Abstract

Identifying sites for economic development is the first requirement for any such project. Once the developer identifies a sight, then it is often a tedious and frustrating process to receive approval from the controlling municipal authority to develop the site, often complicated by the role of the local community impacting the decision process. The socio-economic factors may be the controlling factors on whether or not economic development can take place in a community. In this study, a Geographic Information System (GIS) model is developed that includes socio-economic constraints in addition to the normally used physical constraint factors in determining the potential for a specific site for development. The proposed model uses mathematical weighting factors to reflect community opinions for a selected set of socio-economic factors. The socio-economic factors are translated into mathematical values by using three dimensions: weight (or the level of importance), acceptability, and a distance factor. Once the physical constraints have identified accepted sites, then the socio-economic values are then overlaid on top of the physical constraint suitability map that then further restricts sites to those that are acceptable to the community based upon their own criteria that was used to develop the socio-constraint portion of the GIS model. The weighting and acceptability factors are developed from community input. These factors then combined with the distance factor, which is a quantitative fact result in site restrictions. The model was applied to a community in Southampton, New York to demonstrate its utility in addressing community concerns over a potential development project. This community was debating whether or not to allow additional near shore aquaculture activity. The conventional GIS model, which determines the potential sites solely based upon using physical conditions, e.g., oxygen, salinity, temperature, water depth-- identified 4,338 ha of appropriate submerged land, but was reduced to 162 ha once the socio-economic factors were applied in the model. Another socio-economic data set was applied to the model to see the sensitivity of the factors that were being applied. The weights of the smell, hearing, and taste/ touch combined were raised (smell by 5, hearing by 1, and touch/taste by 3) while keeping other parameters the consistent with the first data set. The model then yielded 4,312 ha of submerged land with a negative suitability index, and only 23 ha of submerged land with a positive suitability index. This study is one of the first attempts to incorporate surrounding community non-physical parameter variables when determining whether or not to allow further economic development for the local community. This model can act as a bridge between developers and the local community when political leaders make decisions relative to allowing development to be allowed.