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  • 标题:3D Modeling of Individual Trees from LiDAR and Photogrammetric Point Clouds by Explicit Parametric Representations for Green Open Space (GOS) Management
  • 本地全文:下载
  • 作者:Deni Suwardhi ; Kamal Nur Fauzan ; Agung Budi Harto
  • 期刊名称:ISPRS International Journal of Geo-Information
  • 电子版ISSN:2220-9964
  • 出版年度:2022
  • 卷号:11
  • 期号:3
  • 页码:174
  • DOI:10.3390/ijgi11030174
  • 语种:English
  • 出版社:MDPI AG
  • 摘要:The development and management of green open spaces are essential in overcoming environmental problems such as air pollution and urban warming. 3D modeling and biomass calculation are the example efforts in managing green open spaces. In this study, 3D modeling was carried out on point clouds data acquired by the UAV photogrammetry and UAV LiDAR methods. 3D modeling is done explicitly using the point clouds fitting method. This study uses three fitting methods: the spherical fitting method, the ellipsoid fitting method, and the spherical harmonics fitting method. The spherical harmonics fitting method provides the best results and produces an R2 value between 0.324 to 0.945. In this study, Above-Ground Biomass (AGB) calculations were also carried out from the modeling results using three methods with UAV LiDAR and Photogrammetry data. AGB calculation using UAV LiDAR data gives better results than using photogrammetric data. AGB calculation using UAV LiDAR data gives an accuracy of 78% of the field validation results. However, for visualization purposes with a not-too-wide area, a 3D model of photogrammetric data using the spherical harmonics method can be used.
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