Predicting Loblolly Pine Site Index from Soil Properties Using Partial Least-Squares Regression
Author:
Publisher
Oxford University Press (OUP)
Subject
Ecological Modeling,Ecology,Forestry
Cited by 19 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Modeling dominant height with USGS 3DEP LiDAR to determine site index in even-aged loblolly pine (Pinus taeda L.) plantations in the southeastern US;Forestry: An International Journal of Forest Research;2024-07-23
2. Modeling structural traits of Aleppo pine ( Pinus halepensis Mill.) forests with low-density LiDAR;European Journal of Remote Sensing;2024-05-09
3. Productivity-environment models for Scots pine plantations in Bulgaria: an interaction of anthropogenic origin peculiarities and climate change;Ecological Modelling;2024-04
4. Forest soil classification for intensive pine plantation management: “Site Productivity Optimization for Trees” system;Forest Ecology and Management;2024-03
5. Estimación de la calidad de sitio de Cinchona pubescens (Rubiaceae), en el bosque montano La Palma, Chota, Perú;Lilloa;2023-12-12
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