@InProceedings{Kumar_ICDM_20151117,
 author		= {Jitendra Kumar and Jon Weiner and William W. Hargrove and Steven P. Norman and Forrest M. Hoffman and Doug Newcomb},
 title		= {Characterization and Classification of Vegetation Canopy Structure and Distribution within the {G}reat {S}moky {M}ountains {N}ational {P}ark using {LiDAR}},
 booktitle	= {Proceedings of the 15th {IEEE} International Conference on Data Mining Workshops ({ICDMW} 2015)},
 editor		= {Peng Cui and Jennifer Dy and Charu Aggarwal and Zhi-Hua Zhou and Alexander Tuzhilin and Hui Xiong and Xindong Wu},
 organization	= {Institute of Electrical and Electronics Engineers (IEEE)},
 publisher	= {Conference Publishing Services (CPS)},
 pages		= {1478--1485},
 doi		= {10.1109/ICDMW.2015.178},
 day		= 17,
 month		= nov,
 year		= 2015,
 abstract	= {Vegetation canopy structure is a critically important habitat characteristic for many threatened and endangered birds and other animal species, and it is key information needed by forest and wildlife managers for monitoring and managing forest resources, conservation planning and fostering biodiversity. Advances in Light Detection and Ranging (LiDAR) technologies have enabled remote sensing-based studies of vegetation canopies by capturing three-dimensional structures, yielding information not available in two-dimensional images of the landscape provided by traditional multi-spectral remote sensing platforms. However, the large volume data sets produced by airborne LiDAR instruments pose a significant computational challenge, requiring algorithms to identify and analyze patterns of interest buried within LiDAR point clouds in a computationally efficient manner, utilizing state-of-art computing infrastructure. We developed and applied a computationally efficient approach to analyze a large volume of LiDAR data and characterized the vegetation canopy structures for 139,859 hectares (540 sq.\ miles) in the Great Smoky Mountains National Park. This study helps improve our understanding of the distribution of vegetation and animal habitats in this extremely diverse ecosystem.}
}