Methods for variable selection in LiDAR-assisted forest inventories

No abstract is available for this paper.

• Publication year

  2017

• Venue

  Forestry

• Publication date

  Unknown publication date

• Fields of study

  Mathematics, Engineering, Environmental Science

• Identifiers
  DOI 10.1093/FORESTRY/CPW041
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Neural networks in data mining

  2018cited by this paper
• Comparing echo-based and canopy height model-based metrics for enhancing estimation of forest aboveground biomass in a model-assisted framework

  2016cited by this paper
• A general method for assessing the effects of uncertainty in individual-tree volume model predictions on large-area volume estimates with a subtropical forest illustration

  2015influential reference
• Comparison of uncertainty in per unit area estimates of aboveground biomass for two selected model sets

  2015cited by this paper
• Effects of uncertainty in model predictions of individual tree volume on large area volume estimates

  2014cited by this paper
• Estimation for inaccessible, non-sampled forest areas using model-based inference and remotely sensed auxiliary information

  2014cited by this paper
• Sample-Based Estimation of Greenhouse Gas Emissions From Forests—A New Approach to Account for Both Sampling and Model Errors

  2014cited by this paper
• Evolutionary feature selection to estimate forest stand variables using LiDAR

  2014cited by this paper
• Quantifying the Model-Related Variability of Biomass Stock and Change Estimates in the Norwegian National Forest Inventory

  2014cited by this paper
• Effects of Measurement Errors on Individual Tree Stem Volume Estimates for the Austrian National Forest Inventory

  2014cited by this paper
• A critical review of forest biomass estimation models, common mistakes and corrective measures

  2014cited by this paper
• Above-Ground Biomass and Biomass Components Estimation Using LiDAR Data in a Coniferous Forest

  2013cited by this paper
• Impiego di dati lidar di pubblica disponibilità per il monitoraggio forestale a grande e piccola scala: il progetto ITALID

  2013cited by this paper
• Inference for lidar-assisted estimation of forest growing stock volume

  2013cited by this paper
• How did we get here? An early history of forestry lidar1

  2013cited by this paper
• Estimation of forest biomass by means of genetic algorithm-based optimization of airborne laser scanning and digital aerial photograph features

  2013cited by this paper
• Accuracy and Precision for Remote Sensing Applications of Nonlinear Model-Based Inference

  2013cited by this paper
• A new variable selection approach using Random Forests

  2013cited by this paper
• Allometric equation choice impacts lidar-based forest biomass estimates: A case study from the Sierra National Forest, CA

  2012cited by this paper
• Aboveground Forest Biomass Estimation with Landsat and LiDAR Data and Uncertainty Analysis of the Estimates

  2012cited by this paper
• Assessing the accuracy of regional LiDAR-based biomass estimation using a simulation approach

  2012cited by this paper
• Estimating above-ground biomass in young forests with airborne laser scanning

  2011cited by this paper
• Measuring forest structure and biomass in New England forest stands using Echidna ground-based lidar

  2011cited by this paper
• Measuring Effective Leaf Area Index, Foliage Profile, and Stand Height in New England Forest Stands Using a Full-Waveform Ground-Based Lidar

  2011cited by this paper
• Non-parametric prediction and mapping of standing timber volume and biomass in a temperate forest: application of multiple optical/LiDAR-derived predictors

  2010cited by this paper
• Regression model selection using genetic algorithms

  2010cited by this paper
• Using remotely sensed data to construct and assess forest attribute maps and related spatial products

  2010cited by this paper
• National Forest Inventories : pathways for common reporting

  2010cited by this paper
• Assessing general relationships between aboveground biomass and vegetation structure parameters for improved carbon estimate from lidar remote sensing

  2009cited by this paper
• Overfitting cautious selection of classifier ensembles with genetic algorithms

  2009cited by this paper
• Nonparametric and Semiparametric Estimation in Complex Surveys

