Paper Info
Title
Forest Data Collection Using Terrestrial Image-Based Point Clouds From a Handheld Camera Compared to Terrestrial and Personal Laser Scanning
Abstract
Stereo images have long been the main practical data source for the high-accuracy retrieval of 3-D information over large areas. However, stereoscopy has been surpassed by laser scanning (LS) techniques in recent years, particularly in forested areas, because the reflection of laser points from object surfaces directly provides 3-D geometric features and because the laser beam has good penetration capacity through forest canopies. In the last few years, image-based point clouds have become a more widely available data source because of advances in matching algorithms and computer hardware. This paper explores the possibility of using consumer cameras for forest field data collection and presents an application of terrestrial image-based point clouds derived from a handheld camera to forest plot inventories. In the experiment, the sample forest plot was photographed in a stop-and-go mode using different routes and camera settings. Five data sets were generated from photographs taken in the field, representing different photographic conditions. The stem detection accuracy ranged between 60% and 84%, and the root-mean-square errors of the estimated diameters at breast height were between 2.98 and 6.79 cm. The performance of image-based point clouds in forest data collection was compared with that of point clouds derived from two LS techniques, i.e., terrestrial LS (the professional level) and personal LS (an emerging technology). The study indicates that the construction of image-based point clouds of forest field data requires only low-cost, low-weight, and easy-to-use equipment and automated data processing. Photographic measurement is easy and relatively fast. The accuracy of tree attribute estimates is close to an acceptable level for forest field inventory but is lower than that achieved with the tested LS techniques.
Year
DOI
Venue
2015
10.1109/TGRS.2015.2417316
IEEE Trans. Geoscience and Remote Sensing
Keywords
Field
DocType
forest inventory,light detection and ranging (lidar),handheld camera,image-based point cloud,laser scanning (ls),point cloud,structure from motion,terrestrial
Structure from motion,Computer vision,Data collection,Automated data processing,Data set,Laser scanning,Stereoscopy,Remote sensing,Forest inventory,Artificial intelligence,Point cloud,Mathematics
Journal
Volume
Issue
ISSN
53
9
0196-2892
Citations 
PageRank 
References 
9
0.72
11
Authors
8
Name
Order
Citations
PageRank
Xinlian Liang119323.72
Yunsheng Wang2545.41
Anttoni Jaakkola334430.30
Antero Kukko448347.44
Harri Kaartinen560863.10
Juha Hyyppä643966.75
Eija Honkavaara722027.92
Jingbin Liu817422.22