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Randolph H. Wynne

Randolph H. Wynne

D-Index & Metrics

Environmental Sciences

D-Index
40
Citations
14281
World Ranking
7894
National Ranking
2801

Overview

Randolph H. Wynne is affiliated with Virginia Tech in the United States and has contributed extensively to the field of Environmental Science. Their research primarily focuses on topics within remote sensing applications and forest ecology, reflecting a multidisciplinary approach to environmental management and conservation.

The main fields of study associated with Wynne include Environmental Science, with significant contributions to related subfields such as Environmental Engineering, Ecology, Global and Planetary Change, Nature and Landscape Conservation, and Insect Science. These areas highlight an emphasis on understanding the interactions within ecosystems and their responses to environmental changes.

Wynne's research interests are concentrated around several key topics, including:

  • Remote Sensing and LiDAR Applications
  • Remote Sensing in Agriculture
  • Forest ecology and management
  • Forest Management and Policy
  • Forest Ecology and Biodiversity Studies
  • Land Use and Ecosystem Services
  • Conservation, Biodiversity, and Resource Management

Their publication record features contributions to journals specializing in remote sensing, environmental monitoring, and forestry research. Frequent venues for Wynne's work include:

  • Remote Sensing of Environment
  • International Journal of Applied Earth Observation and Geoinformation
  • International Journal of Remote Sensing
  • Ecological Informatics
  • Forestry An International Journal of Forest Research

Wynne has co-authored extensively with several researchers, reflecting collaboration within the forestry and environmental science community. Notable frequent co-authors include Valerie A. Thomas, David R. Carter, Rachel L. Cook, John W. Coulston, and Otávio Camargo Campoe.

Among recent published papers are the following:

  • Estimating the overstory and understory vertical extents and their leaf area index in intensively managed loblolly pine (Pinus taeda L.) plantations using airborne laser scanning, 2020, Remote Sensing of Environment
  • Mapping thins to identify active forest management in southern pine plantations using Landsat time series stacks, 2020, Remote Sensing of Environment
  • Enhancing the precision of broad-scale forestland removals estimates with small area estimation techniques, 2020, Forestry An International Journal of Forest Research
  • Assessing the utility of NAIP digital aerial photogrammetric point clouds for estimating canopy height of managed loblolly pine plantations in the southeastern United States, 2022, International Journal of Applied Earth Observation and Geoinformation
  • Increased Precision in County-Level Volume Estimates in the United States National Forest Inventory With Area-Level Small Area Estimation, 2022, Frontiers in Forests and Global Change

Best Publications

  • Landsat-8: Science and Product Vision for Terrestrial Global Change Research

    David P. Roy;M.A. Wulder;Thomas R. Loveland;C.E. Woodcock

  • Historical Trends in Lake and River Ice Cover in the Northern Hemisphere

    John J. Magnuson;Dale M. Robertson;Barbara J. Benson;Randolph H. Wynne

  • Free access to Landsat imagery.

    Curtis E. Woodcock;Richard Allen;Martha Anderson;Alan Belward

  • Current status of Landsat program, science, and applications

    Michael A. Wulder;Thomas R. Loveland;David P. Roy;Christopher J. Crawford

  • Measuring individual tree crown diameter with lidar and assessing its influence on estimating forest volume and biomass

    Sorin C Popescu;Randolph H Wynne;Ross F Nelson

  • Seeing the Trees in the Forest: Using Lidar and Multispectral Data Fusion with Local Filtering and Variable Window Size for Estimating Tree Height

    Sorin C. Popescu;Randolph H. Wynne

  • Fusion of small footprint LiDAR and multispectral data to estimate plot-level volume and biomass in deciduous and pine forests in Virginia, USA

    Sorin C. Popescu;Randolph H. Wynne;John A. Scrivani

  • Estimating plot-level tree heights with lidar: local filtering with a canopy-height based variable window size

    Sorin C Popescu;Randolph H Wynne;Ross F Nelson

  • Evaluation of Landsat and MODIS data fusion products for analysis of dryland forest phenology

    J.J. Walker;K.M. de Beurs;R.H. Wynne;F. Gao

  • Estimating forest biomass using small footprint LiDAR data: An individual tree-based approach that incorporates training data

    Zachary J. Bortolot;Randolph H. Wynne

  • Measuring the sensitivity of southern Wisconsin lake ice to climate variations and lake depth using a numerical model

    Stephen J. Vavrus;Randolph H. Wynne;Jonathan A. Foley

  • Dryland vegetation phenology across an elevation gradient in Arizona, USA, investigated with fused MODIS and Landsat data

    J.J. Walker;K.M. de Beurs;R.H. Wynne

  • Forest Volume and Biomass Estimation Using Small-Footprint Lidar-Distributional Parameters on a Per-Segment Basis

    Jan A.N. van Aardt;Randolph H. Wynne;Richard G. Oderwald

  • On-the-Fly Massively Multitemporal Change Detection Using Statistical Quality Control Charts and Landsat Data

    Evan B. Brooks;Randolph H. Wynne;Valerie A. Thomas;Christine E. Blinn

  • Revisiting Theories of Frontier Expansion in the Brazilian Amazon: A Survey of the Colonist Farming Population in Rondônia’s Post-Frontier, 1992–2002

    John O. Browder;Marcos A. Pedlowski;Robert Walker;Randolph H. Wynne

  • Fitting the Multitemporal Curve: A Fourier Series Approach to the Missing Data Problem in Remote Sensing Analysis

    Evan B. Brooks;V. A. Thomas;R. H. Wynne;J. W. Coulston

  • Spectral Separability among Six Southern Tree Species

    Randolph H. Wynne;Richard G. Oderwald;James B. Campbell

  • Approximating Prediction Uncertainty for Random Forest Regression Models

    John W. Coulston;Christine E. Blinn;Valerie A. Thomas;Randolph H. Wynne

  • A review of past research on dendrometers

    Neil A. Clark;Randolph H. Wynne;Daniel L. Schmoldt

  • Examining pine spectral separability using hyperspectral data from an airborne sensor: An extension of field-based results

    J. A. N. van Aardt;R. H. Wynne

  • Global patterns of lake ice phenology and climate' Model simulations and observations

    Sinead E. Walsh;Stephen J. Vavrus;Jonathan A. Foley;Veronica A. Fisher

Frequent Co-Authors

Layne T. Watson
Layne T. Watson Virginia Tech
Thomas R. Fox
Thomas R. Fox Boehringer Ingelheim (Germany)
John W. Coulston
John W. Coulston US Forest Service
Martha C. Anderson
Martha C. Anderson Agricultural Research Service
Asko Noormets
Asko Noormets Texas A&M University
Curtis E. Woodcock
Curtis E. Woodcock Boston University
Zhe Zhu
Zhe Zhu University of Connecticut
Harold E. Burkhart
Harold E. Burkhart Virginia Tech
Sorin C. Popescu
Sorin C. Popescu Texas A&M University
David J. Harding
David J. Harding Goddard Space Flight Center

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