dc.contributor.author | Lofgren, Sean Joseph | |
dc.description.abstract | Characterizing features that influence beaver (Castor Canadensis) to select a site to construct a dam may have important implications for managing damage to select stands of bottomland hardwood forest by beaver activity. This study was initiated to determine and develop a quick and simple approach for managers to determine areas of most concern. Advanced Light Detection and Ranging (LiDAR) was collected for the study area in November of 2009. The study utilized software that has been developed to extract topographic features from a Digital Elevation Model (DEM). The extracted data was used to identify landscape variables to try and specify presence, future presence, and suitability of an area to support dam sites. This study, however, found that the development and use of such advanced LiDAR and DEM creation was error prone, which resulted in errors in the metrics that were calculated relative to the DEM. | en_US |
dc.publisher | North Dakota State University | en_US |
dc.rights | NDSU policy 190.6.2 | |
dc.title | Using Lidar Derived Information for Predicting Beaver Dam Site Selection at Mingo National Wildlife Refuge | en_US |
dc.type | Thesis | en_US |
dc.date.accessioned | 2017-11-14T16:58:21Z | |
dc.date.available | 2017-11-14T16:58:21Z | |
dc.date.issued | 2012 | |
dc.identifier.uri | https://hdl.handle.net/10365/26817 | |
dc.rights.uri | https://www.ndsu.edu/fileadmin/policy/190.pdf | |
ndsu.degree | Master of Science (MS) | en_US |
ndsu.college | Agriculture, Food Systems and Natural Resources | en_US |
ndsu.department | Natural Resources Management | en_US |
ndsu.department | School of Natural Resource Sciences | en_US |
ndsu.program | Natural Resources Management | en_US |
ndsu.advisor | Norland, Jack | |