On the public citation graph
A Hybrid Allometric-Machine Learning Model for Crown Base Height Prediction in the Republic of Korea
0 signed · 43 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/ecs2.2934openalex-snapshot
Widespread severe wildfires under climate change lead to increased forest homogeneity in dry mixed‐conifer forests
inferredcites →https://doi.org/10.1007/s10651-023-00590-7openalex-snapshot
Logistic regression versus XGBoost for detecting burned areas using satellite images
inferredcites →https://doi.org/10.1007/s11676-015-0194-xopenalex-snapshot
Modeling frequency distributions of tree height, diameter and crown area by six probability functions for open forests of Quercus persica in Iran
inferredcites →https://doi.org/10.1016/0378-1127(96)03768-1openalex-snapshot
A crown ratio model for Austrian forests
inferredcites →https://doi.org/10.1016/j.biosystemseng.2015.02.013openalex-snapshot
Estimation of Weibull function parameters for modelling tree diameter distribution using least squares and artificial neural networks methods
inferredcites →https://doi.org/10.1016/j.proci.2020.11.006openalex-snapshot
Combustion dynamics of large-scale wildfires
inferredcites →https://doi.org/10.1016/j.rse.2025.114721openalex-snapshot
Spatially continuous mapping of pre-fire fuel characteristics with imaging spectroscopy and lidar for fire emissions modeling
inferredcites →https://doi.org/10.1016/j.scitotenv.2022.157788openalex-snapshot
Exploring characteristics of national forest inventories for integration with global space-based forest biomass data
inferredcites →https://doi.org/10.1016/s0378-1127(97)00155-2openalex-snapshot
Suitability of the Normal, Log-normal and Weibull distributions for fitting diameter distributions of neem plantations in Northern Ghana
inferredcites →https://doi.org/10.1038/s41598-024-71133-8openalex-snapshot
Advancing forest carbon stocks’ mapping using a hierarchical approach with machine learning and satellite imagery
inferredcites →https://doi.org/10.1051/forest:2001118openalex-snapshot
A tree crown ratio prediction equation for eucalypt plantations
inferredcites →https://doi.org/10.1080/01621459.1951.10500769openalex-snapshot
The Kolmogorov-Smirnov Test for Goodness of Fit
inferredcites →https://doi.org/10.1080/21580103.2016.1144541openalex-snapshot
Exploring tree crown spacing and slope interaction effects on fire behavior with a physics-based fire model
inferredcites →https://doi.org/10.1088/2632-2153/ada47eopenalex-snapshot
Deep-learning-based canopy height model generation from sub-meter resolution panchromatic satellite imagery
inferredcites →https://doi.org/10.1109/isit.2008.4595271openalex-snapshot
Kullback-Leibler divergence estimation of continuous distributions
inferredcites →https://doi.org/10.1139/x06-157openalex-snapshot
Estimating canopy fuel characteristics in five conifer stands in the western United States using tree and stand measurements
inferredcites →https://doi.org/10.1139/x77-004openalex-snapshot
Conditions for the start and spread of crown fire
inferredcites →https://doi.org/10.1139/x87-096openalex-snapshot
Compatible crown ratio and crown height models
inferredcites →https://doi.org/10.1145/3514228openalex-snapshot
Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental Systems
inferredcites →https://doi.org/10.1146/annurev-statistics-030718-104938openalex-snapshot
Statistical Aspects of Wasserstein Distances
inferredcites →https://doi.org/10.1186/s40663-020-00226-3openalex-snapshot
Innovative deep learning artificial intelligence applications for predicting relationships between individual tree height and diameter at breast height
inferredcites →https://doi.org/10.1214/aos/1013203451openalex-snapshot
Greedy function approximation: A gradient boosting machine.
inferredcites →https://doi.org/10.1287/isre.2013.0480openalex-snapshot
Research Commentary —Too Big to Fail: Large Samples and the p -Value Problem
inferredcites →https://doi.org/10.1371/journal.pone.0132066openalex-snapshot
A Novel Modelling Approach for Predicting Forest Growth and Yield under Climate Change
inferredcites →https://doi.org/10.14191/atmos.2013.23.4.485openalex-snapshot
Study on Sensitivities and Fire Area Errors in WRF-Fire Simulation to Different Resolution Data Set of Fuel and Terrain, and Surface Wind
inferredcites →https://doi.org/10.14251/crisisonomy.2021.17.6.89openalex-snapshot
Effect of Climate Factors on Fuel Moisture Contents in Forest
inferredcites →https://doi.org/10.1609/aaai.v39i27.35068openalex-snapshot
Hybrid Phenology Modeling for Predicting Temperature Effects on Tree Dormancy
inferredcites →https://doi.org/10.2737/int-gtr-133openalex-snapshot
User's Guide to the Stand Prognosis Model
inferredcites →https://doi.org/10.2737/int-gtr-208openalex-snapshot
Supplement to The User's Guide for The Stand Prognosis Model-version 5.0
inferredcites →https://doi.org/10.2737/int-rp-438openalex-snapshot
Predicting behavior and size of crown fires in the northern Rocky Mountains
inferredcites →https://doi.org/10.3390/f10100859openalex-snapshot
Stand Diameter Distribution Modeling and Prediction Based on Maximum Entropy Principle
inferredcites →https://doi.org/10.3390/f14112126openalex-snapshot
Aerial Imaging-Based Fuel Information Acquisition for Wildfire Research in Northeastern South Korea
inferredcites →https://doi.org/10.3390/f9090555openalex-snapshot
Generalized Nonlinear Mixed-Effects Individual Tree Crown Ratio Models for Norway Spruce and European Beech
inferredcites →https://doi.org/10.3390/fire6080321openalex-snapshot
Vertical and Horizontal Crown Fuel Continuity Influences Group-Scale Ignition and Fuel Consumption
inferredcites →https://doi.org/10.3390/rs3112346openalex-snapshot
Estimating Crown Variables of Individual Trees Using Airborne and Terrestrial Laser Scanners
inferredcites →https://doi.org/10.3390/rs9090940openalex-snapshot
Estimating Forest Structural Parameters Using Canopy Metrics Derived from Airborne LiDAR Data in Subtropical Forests
inferredcites →https://doi.org/10.5194/gchron-5-263-2023openalex-snapshot
Short communication: The Wasserstein distance as a dissimilarity metric for comparing detrital age spectra and other geological distributions
inferredcites →https://doi.org/10.5194/gmd-18-7603-2025openalex-snapshot
PHOREAU v1.0: a new process-based model to predict forest functioning, from tree ecophysiology to forest dynamics and biogeography
inferredcites →https://doi.org/10.5194/nhess-24-3579-2024openalex-snapshot
Where to start with climate-smart forest management? Climatic risk for forest-based mitigation
inferredcites →https://doi.org/10.5424/fs/2020292-16393openalex-snapshot
Artificial intelligence with deep learning algorithms to model relationships between total tree height and diameter at breast height
inferredcites →https://doi.org/10.5558/tfc81133-1openalex-snapshot
Tree crown ratio models for multi-species and multi-layered stands of southeastern British Columbia
inferredcites →https://doi.org/10.7744/kjoas.20160032openalex-snapshot
Brief history of Korean national forest inventory and academic usage
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.