Terrain categorization using LIDAR and multispectral data

Angela M. Puetz; R. C. Olsen; Michael A. Helt

doi:10.1117/12.719885

14 May 2007 Terrain categorization using LIDAR and multispectral data

Angela M. Puetz, R. C. Olsen, Michael A. Helt

Proceedings Volume 6565, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIII; 65650V (2007) https://doi.org/10.1117/12.719885
Event: Defense and Security Symposium, 2007, Orlando, Florida, United States

Abstract

LIDAR data taken over the Elkhorn Slough region in central California were analyzed for terrain classification. Data were collected on April 12th, 2005 over a 10 km × 20 km region that is mixed use agriculture and wetlands. LIDAR temporal information (elevation values), intensity of returned light and distribution of point returns (in both vertical and spatial dimensions) were used to distinguish land-cover types. Terrain classification was accomplished using LIDAR data alone, multi-spectral QuickBird data alone and a combination of the two data-types. Results are compared to significant ground truth information.

Citation Download Citation

Angela M. Puetz, R. C. Olsen, and Michael A. Helt "Terrain categorization using LIDAR and multispectral data", Proc. SPIE 6565, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIII, 65650V (14 May 2007); https://doi.org/10.1117/12.719885

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