Literature DB >> 18365761

Using LiDAR technology in forestry activities.

Abdullah Emin Akay1, Hakan Oğuz, Ismail Rakip Karas, Kazuhiro Aruga.   

Abstract

Managing natural resources in wide-scale areas can be highly time and resource consuming task which requires significant amount of data collection in the field and reduction of the data in the office to provide the necessary information. High performance LiDAR remote sensing technology has recently become an effective tool for use in applications of natural resources. In the field of forestry, the LiDAR measurements of the forested areas can provide high-quality data on three-dimensional characterizations of forest structures. Besides, LiDAR data can be used to provide very high quality and accurate Digital Elevation Model (DEM) for the forested areas. This study presents the progress and opportunities of using LiDAR remote sensing technology in various forestry applications. The results indicate that LiDAR based forest structure data and high-resolution DEMs can be used in wide-scale forestry activities such as stand characterizations, forest inventory and management, fire behaviour modeling, and forest operations.

Mesh:

Year:  2008        PMID: 18365761     DOI: 10.1007/s10661-008-0254-1

Source DB:  PubMed          Journal:  Environ Monit Assess        ISSN: 0167-6369            Impact factor:   2.513


  4 in total

1.  Assessing the influence of topography and canopy structure on Douglas fir throughfall with LiDAR and empirical data in the Santa Cruz mountains, USA.

Authors:  K T Griffith; A G Ponette-González; L M Curran; K C Weathers
Journal:  Environ Monit Assess       Date:  2015-04-18       Impact factor: 2.513

2.  The determination of some stand parameters using SfM-based spatial 3D point cloud in forestry studies: an analysis of data production in pure coniferous young forest stands.

Authors:  Sercan Gülci
Journal:  Environ Monit Assess       Date:  2019-07-13       Impact factor: 2.513

3.  The use of airborne laser scanning to develop a pixel-based stratification for a verified carbon offset project.

Authors:  Jordan Golinkoff; Mark Hanus; Jennifer Carah
Journal:  Carbon Balance Manag       Date:  2011-10-17

4.  A novel smartphone-based activity recognition modeling method for tracked equipment in forest operations.

Authors:  Ryer M Becker; Robert F Keefe
Journal:  PLoS One       Date:  2022-04-06       Impact factor: 3.240

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.