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    Dense Point Cloud Extraction from UAV Captured Images in Forest Area


    Tao, Wang and Lei, Yan and Mooney, Peter (2011) Dense Point Cloud Extraction from UAV Captured Images in Forest Area. In: Spatial Data Mining and Geographical Knowledge Services (ICSDM), 2011 IEEE International Conference on. IEEE, pp. 389-392. ISBN 978-1-4244-8352-5

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    Abstract

    LIDAR (Light Detection And Ranging) is widely used in forestry applications to obtain information about tree density, composition, change, etc. An advantage of LIDAR is its ability to get this information in a 3D structure. However, the density of LIDAR data is low, the acquisition of LIDAR data is often very expensive, and it is difficult to be utilised in small areas. In this article we present an alternative to LIDAR by using a UAV (Unmanned Aerial Vehicle) to acquire high resolution images of the forest. Using the dense match method a dense point cloud can be generated. Our analysis shows that this method can provide a good alternative to using LIDAR in situations such as these.

    Item Type: Book Section
    Additional Information: The definitive version of this article is available at DOI: 10.1109/ICSDM.2011.5969071 ©2011 IEEE
    Keywords: Dense Match; Forest; Point Cloud; SFM; UAV;
    Academic Unit: Faculty of Science and Engineering > Computer Science
    Item ID: 5882
    Identification Number: https://doi.org/10.1109/ICSDM.2011.5969071
    Depositing User: Peter Mooney
    Date Deposited: 19 Feb 2015 16:34
    Publisher: IEEE
    Refereed: Yes
    URI:

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