Wind Power Suitability Analysis for the Gulf of Maine

This map shows one option for a viable energy source that is clean, free and endless: wind power. This map shows that the coast of Maine has the potential space and wind speed to be a location for wind farms. Four NOAA buoys placed in different locations along the Maine coast are the source of the wind speed data for this project. The average wind speed of every ten minutes of every day for the year 2004 were averaged so that each buoy was represented by one number of wind speed measured in meters/ second. The values in between these four buoys were estimated, or interpolated, using ArcGIS. Other factors that I took into consideration during this lab were distance from airports (no wind farm can be with in a three mile radius of an airport ) and distance from counties (no one wants an offshore wind farm that obstructs their view). I calculated the most appropriate locations for a wind farm in ArcGIS, by adding these three layers. The final output shows an area along Mt. Desert to be the most appropriate for development.

Gulf of Mexico's Offshore Oil Platform Wind Potential

There are over 6000 natural resource drilling platforms in the Gulf of Mexico, all of which will become obsolete once their deposits are extracted. This study examined one of the possible alternate uses for these platforms, wind power potential. Using ArcGIS the number of platforms was reduced by weighting their distance from National Data Buoy Center wind speed collection points and water depth. Calculations were done to assess the optimal sites remaining, as well as provide an estimate of the energy potential for each site. Data for this project was obtained from the Minerals Management Service (MMS), United States Geological Service (USGS), and National Data Buoy Center (NDBC). A major limitation of this project was a lack of NDBC wind speed buoys, creating large data gaps and excluding many oil rigs that have otherwise high energy potential.

Fire Hazard in Coconino County, Arizona

Fire is a major management issue in the southwestern United States. Three spatial models of fire risk for Coconino County, Northern Arizona. These models were generated using thematic data layers depicting vegetation, elevation, wind speed and direction, and precipitation for January (winter), June (summer), and July (start of monsoon season). ArcGIS 9.0 was used to weight attributes in raster layers to reflect their influence on fire risk and to interpolate raster data layers from point data. Final models were generated using the raster calculator in the Spatial Analyst extension of ArcGIS 9.0. Ultimately, the unique combinations of variables resulted in three different models illustrating the change in fire risk during the year.