BACKGROUND
In more recent history, Americans have become more aware of the costs and consequences of using traditional coal and fossil fuels as energy sources. Now equipped with this knowledge and improved technology, the U.S. has increasingly turned to renewable energy sources such as wind energy. In the 1990s the State of California had long been the leader in generating wind energy, having the most windmill farms in the U.S. (CA Energy). Although Texas now generates the most wind energy in the United States, California's growing population demands increased energy that is renewable and sustainable. The State's varied terrain and land cover allows for additional sites for wind farms.
Inspired by the windmills along the Tehachapi Pass, I focused my research suitable locations within Southern California. This region of the state includes bustling metropolitan areas and burgeoning suburbs which have experienced increased immigration from other areas in recent years. Another point of interest in Southern California is that, compared to Central and Northern California's vegetation and agricultural land, the heavily urbanized areas in Southern California pose a challenge to finding space for wind farms. However, a large part of Southern California's land cover includes desert and grass which is more suitable for potential windmill sites.
METHOD
Before starting my project, I was posed with the question of defining which portion of the state constitutes "Southern California" versus Central or Northern California. Since these separate regions are culturally distinct from one another, residents of each region are particular (and even proud) about where they live. According to DeLio and Smith, Southern California includes, Santa Barbara, Ventura, Los Angeles, and San Bernardino Counties and southward, which are the counties included in my study.
Prior to my research, I considered several factors that would constitute a suitable location for a windmill farm, including: 1) landcover types, 2) elevation or slope of the area, 3) distance from urbanized areas (to provide energy for those communities), 4) impacts on bird migration paths, 5) regional wind speed averages, and 6) distance from already-established wind farms. While bird migration paths are a very important factor in siting for wind farms, I decided to exclude this factor, considering the time and resource limitations of this project.
In order to produce a map of the slope of Southern California Counties, I obtained Digital Elevation Models (DEMs) from the USGS Seamless Server. With ArcGIS I projected the rasters of the DEMs and then produced slope by percent rise. According to research by the State of California Energy Commission, higher elevations tend to yield faster winds, making areas of higher slope more suitable for windmill locations.
To convey the various types of land use and landcover throughout Southern California counties, I obtained data from the California Fire and Resource Assessment Program (FRAP). This data included the following categories: Agriculture, Herbaceous, Desert, Barren/Other, Shrub, Hardwood, Wetland, Conifer, Water, and Urban. I reclassfied the categories as follows (highest being the most suitable land for potential wind farms):
8: Barren/Other
7: Desert
6: Herbaceous
5: Shrub
4: Hardwood
3: Conifer
2: Wetland
1: Agriculture
0: Water
NoData: Urban
For distance in relation to urbanized areas, I obtained shapefiles of urbanized areas from the UCLA GIS Mapshare. From this data, I created 5-mile buffers from the boundaries of urbanized areas for two reasons: 1) to keep a reasonable distance from metropolitan areas, but 2) sometimes being closer may help make generating wind power more efficient.
To visualize the current locations of existing windmills, I geocoded the approximate addresses to avoid building turbines too closely to existing wind farms.
Lastly, from the State of California Department of Energy, I obtained data of annual average wind power in California (in miles per hour as well as meters per second). Seeing how this data spatially shows that some of the windiest on-shore areas in California are in Southern California counties.
Using the raster calculator, I reclassfied the layers of each suitability factor:
[ Land Use Type ] + [ Average Wind ] + [ Slope ] + [ Distance Urban Buffer ] + [ Distance from Existing Wind Farms ]
RESULTS
Reclassifying land use data revealed that a large portion of Southern California counties are desert, largely in San Bernardino and Riverside Counties. Naturally it makes sense that most existing California wind farms are located in these counties. Overlaying the layer of existing wind mills with the urbanized area layer revealed that windmills are currently fairly close to cities. Tjhis might suggest that the factor of distance from urbanized areas might not be as problematic as one might expect, depending on slope and other factors. In addition, while increased slope allows for faster winds, it may be more difficult to build turbines on high slopes.
After considering all five factors and running the raster calculation, it appears that the most suitable areas would exist in the eastern region of the San Bernardino Mountains. In this area there are higher wind speeds and higher slopes which are farther from heavily urbanized areas. Another suitable location appears to be in north San Bernardino County, just south of Kern County. While the Tehachapi and Mojave Wild Farms are situated in Kern County, just outside what is considered “Southern California,” these two locations are close enough to the southern counties to provide efficient wind energy.
CONCLUSION
Considering the factors of suitability included in this study, I think that a suitability analysis using this data would be helpful in locating potential windmill locations for Southern California. If it were not for time or resource limitations, I would certainly include analysis of avian migration information as it is extremely important when considering wind mill sites to minimize the incidences of avian deaths in the process of implementing renewable energy technologies.
