Presentations

Talks, lectures, meetings, and webinars.

  1. Comparison of photogrammetric point clouds and neural network canopy height models with national forest inventory data.

    Frank, Bryce. 2026. Operational Lidar Inventory Meeting . Vancouver, WA. Invited talk.

    STATStatistical methods in forestryRSRemote sensing of the forested environment Photogrammetry 3

  2. Post-stratification in the Pacific Northwest and Rocky Mountain FIA Regions

    Frank, Bryce, Schleeweis, K. 2026. All Forest Inventory and Analysis Operations Meeting . Portland, OR.

    STATStatistical methods in forestry Forest Measurements 4

  3. Sunsetting of Pacific Northwest FIA's Height Subsampling

    Frank, Bryce. 2026. California, Oregon, and Washington FIA Data Collection Spring Training . Invited talk.

    AGYAllometrics, growth, and yield Allometric Models 1

  4. The End of Growth Sample Trees in the Pacific Northwest FIA Program

    Frank, Bryce. 2026. All Forest Inventory and Analysis Operations Meeting . Portland, OR.

    AGYAllometrics, growth, and yield Forest Measurements 4

  5. The Essence of Measurement Error on Remeasured Tree Heights

    Frank, Bryce. 2026. Forest Models . Oregon State University. Corvallis, OR. Invited talk.

    AGYAllometrics, growth, and yieldSTATStatistical methods in forestry Measurement Error 1

  6. Classification and Regression Trees in Forest Inventory and Analysis

    Frank, Bryce. 2025. Forest Modeling with Machine Learning . Oregon State University. Corvallis, OR. Invited talk.

    STATStatistical methods in forestry Classification and Regression Trees 1 Forest Monitoring 5

  7. Estimating forest biomass in Oregon using small area estimation

    Joo, S., Temesgen, H., Frank, B. 2025. Center for Intensive Planted-forest Silviculture Technical Review . Corvallis, OR.

    STATStatistical methods in forestry Small Area Estimation 8

  8. Integrating FIA data and remote sensing for small area estimation

    Joo, S., Temesgen, H., Frank, B. 2025. Center for Intensive Planted-forest Silviculture Meeting . Corvallis, OR.

    STATStatistical methods in forestryRSRemote sensing of the forested environment Small Area Estimation 8 Photogrammetry 3

  9. Predicting Heights

    Frank, Bryce. 2025. Vegetation Monitoring, Science, and Applications Team Meeting . Virtual. Invited talk.

    AGYAllometrics, growth, and yieldSTATStatistical methods in forestry Forest Measurements 4

  10. Random Forests in Forest Inventory and Analysis

    Frank, Bryce. 2025. Forest Modeling with Machine Learning . Oregon State University. Corvallis, OR. Invited talk.

    STATStatistical methods in forestry Random Forests 1 Forest Monitoring 5

  11. Small area estimation of stand attributes in Washington using 3D‑NAIP and Sentinel-derived variables

    Joo, S., Temesgen, H., Frank, B. 2025. Presented to the Center for Intensive Planted-forest Silviculture Steering Committee . Corvallis, OR.

    STATStatistical methods in forestryRSRemote sensing of the forested environment

  12. The Alaskan Rough Cull Conundrum

    Frank, Bryce. 2025. Forest Inventory and Analysis Alaska Science Team . Remote.

    AGYAllometrics, growth, and yield Quality Assurance 1 Tree Defect 1

  13. Using small area estimation and 3D‑NAIP/Sentinel-derived variables for multivariate prediction of stand attributes

    Joo, S., Temesgen, H., Frank, B. 2025. Partnership for Small Area Estimation Meeting . Missoula, MT.

    STATStatistical methods in forestryRSRemote sensing of the forested environment Small Area Estimation 8

  14. Using small area estimation and 3D‑NAIP/Sentinel-derived variables for multivariate prediction of stand attributes

    Joo, S., Temesgen, H., Frank, B. 2025. Presented to the Center for Research on Sustainable Forests Industry Advisory Board . Waimea, HI.

    STATStatistical methods in forestryRSRemote sensing of the forested environment

  15. Applications of Small Area Estimation

    Frank, Bryce. 2024. Forest Biometrics . Oregon State University. Corvallis, OR. Invited talk.

    STATStatistical methods in forestry Small Area Estimation 8 Forest Monitoring 5

  16. Digital aerial photogrammetry, Sentinel-2, and lidar for post-fire forest modeling

    Frank, Bryce, Strunk, J. L., Wolken, K., Fried, J. S., McKenzie, S. C. 2024. Region 5 Fuel Treatment Effectiveness Coordination Meeting . Virtual. Invited talk.

    RSRemote sensing of the forested environment Forest Management 12 Fire and Fuels 2 Fire Effects 3

  17. Estimation of Wildfire Biomass Consumption with Digital Aerial Photogrammetry

    Frank, Bryce. 2024. Operational Lidar Inventory Meeting . Vancouver, WA. Invited talk.

    STATStatistical methods in forestryRSRemote sensing of the forested environment Photogrammetry 3 Fire Effects 3

  18. Latent Site Index

    Frank, Bryce. 2024. Vegetation Monitoring, Science and Applications Team . Virtual. Invited talk.

