Ben-ArieHayPowersEtAl2009

Référence

Ben-Arie, J.R., Hay, Geoffrey J., Powers, R.P., Castilla, G. and St-Onge, B. (2009) Development of a pit filling algorithm for LiDAR canopy height models. Computers and Geosciences, 35(9):1940-1949. (URL )

Résumé

LiDAR canopy height models (CHMs) can exhibit unnatural looking holes or pits, i.e., pixels with a much lower digital number than their immediate neighbors. These artifacts may be caused by a combination of factors, from data acquisition to post-processing, that not only result in a noisy appearance to the CHM but may also limit semi-automated tree-crown delineation and lead to errors in biomass estimates. We present a highly effective semi-automated pit filling algorithm that interactively detects data pits based on a simple user-defined threshold, and then fills them with a value derived from their neighborhood. We briefly describe this algorithm and its graphical user interface, and show its result in a LiDAR CHM populated with data pits. This method can be rapidly applied to any CHM with minimal user interaction. Visualization confirms that our method effectively and quickly removes data pits.

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@ARTICLE { Ben-ArieHayPowersEtAl2009,
    AUTHOR = { Ben-Arie, J.R. and Hay, Geoffrey J. and Powers, R.P. and Castilla, G. and St-Onge, B. },
    TITLE = { Development of a pit filling algorithm for LiDAR canopy height models },
    JOURNAL = { Computers and Geosciences },
    YEAR = { 2009 },
    VOLUME = { 35 },
    PAGES = { 1940-1949 },
    NUMBER = { 9 },
    MONTH = { sep },
    ABSTRACT = { LiDAR canopy height models (CHMs) can exhibit unnatural looking holes or pits, i.e., pixels with a much lower digital number than their immediate neighbors. These artifacts may be caused by a combination of factors, from data acquisition to post-processing, that not only result in a noisy appearance to the CHM but may also limit semi-automated tree-crown delineation and lead to errors in biomass estimates. We present a highly effective semi-automated pit filling algorithm that interactively detects data pits based on a simple user-defined threshold, and then fills them with a value derived from their neighborhood. We briefly describe this algorithm and its graphical user interface, and show its result in a LiDAR CHM populated with data pits. This method can be rapidly applied to any CHM with minimal user interaction. Visualization confirms that our method effectively and quickly removes data pits. },
    ISSN = { 0098-3004 },
    KEYWORDS = { LiDAR, Data pits, Noise removal, Canopy height model, Interactive data language (IDL) },
    OWNER = { sobru1 },
    TIMESTAMP = { 2009.08.27 },
    URL = { http://www.sciencedirect.com/science/article/B6V7D-4VWB19B-1/2/4421b767752578dd455d3de6c4950c14 },
}

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