Related references
Note: Only part of the references are listed.Detecting Dead Standing Eucalypt Trees from Voxelised Full-Waveform Lidar Using Multi-Scale 3D-Windows for Tackling Height and Size Variations
Milto Miltiadou et al.
FORESTS (2020)
Combined Impact of Sample Size and Modeling Approaches for Predicting Stem Volume in Eucalyptus spp. Forest Plantations Using Field and LiDAR Data
Vanessa Sousa da Silva et al.
REMOTE SENSING (2020)
Comparison of Statistical Modelling Approaches for Estimating Tropical Forest Aboveground Biomass Stock and Reporting Their Changes in Low-Intensity Logging Areas Using Multi-Temporal LiDAR Data
Franciel Eduardo Rex et al.
REMOTE SENSING (2020)
ARTIFICIAL NEURAL NETWORKS APPLIED IN FOREST BIOMETRICS AND MODELING: STATE OF THE ART (JANUARY/2007 TO JULY/2018)
Flavio Chiarello et al.
CERNE (2019)
Modelling vegetation understory cover using LiDAR metrics
Lisa A. Venier et al.
PLOS ONE (2019)
Comparative Performances of Airborne LiDAR Height and Intensity Data for Leaf Area Index Estimation
Shezhou Luo et al.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING (2018)
Important LiDAR metrics for discriminating forest tree species in Central Europe
Yifang Shi et al.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2018)
Artificial neural networks: Modeling tree survival and mortality in the Atlantic Forest biome in Brazil
Samuel Jose Silva Soares da Rocha et al.
SCIENCE OF THE TOTAL ENVIRONMENT (2018)
Modeling of stem form and volume through machine learning
Ana B. Schikowski et al.
ANAIS DA ACADEMIA BRASILEIRA DE CIENCIAS (2018)
Successional stages and their evolution in tropical forests using multi-temporal photogrammetric surface models and superpixels
Adilson Berveglieri et al.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2018)
Predicting Stem Total and Assortment Volumes in an Industrial Pinus taeda L. Forest Plantation Using Airborne Laser Scanning Data and Random Forest
Carlos Alberto Silva et al.
FORESTS (2017)
Comparing Modeling Methods for Predicting Forest Attributes Using LiDAR Metrics and Ground Measurements
Joonghoon Shin et al.
CANADIAN JOURNAL OF REMOTE SENSING (2016)
Prognosis on the diameter of individual trees on the eastern region of the amazon using artificial neural networks
Leonardo Pequeno Reis et al.
FOREST ECOLOGY AND MANAGEMENT (2016)
Identification of Successional Stages and Cover Changes of Tropical Forest Based on Digital Surface Model Analysis
Adilson Berveglieri et al.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING (2016)
Comparison of small-footprint discrete return and full waveform airborne lidar data for estimating multiple forest variables
Matthew J. Sumnall et al.
REMOTE SENSING OF ENVIRONMENT (2016)
Comparing Modeling Methods for Predicting Forest Attributes Using LiDAR Metrics and Ground Measurements
Joonghoon Shin et al.
CANADIAN JOURNAL OF REMOTE SENSING (2016)
A performance comparison of machine learning methods to estimate the fast-growing forest plantation yield based on laser scanning metrics
Eric Bastos Goergens et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2015)
A comparison of machine learning regression techniques for LiDAR-derived estimation of forest variables
J. Garcia-Gutierrez et al.
NEUROCOMPUTING (2015)
Habitat fragmentation and its lasting impact on Earth's ecosystems
Nick M. Haddad et al.
SCIENCE ADVANCES (2015)
A Review of Methods for Mapping and Prediction of Inventory Attributes for Operational Forest Management
Kimberley D. Brosofske et al.
FOREST SCIENCE (2014)
INFLUENCE OF THE ARCHITECTURE IN ESTIMATED VOLUME OF INDIVIDUAL TREES USING ARTIFICIAL NEURAL NETWORKS
Eric Bastos Gorgens et al.
REVISTA ARVORE (2014)
Sensitivity Analysis of 3D Individual Tree Detection from LiDAR Point Clouds of Temperate Forests
Wei Yao et al.
FORESTS (2014)
Support vector machines for tree species identification using LiDAR-derived structure and intensity variables
Zhenyu Zhang et al.
GEOCARTO INTERNATIONAL (2013)
Quantifying aboveground forest carbon pools and fluxes from repeat LiDAR surveys
Andrew T. Hudak et al.
