Improving Vegetation and Background Discrimination from Hyperspectral Imaging (HSI) and Light Detection and Ranging (LiDAR) Fusion Using an Added Shortwave Infrared (SWIR) HSI Component
| dc.contributor.advisor | Stefanidis, Tony | |
| dc.contributor.author | Magarick, Joshua F. | |
| dc.creator | Magarick, Joshua F. | |
| dc.date | 2012-11-15 | |
| dc.date.accessioned | 2013-02-18T17:34:53Z | |
| dc.date.available | NO_RESTRICTION | |
| dc.date.available | 2013-02-18T17:34:53Z | |
| dc.date.issued | 2013-02-18 | |
| dc.description.abstract | An observation made with respect to reviewing previous work in this domain is that many authors do not include the use of shortwave infrared (SWIR) bands that are made available by some hyperspectral imaging (HSI) sensor systems. This work will investigate the fusion of HSI and light detection and ranging (LiDAR) data that will include the use of SWIR bands during the fusion process in order to better characterize, discriminate, map, detect, and possibly identify, background vegetation materials. Data for this project comes from an August 2008 collection over the Washington, DC National Arboretum using the Mapping Reflected Energy Spectrometer (MaRS) Visible Near Infrared and SWIR (VNIR/SWIR) HSI system, and also from an Optech 3100 ALTM LiDAR system. The two targets chosen for analysis were the American sweetgum tree and several trails (footpaths). The objective of this work is to run several data fusion experiments where LiDAR raster transformations are fused with VNIR-only, SWIR-only, and full VNIR/SWIR HSI data to investigate which combination of fusion methods are optimal under the given circumstances. In some cases, improvement in the American sweetgum tree detection and trails detection is noted when the SWIR HSI bands are included in the data fusion analysis. | |
| dc.identifier.uri | https://hdl.handle.net/1920/8015 | |
| dc.language.iso | en | |
| dc.subject | Hyperspectral | |
| dc.subject | LiDAR | |
| dc.subject | HSI LiDAR Fusion | |
| dc.subject | Data fusion | |
| dc.subject | VNIR/SWIR HSI | |
| dc.subject | Vegetation discrimination | |
| dc.title | Improving Vegetation and Background Discrimination from Hyperspectral Imaging (HSI) and Light Detection and Ranging (LiDAR) Fusion Using an Added Shortwave Infrared (SWIR) HSI Component | |
| dc.type | Thesis | |
| thesis.degree.discipline | Geoinformatics and Geospatial Intelligence | |
| thesis.degree.grantor | George Mason University | |
| thesis.degree.level | Master's | |
| thesis.degree.name | Master of Science in Geoinformatics and Geospatial Intelligence |