4.7 Article

Terrestrial laser scanning in forest inventories

期刊

出版社

ELSEVIER
DOI: 10.1016/j.isprsjprs.2016.01.006

关键词

Forest inventory; Point cloud; Terrestrial laser scanning; Mobile laser scanning; Personal laser scanning; Image-based point cloud

资金

  1. Finnish Academy project Centre of Excellence in Laser Scanning Research (CoE-LaSR) [272195]
  2. Finnish Academy project Interaction of Lidar/Radar Beams with Forests Using Mini-UAV and Mobile Forest Tomography [259348]
  3. Finnish Academy project Competence Based Growth Through Integrated Disruptive Technologies of 3D Digitalization, Robotics, Geospatial Information and Image Processing/Computing Point Cloud Ecosystem [293389]
  4. European Community's Seventh Framework Programme ([FP7]) [606971]

向作者/读者索取更多资源

Decision making on forest resources relies on the precise information that is collected using inventory. There are many different kinds of forest inventory techniques that can be applied depending on the goal, scale, resources and the required accuracy. Most of the forest inventories are based on field sample. Therefore, the accuracy of the forest inventories depends on the quality and quantity of the field sample. Conventionally, field sample has been measured using simple tools. When map is required, remote sensing materials are needed. Terrestrial laser scanning (TLS) provides a measurement technique that can acquire millimeter-level of detail from the surrounding area, which allows rapid, automatic and periodical estimates of many important forest inventory attributes. It is expected that TLS will be operationally used in forest inventories as soon as the appropriate software becomes available, best practices become known and general knowledge of these findings becomes more wide spread. Meanwhile, mobile laser scanning, personal laser scanning, and image-based point clouds became capable of capturing similar terrestrial point cloud data as TLS. This paper reviews the advances of applying TLS in forest inventories, discusses its properties with reference to other related techniques and discusses the future prospects of this technique. (C) 2016 The Authors. Published by Elsevier B.V. on behalf of International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licensesiby-nc-nd/11.0/).

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