    AGYAllometrics, growth, and yield Forest Productivity 2 Site Index 2

  19. Linking Site Tree Measurements Through Time

    Frank, Bryce. 2024. All Forest Inventory and Analysis Operations Meeting . Portland, OR.

    AGYAllometrics, growth, and yield Forest Productivity 2 Site Index 2

  20. National Forest Inventory Plot Remeasurement Planning Committee: Decisions and Implications

    Frank, Bryce. 2024. Vegetation Monitoring and Science Application Team . Virtual.

    STATStatistical methods in forestry Sampling Designs 1

  21. Post-fire Vegetative Mapping with Lidar And Digital Aerial Photogrammetry: A Regional Opportunity

    Frank, Bryce. 2024. Webinar . Virtual.

    RSRemote sensing of the forested environment Forest Management 12 Fire and Fuels 2 Fire Effects 3

  22. Small Area Estimation: Motivations and Applications for Forest Inventories

    Frank, Bryce. 2024. Weyerhaeuser Quantitative Systems and Inventory Team . Centralia, WA. Invited talk.

    STATStatistical methods in forestryRSRemote sensing of the forested environment Small Area Estimation 8 Forest Management 12 Lidar 8

  23. Using small area estimation and 3D‑NAIP/Sentinel-derived variables for multivariate prediction of stand attributes

    Joo, S., Temesgen, H., Frank, B., Strunk, J., Hogg, D., Naumann, N., Montes, C., Radtke, P., Cook, R., Hughes, E. 2024. Presented to the Center for Research on Sustainable Forests Industry Advisory Board . Madison, WI.

    STATStatistical methods in forestryRSRemote sensing of the forested environment

  24. Small area estimation in forest inventories, what to do when sample sizes become small

    Mauro, Francisco, Frank, B. 2023. International Union of Forest Research Organizations . Webinar. Invited talk.

    STATStatistical methods in forestryRSRemote sensing of the forested environment Forest Management 12 Lidar 8 Small Area Estimation 8

  25. Stand Effects: What Are They and What Can We Do About Them?

    Frank, Bryce. 2023. Operational Lidar Inventory Meeting . Vancouver, WA. Invited talk.

    STATStatistical methods in forestryRSRemote sensing of the forested environment Forest Management 12 Lidar 8

  26. Charting a Course for the Bureau of Land Management Strategic Forest Inventory System

    Frank, Bryce. 2022. Presented to the Pacific Northwest Regional Biometrics Meeting . Virtual.

    STATStatistical methods in forestry Forest Management 12

  27. Small Area Estimation of Site Potential Tree Height in Western Oregon

    Frank, Bryce. 2022. Forest Biometrics . Oregon State University. Corvallis, OR. Invited talk.

    STATStatistical methods in forestry Small Area Estimation 8 Forest Monitoring 5

  28. Predicting Site Potential Tree Height with Climatically Driven Site Index Models

    Frank, Bryce. 2021. Presented to the Pacific Northwest Regional Biometrics Meeting . Virtual.

    AGYAllometrics, growth, and yield Forest Management 12

  29. Small Area Estimation in Remote Sensing Forest Inventories

    Frank, Bryce. 2020. Forest Biometrics . Oregon State University. Corvallis, OR. Invited talk.

    STATStatistical methods in forestryRSRemote sensing of the forested environment Small Area Estimation 8 Forest Monitoring 5

  30. Comparison of Classification Models for Commercial Thinning Eligibility using LiDAR

    Frank, Bryce, Mauro, F., Temesgen, H. 2019. Presented to the USDA Forest Service Region 6 Biometrics Team . Portland, OR. Invited talk.

    RSRemote sensing of the forested environment Forest Management 12 Lidar 8

  31. Estimation of tree-lists in southwestern Oregon using LiDAR

    Mauro, Francisco, Temesgen, H., Frank, B. 2019. Bureau of Land Management Science Meeting . Salem, OR.

    RSRemote sensing of the forested environment Forest Management 12 Lidar 8 kNN Imputation 1

  32. Forest Sampling and Measurement Concepts

    Frank, Bryce. 2019. Forest Mensuration . Oregon State University. Corvallis, OR. Invited talk.

    AGYAllometrics, growth, and yield Forest Sampling 1 Forest Measurements 4

  33. The semi-individual tree crown approach: considerations for a model-based inference

    Frank, Bryce, Mauro, F., Hailemariam, T. 2019. Western Mensurationists Meeting . Kamloops, BC, Canada.

    STATStatistical methods in forestryRSRemote sensing of the forested environment Lidar 8 Forest Management 12

  34. Prediction of stand level tree-lists and estimation of growth using LiDAR

    Mauro, Francisco, Frank, B., Temesgen, H. 2018. Presented to Willamette National Forest Supervisor . Springfield, OR. Invited talk.

    RSRemote sensing of the forested environmentAGYAllometrics, growth, and yield Forest Management 12 Lidar 8

  35. Selecting Stands for Thinning with LiDAR

    Frank, Bryce, Mauro, F., Temesgen, H. 2018. Presented to Willamette National Forest Supervisor . Springfield, OR. Invited talk.

    RSRemote sensing of the forested environment Forest Management 12 Lidar 8