Sheng-I Yang

Assistant Professor of Forest Biometrics

The University of Tennessee Knoxville

United States

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Dr. Sheng-I Yang is an Assistant Professor of Forest Biometrics at The University of Tennessee Knoxville, USA. His research focuses on forest metrics, including stand carrying capacity, stem taper, and height-diameter relationships, with recent publications addressing various methods to quantify forest characteristics and tree species, particularly in North America and Türkiye. He utilizes advanced modeling techniques and remote sensing data to enhance forest management and ecological understanding.

Articles (15)

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2025

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2024

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2023

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2023

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2022

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2022

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2022

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2020

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2020

Collaborators (1)

Lisa Muller

Professor, Assistant Department Head, and Graduate Coordinator

University of Tennessee

UNITED STATES

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Sheng-I Yang

Research Interests

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Articles (15)

Estimating Stand Carrying Capacity for Three Common Pine Species Across Various Regions of Türkiye

Quantifying bark thickness and bark volume with alternative modeling procedures for eight species in the southeastern US

Quantifying the Profiles of Heartwood, Sapwood, and Bark Using a Seemingly Unrelated Mixed-Effect Model for Larix Olgensis in Northeast China

MORTALITY, SURVIVAL, AND SEROLOGIC RESULTS FOR ELK (CERVUS CANADENSIS) IN THE CUMBERLAND MOUNTAINS OF TENNESSEE, USA

Evaluating semi- and nonparametric regression algorithms in quantifying stem taper and volume with alternative test data selection strategies

Synergistic use of Sentinel-1, Sentinel-2, and Landsat 8 in predicting forest variables

Evaluation of regression methods and competition indices in characterizing height-diameter relationships for temperate and pantropical tree species

Comparison of Data Grouping Strategies on Prediction Accuracy of Tree-Stem Taper for Six Common Species in the Southeastern US

Predicting bark thickness with one- and two-stage regression models for three hardwood species in the southeastern US

Characterizing height-diameter relationships for Caribbean trees using mixed-effects random forest algorithm

Estimating maximum stand density for mixed-hardwood forests among various physiographic zones in the eastern US

Characterizing Stand and Biomass Tables from Diameter Distribution Models: A Case Study for Mixed-Hardwood Forests in Eastern Tennessee, USA

A retrospective comparison of carrying capacity of two generations of loblolly pine plantations

Comparison of Parametric and Nonparametric Methods for Estimating Size–Density Relationships in Old-Growth Japanese Cedar (<i>Cryptomeria japonica</i> D. Don) Plantations

Evaluation of total tree height subsampling strategies for estimating volume in loblolly pine plantations

Collaborators (1)

Lisa Muller

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