Predicting black spruce fuel characteristics with Airborne Laser Scanning (ALS)
Published 2021 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Predicting black spruce fuel characteristics with Airborne Laser Scanning (ALS)
Authors
Keywords
-
Journal
INTERNATIONAL JOURNAL OF WILDLAND FIRE
Volume 31, Issue 2, Pages 124-135
Publisher
CSIRO Publishing
Online
2021-12-14
DOI
10.1071/wf21004
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Early Regeneration Dynamics of Pure Black Spruce and Aspen Forests after Wildfire in Boreal Alberta, Canada
- (2020) Stephanie A. Jean et al. Forests
- Multispectral LiDAR-Based Estimation of Surface Fuel Load in a Dense Coniferous Forest
- (2020) Alexandra Stefanidou et al. Remote Sensing
- Prediction of Forest Canopy and Surface Fuels from Lidar and Satellite Time Series Data in a Bark Beetle-Affected Forest
- (2017) Benjamin Bright et al. Forests
- Remote Sensing Technologies for Enhancing Forest Inventories: A Review
- (2016) Joanne C. White et al. CANADIAN JOURNAL OF REMOTE SENSING
- Individual tree crown delineation using localized contour tree method and airborne LiDAR data in coniferous forests
- (2016) Bin Wu et al. International Journal of Applied Earth Observation and Geoinformation
- Effects of forest structure and airborne laser scanning point cloud density on 3D delineation of individual tree crowns
- (2016) Kaja Kandare et al. European Journal of Remote Sensing
- Remote Sensing Technologies for Enhancing Forest Inventories: A Review
- (2016) Joanne C. White et al. CANADIAN JOURNAL OF REMOTE SENSING
- Fuel load, structure, and potential fire behaviour in black spruce bogs
- (2015) D.C. Johnston et al. CANADIAN JOURNAL OF FOREST RESEARCH
- The Flammability of Forest and Woodland Litter: a Synthesis
- (2015) J. Morgan Varner et al. Current Forestry Reports
- Regularization Paths for Generalized Linear Models via Coordinate Descent
- (2015) Jerome Friedman et al. Journal of Statistical Software
- Tables for Estimating Canopy Fuel Characteristics from Stand Variables in Four Interior West Conifer Forest Types
- (2014) Martin E. Alexander et al. FOREST SCIENCE
- A best practices guide for generating forest inventory attributes from airborne laser scanning data using an area-based approach
- (2014) Joanne C. White et al. FORESTRY CHRONICLE
- Predicting wood quantity and quality attributes of balsam fir and black spruce using airborne laser scanner data
- (2013) J. E. Luther et al. FORESTRY
- Estimation of forest structure and canopy fuel parameters from small-footprint full-waveform LiDAR data
- (2013) Txomin Hermosilla et al. INTERNATIONAL JOURNAL OF WILDLAND FIRE
- Mapping fire risk in the Model Forest of Urbión (Spain) based on airborne LiDAR measurements
- (2012) José-Ramón González-Olabarria et al. FOREST ECOLOGY AND MANAGEMENT
- LiDAR Sampling Density for Forest Resource Inventories in Ontario, Canada
- (2012) Paul Treitz et al. Remote Sensing
- Comparative testing of single-tree detection algorithms under different types of forest
- (2011) J. Vauhkonen et al. FORESTRY
- Combination of individual tree detection and area-based approach in imputation of forest variables using airborne laser data
- (2011) Mikko Vastaranta et al. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
- Fusion of LiDAR and imagery for estimating forest canopy fuels
- (2010) Todd L. Erdody et al. REMOTE SENSING OF ENVIRONMENT
- Three-dimensional canopy fuel loading predicted using upward and downward sensing LiDAR systems
- (2010) Nicholas S. Skowronski et al. REMOTE SENSING OF ENVIRONMENT
- A voxel-based lidar method for estimating crown base height for deciduous and pine trees
- (2007) Sorin C. Popescu et al. REMOTE SENSING OF ENVIRONMENT
Create your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create NowAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started