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Simulating Sustainable Forest Management Practices Using Crown Attributes: Insights for Araucaria angustifolia Trees in Southern Brazil
César Augusto Guimarães Finger, Emanuel Arnoni Costa, André Felipe Hess, Veraldo Liesenberg and Polyanna da Conceição Bispo Forests 14(7) 1285 (2023) https://doi.org/10.3390/f14071285
Compatible Biomass Model with Measurement Error Using Airborne LiDAR Data
Xingjing Chen, Dongbo Xie, Zhuang Zhang, Ram P. Sharma, Qiao Chen, Qingwang Liu and Liyong Fu Remote Sensing 15(14) 3546 (2023) https://doi.org/10.3390/rs15143546
Developing nonlinear additive tree crown width models based on decomposed competition index and tree variables
Siyu Qiu, Peiwen Gao, Lei Pan, Lai Zhou, Ruiting Liang, Yujun Sun and Yifu Wang Journal of Forestry Research 34(5) 1407 (2023) https://doi.org/10.1007/s11676-022-01576-0
Using machine learning to identify urban forest crown bounding boxes (CBB): Exploring a new method to develop urban forest policy
Marco Amati, Johann Tiede, Qian (Chayn) Sun, Kaveh Deilami, Joe Hurley, Andrew Fox and Julie Dickson Urban Forestry & Urban Greening 85 127943 (2023) https://doi.org/10.1016/j.ufug.2023.127943
Using Machine Learning to Identify Urban Forest Crown Bounding Boxes (Cbb): A Fit for Purpose Test of Future Urban Sustainability?
Marco Amati, Johann Tiede, Qian Chayn Sun, Kaveh Deilami, Joe Hurley, Andrew Fox and Julie Dickson SSRN Electronic Journal (2022) https://doi.org/10.2139/ssrn.4137384
Comparative analysis of machine learning algorithms and statistical models for predicting crown width of Larix olgensis
Allometric models for the estimation of foliage area and biomass from stem metrics in black locust
SR Tziaferidis, G Spyroglou, MN Fotelli and K Radoglou iForest - Biogeosciences and Forestry 15(4) 281 (2022) https://doi.org/10.3832/ifor3939-015
The Last Trees Standing: Climate modulates tree survival factors during a prolonged bark beetle outbreak in Europe
Nataliya Korolyova, Arne Buechling, Renata Ďuračiová, Khodabakhsh Zabihi, Marek Turčáni, Miroslav Svoboda, Jaromír Bláha, Kelly Swarts, Miroslav Poláček, Jaromir Hradecký, Jaroslav Červenka, Pavel Němčák, Fredrik Schlyter and Rastislav Jakuš Agricultural and Forest Meteorology 322 109025 (2022) https://doi.org/10.1016/j.agrformet.2022.109025
Predicting crown width and length using nonlinear mixed-effects models: a test of competition measures using Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.)
Effects of disturbances by forest elephants on diversity of trees and insects in tropical rainforests on Mount Cameroon
Vincent Maicher, Sylvain Delabye, Mercy Murkwe, Jiří Doležal, Jan Altman, Ishmeal N. Kobe, Julie Desmist, Eric B. Fokam, Tomasz Pyrcz and Robert Tropek Scientific Reports 10(1) (2020) https://doi.org/10.1038/s41598-020-78659-7
Dynamic coupling of allometric ratios to a process-based forest growth model for estimating the impacts of stand density changes
Rüdiger Grote, David Kraus, Wendelin Weis, Rasmus Ettl and Axel Göttlein Forestry: An International Journal of Forest Research 93(5) 601 (2020) https://doi.org/10.1093/forestry/cpaa002
Selection of crown type provides a potential to improve the content of isorhamnetin in Ginkgo biloba
New Method for Forest Resource Data Collection Based on Smartphone Fusion with Multiple Sensors
Guangpeng Fan, Yanqi Dong, Danyu Chen and Feixiang Chen Mobile Information Systems 2020 1 (2020) https://doi.org/10.1155/2020/5736978
Vincent Maicher, Sylvain Delabye, Mercy Murkwe, Jiří Doležal, Jan Altman, Ishmeal N. Kobe, Julie Desmist, Eric B. Fokam, Tomasz Pyrcz and Robert Tropek (2020) https://doi.org/10.1101/2020.06.10.144279
Interregional Crown Width Models for Individual Trees Growing in Pure and Mixed Stands in Austria
The Effect of Tree Crown Allometry on Community Dynamics in Mixed-Species Stands versus Monocultures. A Review and Perspectives for Modeling and Silvicultural Regulation
Automatic Assessment of Crown Projection Area on Single Trees and Stand-Level, Based on Three-Dimensional Point Clouds Derived from Terrestrial Laser-Scanning
Development of a System of Compatible Individual Tree Diameter and Aboveground Biomass Prediction Models Using Error-In-Variable Regression and Airborne LiDAR Data