by Luke Boggess, GISP – Group Manager: GIS Services
The long-term success and utility of many development projects often depends on where the project is located. An optimal location for a given facility frequently requires that the facility be located appropriately in relation to a multitude of constraints. For instance, in determining a suitable location for a wind farm, you must consider environmental, technical and economic factors when optimizing the location of the facility.
- Environmental factors include things such as the slope and elevation of the terrain, distances from faults and rivers, proximity to protected areas, land ownership, land cover and airspace.
- Technical factors include average wind speeds, wind continuity and wind density.
- Economic factors include distances from existing transmission corridors, urban areas and other utilities.
All of these factors can be modeled as geospatial layers in a Geographic Information System (GIS), and analyzed using overlay and proximity geoprocessing tools to determine the optimal location.
Before beginning the analysis, you must determine the criteria for what is suitable for a wind farm site. For example, within the land cover layer, forest land may not be optimal, while tundra may be ideal. Likewise, a site that is a far from an existing transmission corridor would be less desirable than one located nearer. After establishing all criteria, the project team would acquire necessary data. This may involve gathering existing data, converting data from a different format or collecting data in the field.
Once our team has acquired data for each of the environmental, technical and economic factors in the area of interest, we can begin site suitability analysis with preparatory geoprocessing. We process each factor using raster-based spatial analysis tools. We derive slope layers from elevation data (i.e. Digital Elevation Models (DEMs). Proximity geoprocessing tools are used to derive layers for distance to faults, rivers, transmission corridors, etc. After deriving the layers, the project team re-classifies and assigns values for each respective derived data layer using a uniform measurement scale (e.g. 1-10 Low-to-High).
Next, the project team determines the relative weight of each factor according to the percentage of influence and the rank of each scaled value. For instance, overall land cover may be considered to have a 15% influence, while wind speed has an influence of 50%. Also, within the land cover layer, the forest value may be ranked a 4, tundra ranked a 10 and wetlands (2) ranked as restricted.
After setting percentage of influence and rankings for each layer and all values, the project team combines the data layers using a weighted overlay process that results in a layer that depicts more desirable locations as a higher combined rank and less desirable locations as a lower rank. The project team extracts those with the highest rank to only optimal locations are depicted. However, many of the remaining optimal locations are too small in area to be feasible, so the project team uses a filter to refine the optimal locations resulting in generally larger optimal location areas.
The project team can then convert and query the refined optimal location layer to find the optimal locations that meet the minimum area requirements. We save these locations to a final data layer to be used for further investigation, planning, field verification, additional analysis, map production, and ultimately, wind farm site design.
Multi-criteria site suitability analysis is an evaluative process well-suited to GIS techniques. Combining multiple layers of data to discover patterns and relationships meeting the requirements of a particular facility is a core capability of GIS and can often reveal a meaningful picture of a site’s potential and limitations.
Azizi, A. (2014). Land suitability assessment for wind power plant site selection using ANP-DEMATEL in a GIS environment. Environ Monit Assess. 186:6695-6709
Esri (2014). ArcGIS Resources. Retrieved from http://resources.arcgis.com/en/help/main/10.2/index.html#/Exercise_3_Finding_a_site_for_a_new_school/00nt00000008000000/
Luke Boggess, GISP joined R&M as the firm’s Group Manager of GIS Services in 2011. He has more than 15 years of professional experience in GIS, Geomatics, land and natural resource management, and natural science. Luke is a certified GIS Professional and has been responsible for many phases of project work, including management, geospatial data collection, acquisition, interpretation and literature reviews, data and cartographic standards development and documentation, geospatial data QA/QC compliance and senior review. He has provided GIS support for a variety of projects across disciplines, including Earth Sciences, Urban and Regional Planning, Environmental Sciences, Surface Transportation, Site Development and Airports.
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