  2009cited by this paper
• BMC Bioinformatics BioMed Central Methodology article Conditional variable importance for random forests

  2008cited by this paper
• An approach to estimate carbon stocks change in forest carbon pools under the UNFCCC: the Italian case

  2008cited by this paper
• Data combination and feature selection for multi-source forest inventory

  2008cited by this paper
• BMC Bioinformatics BioMed Central Methodology article

  2007cited by this paper
• Development of total aboveground volume equations for seven important forest tree species in France

  2006cited by this paper
• Variable Selection Using Random Forests

  2006cited by this paper
• Isolating individual trees in a savanna woodland using small footprint lidar data

  2006cited by this paper
• Global biomass mapping for an improved understanding of the CO2 balance—the Earth observation mission Carbon-3D

  2005cited by this paper
• Biomass and stem volume equations for tree species in Europe

  2005cited by this paper
• Tree allometry and improved estimation of carbon stocks and balance in tropical forests

  2005cited by this paper
• Data Mining And Knowledge Discovery Handbook

  2005cited by this paper
• The canopy surface and stand development: assessing forest canopy structure and complexity with near-surface altimetry

  2004cited by this paper
• Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis

  2003cited by this paper
• The Elements of Statistical Learning

  2003influential reference
• Penalized Spline Model-Based Estimation of the Finite Populations Total from Probability-Proportional-to-Size Samples

  2003cited by this paper
• Measuring carbon in forests: current status and future challenges.

  2002cited by this paper
• Use of Genetic Algorithms to select Input Variables in Artificial Neural Network Models for the Prediction of Benthic Macroinvertebrates

  2002cited by this paper
• Predicting forest stand characteristics with airborne scanning laser using a practical two-stage procedure and field data

  2002influential reference
• Random Forests

  2001cited by this paper
• A genetic algorithm to select variables in logistic regression: example in the domain of myocardial infarction

  1999cited by this paper
• Model Assisted Survey Sampling

  1997cited by this paper
• Evaluating forest Growth Models

  1997cited by this paper
• Genetic algorithms as a method for variable selection in multiple linear regression and partial least squares regression, with applications to pyrolysis mass spectrometry

  1997influential reference
• Feature Subset Selection Using the Wrapper Method: Overfitting and Dynamic Search Space Topology

  1995cited by this paper
• Model Comparisons and R 2

  1994cited by this paper
• Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence, by John H. Holland MIT Press (Bradford Books), Cambridge, Mass., 1992, xiv+211 pp. (Paperback £13.50, cloth £26.95)

  1993cited by this paper
• Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence

  1992cited by this paper
• Evaluation of weighted regression and sample size in developing a taper model for loblolly pine

  1992cited by this paper
• Estimating forest biomass and volume using airborne laser data

  1988cited by this paper
• Genetic algorithms and Machine Learning

  1988cited by this paper
• Inventario forestale nazionale italiano. Tavole di cubatura a doppia entrata

  1984cited by this paper
• An Evaluation of Model-Dependent and Probability-Sampling Inferences in Sample Surveys

  1983cited by this paper
• Johnson: computers and intractability: a guide to the theory of np- completeness (freeman

  1979cited by this paper

• kNN - Bagging NFI, GEDI, Sentinel-2 and Sentinel-1 data to produce estimates of forest volumes

  2025cites this paper
• Effects of model-overfit on model-assisted forest inventory in boreal forests with remote sensing data

  2024cites this paper
• Estimating Forest Variables for Major Commercial Timber Plantations in Northern Spain Using Sentinel-2 and Ancillary Data

  2024cites this paper
• A Methodological Framework for Mapping Canopy Cover Using ICESat-2 in the Southern USA

  2023cites this paper
• Effects of lidar coverage and field plot data numerosity on forest growing stock volume estimation

  2022cites this paper
• Sampling and Estimation Documentation for the Enhanced Forest Inventory and Analysis Program

