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    Subsidence Monitoring Using Lidar and Morton Code Indexing

    Source: Journal of Surveying Engineering:;2016:;Volume ( 142 ):;issue: 001
    Author:
    Jianfeng Ao
    ,
    Kan Wu
    ,
    YongZhi Wang
    ,
    Liang Li
    DOI: 10.1061/(ASCE)SU.1943-5428.0000166
    Publisher: American Society of Civil Engineers
    Abstract: Point-based data-acquisition technology in traditional survey engineering does not provide complete data about mining-induced subsidence basins. To overcome these shortcomings, this research applied light detection and ranging (LIDAR) data, obtained with a terrestrial laser scanner (TLS) for monitoring the surface deformation of mining areas, to acquire full data about mining-induced subsidence basins. First, to improve the organization efficiency of LIDAR data, the decimal Morton code–based indexing method was proposed for discrete-grid indexing to organize LIDAR data according to original point coordinates, to avoid the generation of grids without data, and to build a topological relationship among scattered points. Thus, this approach enabled highly efficient access of LIDAR data and restoration of coordinates for each point. In the end, the processed data were applied in engineering practice. The subsidence curves of two sections of the subsidence basin, in both strike and dip directions measured with a high-grade control survey, were compared with the subsidence curves extracted from the LIDAR data. The good coincidence effect suggests that using LIDAR data to build the subsidence basin model can result not only in richer surface-deformation information than the traditional methods but also in higher monitoring precision.
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      Subsidence Monitoring Using Lidar and Morton Code Indexing

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4244629
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    contributor authorJianfeng Ao
    contributor authorKan Wu
    contributor authorYongZhi Wang
    contributor authorLiang Li
    date accessioned2017-12-30T13:01:21Z
    date available2017-12-30T13:01:21Z
    date issued2016
    identifier other%28ASCE%29SU.1943-5428.0000166.pdf
    identifier urihttp://138.201.223.254:8080/yetl1/handle/yetl/4244629
    description abstractPoint-based data-acquisition technology in traditional survey engineering does not provide complete data about mining-induced subsidence basins. To overcome these shortcomings, this research applied light detection and ranging (LIDAR) data, obtained with a terrestrial laser scanner (TLS) for monitoring the surface deformation of mining areas, to acquire full data about mining-induced subsidence basins. First, to improve the organization efficiency of LIDAR data, the decimal Morton code–based indexing method was proposed for discrete-grid indexing to organize LIDAR data according to original point coordinates, to avoid the generation of grids without data, and to build a topological relationship among scattered points. Thus, this approach enabled highly efficient access of LIDAR data and restoration of coordinates for each point. In the end, the processed data were applied in engineering practice. The subsidence curves of two sections of the subsidence basin, in both strike and dip directions measured with a high-grade control survey, were compared with the subsidence curves extracted from the LIDAR data. The good coincidence effect suggests that using LIDAR data to build the subsidence basin model can result not only in richer surface-deformation information than the traditional methods but also in higher monitoring precision.
    publisherAmerican Society of Civil Engineers
    titleSubsidence Monitoring Using Lidar and Morton Code Indexing
    typeJournal Paper
    journal volume142
    journal issue1
    journal titleJournal of Surveying Engineering
    identifier doi10.1061/(ASCE)SU.1943-5428.0000166
    page06015002
    treeJournal of Surveying Engineering:;2016:;Volume ( 142 ):;issue: 001
    contenttypeFulltext
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