The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLII-4/W9
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W9, 123–127, 2018
https://doi.org/10.5194/isprs-archives-XLII-4-W9-123-2018
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W9, 123–127, 2018
https://doi.org/10.5194/isprs-archives-XLII-4-W9-123-2018

  30 Oct 2018

30 Oct 2018

UNMANNED AERIAL VEHICLE (UAV) SURVEY-ASSISTED 3D MANGROVE TREE MODELING

G. A. Domingo1, A. R. C. Claridades1,2, and M. E. A. Tupas1,2 G. A. Domingo et al.
  • 1IAMBlueCECAM Program Project 9: WebGIS for Mapping, Supporting Decision-making, and Promoting Ecological Services of Blue Carbon Ecosystems, University of the Philippines, Diliman, Quezon City 1101, Philippines
  • 2Department of Geodetic Engineering, University of the Philippines, Diliman, Philippines

Keywords: Mangroves, 3D Visualization, 3D Modeling, Unmanned Aerial Vehicle, Assistive Modeling

Abstract. 3D visualization is a tool that supports geospatial analysis through the application of scientific information. It enhances the quality of standard photography and can be used in many applications. Through this study, a 3D mangrove tree model is generated, as assisted by a tree crown derived from UAV images. The researchers explored different platforms namely: MeshLab, SketchUp (with 3D Tree Maker extension), and Clara.io, to come up with a more realistic three-dimensional (3D) model of a mangrove tree. From an Unmanned Aerial Vehicle (UAV) derived Digital Surface Model (DSM), an isolated tree crown was selected which was then used as an assisting tool in creating the final 3D mangrove tree model. A default tree object was modified according to the characteristics as described by the DSM. Additional branches and leaves were added to the existing tree object, and its shape was modified to conform to the tree crown. The resulting model may be used to more accurately depict objects in the area to be visualized, however an automation procedure is recommended for an easier and more effective generation of multiple tree models expected in an area.