Detection of coarse woody debris using airborne light detection and ranging (LiDAR)

2019 ◽  
Vol 433 ◽  
pp. 678-689 ◽  
Author(s):  
Michael J. Joyce ◽  
John D. Erb ◽  
Barry A. Sampson ◽  
Ron A. Moen
Keyword(s):  
Coarse Woody Debris ◽  
Woody Debris ◽  
Light Detection And Ranging ◽  
Light Detection

Decay classes of coarse woody debris in a lowland Dipterocarp forest: implications for volume, density, and carbon estimates

Biotropica ◽  
2021 ◽  
Author(s):  
Ekaterina Shorohova ◽  
Ekaterina Kapitsa ◽  
Andrey Kuznetsov ◽  
Svetlana Kuznetsova ◽  
Valentin Lopes de Gerenuy ◽  
...  
Keyword(s):  
Coarse Woody Debris ◽  
Woody Debris ◽  
Volume Density ◽  
Dipterocarp Forest ◽  
Lowland Dipterocarp Forest

scholarly journals Forest stand structure and coarse woody debris determine the biodiversity of beetle communities in Mediterranean mountain beech forests

2021 ◽  
pp. e01637
Author(s):  
Francesco Parisi ◽  
Michele Innangi ◽  
Roberto Tognetti ◽  
Fabio Lombardi ◽  
Gherardo Chirici ◽  
...  
Keyword(s):  
Coarse Woody Debris ◽  
Stand Structure ◽  
Woody Debris ◽  
Forest Stand ◽  
Beech Forests ◽  
Forest Stand Structure

scholarly journals Assessing Coarse Woody Debris Nutrient Dynamics in Managed Northern Hardwood Forests Using a Matrix Transition Model

Ecosystems ◽  
2019 ◽  
Vol 23 (3) ◽  
pp. 541-554
Author(s):  
Adam Gorgolewski ◽  
Philip Rudz ◽  
Trevor Jones ◽  
Nathan Basiliko ◽  
John Caspersen
Keyword(s):  
Coarse Woody Debris ◽  
Nutrient Dynamics ◽  
Woody Debris ◽  
Hardwood Forests ◽  
Transition Model ◽  
Northern Hardwood Forests ◽  
Northern Hardwood

scholarly journals Using Airborne Light Detection and Ranging (LIDAR) to Characterize Forest Stand Condition on the Kenai Peninsula of Alaska

2009 ◽  
Vol 24 (2) ◽  
pp. 95-102 ◽  
Author(s):  
Hans-Erik Andersen
Keyword(s):  
Forest Inventory ◽  
Laser Scanning ◽  
Three Dimensional ◽  
Grid Cell ◽  
Forest Stand ◽  
Light Detection And Ranging ◽  
Inventory Analysis ◽  
Light Detection ◽  
Individual Tree ◽  
Kenai Peninsula

Abstract Airborne laser scanning (also known as light detection and ranging or LIDAR) data were used to estimate three fundamental forest stand condition classes (forest stand size, land cover type, and canopy closure) at 32 Forest Inventory Analysis (FIA) plots distributed over the Kenai Peninsula of Alaska. Individual tree crown segment attributes (height, area, and species type) were derived from the three-dimensional LIDAR point cloud, LIDAR-based canopy height models, and LIDAR return intensity information. The LIDAR-based crown segment and canopy cover information was then used to estimate condition classes at each 10-m grid cell on a 300 × 300-m area surrounding each FIA plot. A quantitative comparison of the LIDAR- and field-based condition classifications at the subplot centers indicates that LIDAR has potential as a useful sampling tool in an operational forest inventory program.

Precision and shortcomings of yaw error estimation using spinner-based light detection and ranging

Wind Energy ◽  
2012 ◽  
Vol 16 (3) ◽  
pp. 353-366 ◽  
Author(s):  
Knud A. Kragh ◽  
Morten H. Hansen ◽  
Torben Mikkelsen
Keyword(s):  
Error Estimation ◽  
Light Detection And Ranging ◽  
Light Detection

Hybrid Integrated Silicon NitridePolymer Optical Phased Array for Efficient Light Detection and Ranging

2021 ◽  
pp. 1-1
Author(s):  
Chul-Soon Im ◽  
Sung-Moon Kim ◽  
Kyeong-Pyo Lee ◽  
Seong-Hyeon Ju ◽  
Jung-Ho Hong ◽  
...  
Keyword(s):  
Phased Array ◽  
Light Detection And Ranging ◽  
Light Detection ◽  
Optical Phased Array
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