aid of the collective importance of the model. Policies interested rather in solving environmental problems that arise from a specific field may find this approach more attractive and more practical.

Figure 6: Environmental Health Risks in Port-au-Prince - Maximum combination technique using the Geometric Interval classification method

This approach also outlines the specific location and extent of each hazard considered. For instance, someone accustomed to the area can clearly notice the path of high voltage power lines and the prism of risks in its neighborhood. Likewise, pollution associated to the proximity of the sea and of vehicle traffic is obvious.

The opposite procedure consisted of determining whether some areas were exposed simultaneously at high risk for all the hazards overlaid. A conditional statement was performed to superimpose all the areas where the conditions «high risk and very high risk» were met. This situation was not present in any area. This might be because of the spatial dispersion of the factors over the entire area.

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