Spatial Modeling of Optimum Zones for Wind Farms Using Remote Sensing and Geographic Information System, Application in the Red Sea, Egypt


Wind power is a safe form of renewable energy and is one of the most promising alternative energy sources. Worldwide, the wind power industry has been rapidly growing recently. It is crucial that the locating of new projects must address both environmental and social concerns. The Red Sea shoreline in Egypt provides excellent wind power potential sites for the Red Sea Governorate. In this study, appropriate zones for wind power farms were mapped using remotely sensed data and a GIS-based model namely Spatial Multi-Criteria Evaluation (SMCE). This model incorporated several criteria, two sets of factors and a set of constraints. First, resource factors included wind speed, elevation zones used to derive the wind power density. Second, economic factors included distances from urban areas, roads and power-lines. Third, land constraints were excluded from the evaluation. The land constraints set included land slope angles, shoreline, urban areas, protectorates airports and ecologically sensitive and historical areas. The Analytical Hierarchy Process was used to assign the criteria relative weights. The weighted criteria and constraints maps were combined in the MCE model. The model identified the zones with potential wind power energy. Such zones were found to exist along the northern parts of the Red Sea shoreline. Some of which are unsuitable due to their location within a sensitive eco-system, high slopes and/or a nearby airport. By excluding such land constrains, the model identified the most appropriate zones satisfying all assigned suitability conditions for wind farms. Ideal zones amount to 706 sq. km with suitability values ranging from 83% to 100% and highly suitable zones amount to 3781 sq. km having suitability values ranging from 66% to 83%.

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Effat, H. (2014) Spatial Modeling of Optimum Zones for Wind Farms Using Remote Sensing and Geographic Information System, Application in the Red Sea, Egypt. Journal of Geographic Information System, 6, 358-374. doi: 10.4236/jgis.2014.64032.

Conflicts of Interest

The authors declare no conflicts of interest.


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