  2022cites this paper
• Multisource forest inventories: A model-based approach using k-NN to reconcile forest attributes statistics and map products

  2022cites this paper
• Effects of tree spacing and thinning on root reinforcement in mountain forests of the European Southern Alps

  2021cites this paper
• A Comparison of Model-Assisted Estimators, With and Without Data-Driven Transformations of Auxiliary Variables, With Application to Forest Inventory

  2021influential citation
• Predicting Douglas-fir knot size in the stand: a random forest model based on CT and field measurements

  2021cites this paper
• The Effect of Forest Mask Quality in the Wall-to-Wall Estimation of Growing Stock Volume

  2021cites this paper
• A Tutorial on Model-Assisted Estimation with Application to Forest Inventory

  2020cites this paper
• Wall-to-wall spatial prediction of growing stock volume based on Italian National Forest Inventory plots and remotely sensed data

  2020cites this paper
• The Role of Improved Ground Positioning and Forest Structural Complexity When Performing Forest Inventory Using Airborne Laser Scanning

  2020cites this paper
• Estimating Stem Volume in Eucalyptus Plantations Using Airborne LiDAR: A Comparison of Area- and Individual Tree-Based Approaches

  2020cites this paper
• Assessment of UAV photogrammetric DTM-independent variables for modelling and mapping forest structural indices in mixed temperate forests

  2020cites this paper
• A Model-Based Volume Estimator that Accounts for Both Land Cover Misclassification and Model Prediction Uncertainty

  2020cites this paper
• Comparison of photogrammetric canopy models from archived and made-to-order aerial imagery in forest inventory

  2020cites this paper
• A Comparison of Standard Modeling Techniques Using Digital Aerial Imagery with National Elevation Datasets and Airborne LiDAR to Predict Size and Density Forest Metrics in the Sapphire Mountains MT, USA

  2019cites this paper
• Increasing Precision for French Forest Inventory Estimates using the k-NN Technique with Optical and Photogrammetric Data and Model-Assisted Estimators

  2019cites this paper
• An improved polynomial-based nonlinear variable importance measure and its application to degradation assessment for high-voltage transformer under imbalance data

  2019cites this paper
• Integration of National Forest Inventory and Nationwide Airborne Laser Scanning Data to Improve Forest Yield Predictions in North-Western Spain

  2019cites this paper
• Using Tree Detection Based on Airborne Laser Scanning to Improve Forest Inventory Considering Edge Effects and the Co-Registration Factor

  2019cites this paper
• Forest Site and Type Variability in ALS-Based Forest Resource Inventory Attribute Predictions over Three Ontario Forest Sites

  2019cites this paper
• Potential of remote sensing-based forest attribute models for harmonising large-scale forest inventories on regional level: a case study in Southwest Germany

  2019cites this paper
• Assessing the robustness of variable selection methods when accounting for co-registration errors in the estimation of forest biophysical and ecological attributes

  2019cites this paper
• Assessment of Classifiers and Remote Sensing Features of Hyperspectral Imagery and Stereo-Photogrammetric Point Clouds for Recognition of Tree Species in a Forest Area of High Species Diversity

  2018cites this paper
• Comparison of estimators and feature selection procedures in forest inventory based on airborne laser scanning and digital aerial imagery

  2018cites this paper
• Hyperspectral UAV-imagery and photogrammetric canopy height model in estimating forest stand variables

  2017cites this paper
• Evaluating Site-Specific and Generic Spatial Models of Aboveground Forest Biomass Based on Landsat Time-Series and LiDAR Strip Samples in the Eastern USA

  2017cites this paper
• Individuazione e correzione di outlier nei dati raster LiDAR provenienti dal Geoportale Nazionale e produzione di un CHM idoneo alla stima delle provvigioni legnose della Calabria

  2017cites this paper
• Using Landsat Time-Series and LiDAR to Inform Aboveground Forest Biomass Baselines in Northern Minnesota, USA

  2017cites this paper