Renewable Energy Facility Siting Project
| dc.contributor.author | McKnight, Molly Xi | en |
| dc.date.accessioned | 2019-05-08T14:25:40Z | en |
| dc.date.available | 2019-05-08T14:25:40Z | en |
| dc.date.issued | 2019-04-26 | en |
| dc.description.abstract | The American public has become increasingly concerned about climate change. These concerns over the environment and the desire to decrease energy reliance on other countries have resulted in America’s pursuit of renewable forms of energy (Pew Research Center, 2016). One barrier to implementing renewable energy facility siting projects is public resistance as many people consider renewable energy infrastructure unsightly and intrusive. Some people also feel these projects impinge on their rights to the views to which they are accustomed. However, once the construction begins, community members tend to increase their support for the renewable energy site (Pew Research Center, 2016). This project aims to address public concern about renewable energy facilities by creating an interactive web application hosted on ArcGIS Online. The web application allows the public to type in their address and view how the renewable energy facility siting project impacts the views near their homes. Our hope is that this web application can help the public understand the actual effects on their views, and perhaps in some cases, convince the public that renewable energy is not as unsightly as they might think, allowing developers to overcome this initial barrier. GIS software provides the ability to generate 3D scenes, and GIS data sets, which are widely available on servers, provide basic layers that can be draped over a terrain. However, 3D objects on the terrain are not included in these data, so buildings and trees must be generated or collected for the scenes. In this project, we attempted to generate individual trees through extraction from LiDAR data to promote realism. This LiDAR-based methodology appeared to identify individual trees better areas with less dense tree cover than in heavily forested areas. Future plans include determining the accuracy of our individual tree extraction from LiDAR data method, comparing the LiDAR tree extraction method to a raster-based approach, and creating a fully-functional model of one of our renewable energy facility project sites. | en |
| dc.description.sponsorship | Virginia Tech. Office of Geographical Information Systems and Remote Sensing | en |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.uri | http://hdl.handle.net/10919/89373 | en |
| dc.language.iso | en | en |
| dc.publisher | Virginia Tech | en |
| dc.relation.ispartof | Virginia Tech GIS and Remote Sensing Research Symposium 2019 | en |
| dc.rights | In Copyright | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.title | Renewable Energy Facility Siting Project | en |
| dc.type | Poster | en |
| dc.type | Conference proceeding | en |
| dc.type.dcmitype | Text | en |
| dc.type.dcmitype | StillImage | en |