Comparing terrestrial laser scanning and unmanned aerial vehicle structure from motion to assess top of canopy structure in tropical forests

被引:50
作者
Rosca, Sabina [1 ]
Suomalainen, Juha [1 ,2 ]
Bartholomeus, Harm [1 ]
Herold, Martin [1 ]
机构
[1] Wageningen Univ, Lab Geoinformat Sci & Remote Sensing, Droevendaalsesteeg 3, NL-6708 PB Wageningen, Netherlands
[2] Natl Land Survey Finland, Finnish Geospatial Res Inst, Geodeetinrinne 2, Masala 02430, Finland
关键词
terrestrial LiDAR; terrestrial laser scanning; structure from motion; unmanned aerial vehicle; top of canopy; tropical forest; SMALL-FOOTPRINT LIDAR; TREE HEIGHT; ABOVEGROUND BIOMASS; AIRBORNE LIDAR; POINT CLOUDS; SYSTEM; STANDS; PARAMETERS; INVENTORY; ACCURACY;
D O I
10.1098/rsfs.2017.0038
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Terrestrial laser scanning (TLS) and unmanned aerial vehicles (UAVs) equipped with digital cameras have attracted much attention from the forestry community as potential tools for forest inventories and forest monitoring. This research fills a knowledge gap about the viability and dissimilarities of using these technologies for measuring the top of canopy structure in tropical forests. In an empirical study with data acquired in a Guyanese tropical forest, we assessed the differences between top of canopy models (TCMs) derived from TLS measurements and from UAV imagery, processed using structure from motion. Firstly, canopy gaps lead to differences in TCMs derived from TLS and UAVs. UAV TCMs overestimate canopy height in gap areas and often fail to represent smaller gaps altogether. Secondly, it was demonstrated that forest change caused by logging can be detected by both TLS and UAV TCMs, although it is better depicted by the TLS. Thirdly, this research shows that both TLS and UAVTCMs are sensitive to the small variations in sensor positions during data collection. TCMs rendered from UAV data acquired over the same area at different moments are more similar (RMSE 0.11-0.63 m for tree height, and 0.14-3.05 m for gap areas) than those rendered from TLS data (RMSE 0.21-1.21 m for trees, and 1.02-2.48 m for gaps). This study provides support for a more informed decision for choosing between TLS and UAV TCMs to assess top of canopy in a tropical forest by advancing our understanding on: (i) how these technologies capture the top of the canopy, (ii) why their ability to reproduce the same model varies over repeated surveying sessions and (iii) general considerations such as the area coverage, costs, fieldwork time and processing requirements needed.
引用
收藏
页数:11
相关论文
共 52 条
  • [1] Detection of millimetric deformation using a terrestrial laser scanner: experiment and application to a rockfall event
    Abellan, A.
    Jaboyedoff, M.
    Oppikofer, T.
    Vilaplana, J. M.
    [J]. NATURAL HAZARDS AND EARTH SYSTEM SCIENCES, 2009, 9 (02) : 365 - 372
  • [2] A universal airborne LiDAR approach for tropical forest carbon mapping
    Asner, Gregory P.
    Mascaro, Joseph
    Muller-Landau, Helene C.
    Vieilledent, Ghislain
    Vaudry, Romuald
    Rasamoelina, Maminiaina
    Hall, Jefferson S.
    van Breugel, Michiel
    [J]. OECOLOGIA, 2012, 168 (04) : 1147 - 1160
  • [3] Detection and analysis of individual leaf-off tree crowns in small footprint, high sampling density lidar data from the eastern deciduous forest in North America
    Brandtberg, T
    Warner, TA
    Landenberger, RE
    McGraw, JB
    [J]. REMOTE SENSING OF ENVIRONMENT, 2003, 85 (03) : 290 - 303
  • [4] Creating a virtual tropical forest from three-dimensional aerial imagery to estimate carbon stocks
    Brown, S
    Pearson, T
    Slaymaker, D
    Ambagis, S
    Moore, N
    Novelo, D
    Sabido, W
    [J]. ECOLOGICAL APPLICATIONS, 2005, 15 (03) : 1083 - 1095
  • [5] Estimation of tropical rain forest aboveground biomass with small-footprint lidar and hyperspectral sensors
    Clark, Matthew L.
    Roberts, Dar A.
    Ewel, John J.
    Clark, David B.
    [J]. REMOTE SENSING OF ENVIRONMENT, 2011, 115 (11) : 2931 - 2942
  • [6] Small-footprint lidar estimation of sub-canopy elevation and tree height in a tropical rain forest landscape
    Clark, ML
    Clark, DB
    Roberts, DA
    [J]. REMOTE SENSING OF ENVIRONMENT, 2004, 91 (01) : 68 - 89
  • [7] High spatial resolution three-dimensional mapping of vegetation spectral dynamics using computer vision
    Dandois, Jonathan P.
    Ellis, Erle C.
    [J]. REMOTE SENSING OF ENVIRONMENT, 2013, 136 : 259 - 276
  • [8] Estimation of above-ground biomass of large tropical trees with terrestrial LiDAR
    de Tanago, Jose Gonzalez
    Lau, Alvaro
    Bartholomeus, Harm
    Herold, Martin
    Avitabile, Valerio
    Raumonen, Pasi
    Martius, Christopher
    Goodman, Rosa C.
    Disney, Mathias
    Manuri, Solichin
    Burt, Andrew
    Calders, Kim
    [J]. METHODS IN ECOLOGY AND EVOLUTION, 2018, 9 (02): : 223 - 234
  • [9] Retrieval of tropical forest structure characteristics from bi-directional reflectance of SPOT images
    de Wasseige, C
    Defourny, P
    [J]. REMOTE SENSING OF ENVIRONMENT, 2002, 83 (03) : 362 - 375
  • [10] Experimental Hydrology Wiki, 2010, TOP TERR LAS SCANN R