REMOTE SENSING OF ENVIRONMENT (2012)
Forest structure modeling with combined airborne hyperspectral and LiDAR data
Hooman Latifi et al.
REMOTE SENSING OF ENVIRONMENT (2012)
Accuracy of small footprint airborne LiDAR in its predictions of tropical moist forest stand structure
G. Vincent et al.
REMOTE SENSING OF ENVIRONMENT (2012)
Advances in Forest Inventory Using Airborne Laser Scanning
Juha Hyyppa et al.
REMOTE SENSING (2012)
Support Vector Regression for the Estimation of Forest Stand Parameters Using Airborne Laser Scanning
Jean-Matthieu Monnet et al.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS (2011)
Predicting individual tree attributes from airborne laser point clouds based on the random forests technique
Xiaowei Yu et al.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2011)
Distribution and Endemism of Angiosperms in the Atlantic Forest
Marcio de Souza Werneck et al.
NATUREZA & CONSERVACAO (2011)
Dynamic Range-based Intensity Normalization for Airborne, Discrete Return Lidar Data of Forest Canopies
Demetrios Gatziolis
PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING (2011)
Characterizing forest canopy structure with lidar composite metrics and machine learning
Kaiguang Zhao et al.
REMOTE SENSING OF ENVIRONMENT (2011)
Neural Networks for the Prediction of Species-Specific Plot Volumes Using Airborne Laser Scanning and Aerial Photographs
Harri Niska et al.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (2010)
Principal component analysis
Herve Abdi et al.
WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL STATISTICS (2010)
The Brazilian Atlantic Forest: How much is left, and how is the remaining forest distributed? Implications for conservation
Milton Cezar Ribeiro et al.
BIOLOGICAL CONSERVATION (2009)
Characterizing forest succession with lidar data: An evaluation for the Inland Northwest, USA
Michael J. Falkowski et al.
REMOTE SENSING OF ENVIRONMENT (2009)
Review of plant biogeographic studies in Brazil
Pedro Fiaschi et al.
JOURNAL OF SYSTEMATICS AND EVOLUTION (2009)
Estimates of forest biomass in the Brazilian Amazon: New allometric equations and adjustments to biomass from wood-volume inventories
Euler Melo Nogueira et al.
FOREST ECOLOGY AND MANAGEMENT (2008)
Predicting forest stand variables from LiDAR data in the Great Lakes - St. Lawrence forest of Ontario
M. Woods et al.
FORESTRY CHRONICLE (2008)
Assessment of the influence of flying altitude and scan angle on biophysical vegetation products derived from airborne laser scanning
F. Morsdorf et al.
INTERNATIONAL JOURNAL OF REMOTE SENSING (2008)
Building Predictive Models in R Using the caret Package
Max Kuhn
JOURNAL OF STATISTICAL SOFTWARE (2008)
Remote sensing of species mixtures in conifer plantations using LiDAR height and intensity data
Daniel N. M. Donoghue et al.
REMOTE SENSING OF ENVIRONMENT (2007)
Modelling the known and unknown plant biodiversity of the Amazon Basin
Michael J. G. Hopkins
JOURNAL OF BIOGEOGRAPHY (2007)
The influence of flying altitude, beam divergence, and pulse repetition frequency on laser pulse return intensity and canopy frequency distribution
Chris Hopkinson
CANADIAN JOURNAL OF REMOTE SENSING (2007)
Volume and biomass of trees in central Amazonia: influence of irregularly shaped and hollow trunks
Euler Melo Nogueira et al.
FOREST ECOLOGY AND MANAGEMENT (2006)
Practical large-scale forest stand inventory using a small-footprint airborne scanning laser
E Næsset
SCANDINAVIAN JOURNAL OF FOREST RESEARCH (2004)
Effects of different flying altitudes on biophysical stand properties estimated from canopy height and density measured with a small-footprint airborne scanning laser
E Næsset
REMOTE SENSING OF ENVIRONMENT (2004)
Predicting forest stand characteristics with airborne scanning laser using a practical two-stage procedure and field data
E Næsset
REMOTE SENSING OF ENVIRONMENT (2002)
An assessment of support vector machines for land cover classification
C Huang et al.
INTERNATIONAL JOURNAL OF REMOTE SENSING (2002)
Biodiversity hotspots for conservation priorities
N Myers et al.
NATURE (2000)