In more recent history, Americans have become more aware of the costs and consequences of using traditional coal and fossil fuels as energy sources. Now equipped with this knowledge and improved technology, the U.S. has increasingly turned to renewable energy sources such as wind energy. In the 1990s the State of California had long been the leader in generating wind energy, having the most windmill farms in the U.S. (CA Energy). Although Texas now generates the most wind energy in the United States, California's growing population demands increased energy that is renewable and sustainable. The State's varied terrain and land cover allows for additional sites for wind farms.
Inspired by the windmills along the Tehachapi Pass, I focused my research suitable locations within Southern California. This region of the state includes bustling metropolitan areas and burgeoning suburbs which have experienced increased immigration from other areas in recent years. Another point of interest in Southern California is that, compared to Central and Northern California's vegetation and agricultural land, the heavily urbanized areas in Southern California pose a challenge to finding space for wind farms. However, a large part of Southern California's land cover includes desert and grass which is more suitable for potential windmill sites.
METHOD
Before starting my project, I was posed with the question of defining which portion of the state constitutes "Southern California" versus Central or Northern California. Since these separate regions are culturally distinct from one another, residents of each region are particular (and even proud) about where they live. According to DeLio and Smith, Southern California includes, Santa Barbara, Ventura, Los Angeles, and San Bernardino Counties and southward, which are the counties included in my study.
Prior to my research, I considered several factors that would constitute a suitable location for a windmill farm, including: 1) landcover types, 2) elevation or slope of the area, 3) distance from urbanized areas (to provide energy for those communities), 4) impacts on bird migration paths, 5) regional wind speed averages, and 6) distance from already-established wind farms. While bird migration paths are a very important factor in siting for wind farms, I decided to exclude this factor, considering the time and resource limitations of this project.
In order to produce a map of the slope of Southern California Counties, I obtained Digital Elevation Models (DEMs) from the USGS Seamless Server. With ArcGIS I projected the rasters of the DEMs and then produced slope by percent rise. According to research by the State of California Energy Commission, higher elevations tend to yield faster winds, making areas of higher slope more suitable for windmill locations.
To convey the various types of land use and landcover throughout Southern California counties, I obtained data from the California Fire and Resource Assessment Program (FRAP). This data included the following categories: Agriculture, Herbaceous, Desert, Barren/Other, Shrub, Hardwood, Wetland, Conifer, Water, and Urban. I reclassfied the categories as follows (highest being the most suitable land for potential wind farms):
8: Barren/Other
7: Desert
6: Herbaceous
5: Shrub
4: Hardwood
3: Conifer
2: Wetland
1: Agriculture
0: Water
NoData: Urban
For distance in relation to urbanized areas, I obtained shapefiles of urbanized areas from the UCLA GIS Mapshare. From this data, I created 5-mile buffers from the boundaries of urbanized areas for two reasons: 1) to keep a reasonable distance from metropolitan areas, but 2) sometimes being closer may help make generating wind power more efficient.
To visualize the current locations of existing windmills, I geocoded the approximate addresses to avoid building turbines too closely to existing wind farms.
Lastly, from the State of California Department of Energy, I obtained data of annual average wind power in California (in miles per hour as well as meters per second). Seeing how this data spatially shows that some of the windiest on-shore areas in California are in Southern California counties.
Using the raster calculator, I reclassfied the layers of each suitability factor:
[ Land Use Type ] + [ Average Wind ] + [ Slope ] + [ Distance Urban Buffer ] + [ Distance from Existing Wind Farms ]
RESULTS
Reclassifying land use data revealed that a large portion of Southern California counties are desert, largely in San Bernardino and Riverside Counties. Naturally it makes sense that most existing California wind farms are located in these counties. Overlaying the layer of existing wind mills with the urbanized area layer revealed that windmills are currently fairly close to cities. Tjhis might suggest that the factor of distance from urbanized areas might not be as problematic as one might expect, depending on slope and other factors. In addition, while increased slope allows for faster winds, it may be more difficult to build turbines on high slopes.
After considering all five factors and running the raster calculation, it appears that the most suitable areas would exist in the eastern region of the San Bernardino Mountains. In this area there are higher wind speeds and higher slopes which are farther from heavily urbanized areas. Another suitable location appears to be in north San Bernardino County, just south of Kern County. While the Tehachapi and Mojave Wild Farms are situated in Kern County, just outside what is considered “Southern California,” these two locations are close enough to the southern counties to provide efficient wind energy.
CONCLUSION
Considering the factors of suitability included in this study, I think that a suitability analysis using this data would be helpful in locating potential windmill locations for Southern California. If it were not for time or resource limitations, I would certainly include analysis of avian migration information as it is extremely important when considering wind mill sites to minimize the incidences of avian deaths in the process of implementing renewable energy technologies.
Michael DiLeo, Eleanor Smith, Two Californias: The Truth about the Split-state Movement, Island Press, Covelo, California, 1983. pg. 9-30.
Pasqualetti M. J., Society and Natural Resources, Volume 14, Number 8, 1 September 2001 , pp. 689-699(11). Routledge, part of the Taylor & Francis Group.
