SAF ForestEd
Operationalizing Digital Forest Twins with AI
Includes a Live Web Event on 11/18/2026 at 12:00 PM (EST)
-
You must log in to register
- Non-member - $10
- Member - Free!
Webinar information
This webinar from the University of Idaho Digital Forest Lab shows how quickly AI and digital forestry are advancing, and how they are being tied to everyday forest management and landowner services. It opens with new methods for co-registering repeat point cloud datasets, which allow consistent digital twin measurements over time and growth assessment at scale. It then walks through real-world examples of digital forest twins being used to measure and project stand growth, simulate silvicultural treatments, model what-if scenarios, and share results through interactive dashboards.
Communities of Interest are another way to receive, contribute, and add value to your SAF membership. LEARN MORE about SAF Communities of Interest or how to join the Physiology Community of Interest. JOIN SAF to engage in a community of interest and tap the growing membership benefits.
Is this webinar for you?
This webinar is for forest landowners and managers of any size who want to use remote sensing and AI to better understand, monitor and manage their forestland. You don’t need a technical background, so it fits anyone curious about how LiDAR and digital forest twins can turn complex data into practical management decisions.
Registration
1. Click REGISTER to the right of the webinar title. Be sure to log in with your SAF account username and password.
2. After checking out, the webinar will be available on your MY DASHBOARD page here on ForestEd.
For group registrations or registering someone other than yourself please contact [email protected] or 202-938-3910.
Pricing
Registration is FREE ($0) for SAF members. Members still need to register to gain access to the webinar.
SAF Non-member price is $10. Join SAF today to access Community of Interest webinars for free and other growing member benefits. Affiliate membership is now available!
Webinar access
The webinar will be live on Wednesday, November 18 at 12:00 pm ET.
It will be recorded, and its recording will be accessible for a year following air date. Access will close after November 18, 2027.
The webinar is accessible within the Contents tab (to the right of the Overview information).
Webinar duration
This webinar is 1 hour and 30 minutes.
Learning objectives
Upon successful completion of this webinar, you will be able to:
1. Define a digital forest twin and describe how LiDAR point clouds are used to create one.
2. Explain how repeat point cloud datasets are aligned to measure tree and stand growth over time.
3. Identify ways digital forest twins can support management decisions, including projecting growth, simulating treatments, and modeling what-if scenarios.
Rubric
Successful completion of the webinar is measured by viewing the entire webinar and completing the evaluation.
Evaluation
Participant feedback is appreciated to help the Community of Interest and presenters continually improve webinars for future programming.
CFEs
Upon successful completion of this webinar, you will earn 1.5 CFEs in Category 1. CFEs will automatically be added to your CFE record located on www.eforester.org.
Certificate
Upon successful completion of this webinar and the evaluation, participants may download and print a certificate verifying completion of the webinar and earning CFEs. CFEs will be uploaded to participant CFE records by the end of the day (11:59 pm ET).
Return to Webinar (live or archived)
Once you are registered for the webinar, access this webinar within your MY DASHBOARD. Prior to the start time, the webinar will be listed under "Upcoming Live Events." Following the end of the webinar, the webinar will be accessible within the general listing of registered items of YOUR DASHBOARD. The archived webinar will be available for 1 year following its live air date.
Webinar Resources
Additional resources are available within the Resources tab and within the Contents tab.
Need Help?
For ForestEd questions, visit FAQs, email [email protected], or check out the registration quick tips in the Handouts tab. For questions about this Community of Interest, contact the Inventory and Biometrics Community of Interest point of contact Mark Kimsey at [email protected]. For technical assistance and questions about this webinar, email [email protected].
Refund
This is a non-refundable item. Please view FAQs for additional information.
Edward Flathers
Postdoctoral Research Fellow
Intermountain Forestry Cooperative - University of Idaho
Edward Flathers holds a PhD in natural resources from the University of Idaho and is currently a Research Scientist specializing in remote sensing applications for forest measurement and monitoring. His work focuses on the use of LiDAR and related three-dimensional point cloud data to quantify forest structure, derive individual-tree attributes, and assess applications of spatial datasets across multiple sensing modalities. By combining geospatial computation, ecological insight, and reproducible software practices, his research contributes to the development of quantitative frameworks for digital forest monitoring and inventory.
Steevensen Alcius
PhD Research Assistant
Forest Innovations Institute, University of Idaho
Steevensen Alcius is a PhD student in the Department of Forest, Rangeland and Fire Sciences at the University of Idaho, specializing in forest biometrics and remote sensing. His current research focusing on aligning and comparing LiDAR and aerial imagery derived point clouds collected over time to measure tree growth and assess forest productivity. He is particularly interested in connecting advances in remote sensing with the practical questions about how forests are changing and what those changes mean for management.
Jaslam Poolakkal
Data Scientist
Intermountain Forestry Cooperative, University of Idaho
Jaslam Poolakkal is a Research Scientist II and Lead Data Scientist with the Intermountain Forestry Cooperative at the University of Idaho, where he specializes in small area estimation, spatial statistics, uncertainty quantification and machine learning applied to LiDAR and remote sensing data. He holds a Ph.D. in Statistics from CCS Haryana Agricultural University, and he has developed widely used forestry decision-support tools, including the SDImax carrying-capacity models, the Forest Site Type tool and the open-source CONIFER package. He has written 26 peer-reviewed articles and two books, is a named investigator on more than $900,000 in competitive funding, and mentors students and researchers in statistics, forestry and data science.
Bruce Ripley
Chief Innovation Officer
College of Natural Resources at the University of Idaho
Bruce Ripley is currently the Chief Innovation Officer for the College of Natural Resources at the University of Idaho. Over the last 35 years he has worked in industrial forestry across the breadth of North America, from Northern New England to the Intermountain West, Pacific, South and Southeast. He has extensive experience in designing and managing forest information systems, as well as experience in forest planning, growth and yield, and financial analysis. More recently Bruce joined the University of Idaho to support its commitment to advance the science of forest innovation and high precision digital forestry leveragingLiDAR and other remote sensed data.
Mark Kimsey (Moderator)
Associate Professor
Department of Forest, Rangeland, and Fire Sciences, University of Idaho
Mark Kimsey Jr. is an Associate Professor in the Department of Forest, Rangeland and Fire Sciences at the University of Idaho. He directs the Intermountain Forestry Cooperative and co-leads the UofI Digital Forest Laboratory. His research covers production silviculture, forest mensuration, tree nutrition, and soils and spatial modeling. He holds a Ph.D. in Natural Resources from the University of Idaho, teaches forest mensuration and digital forestry, and serves as Chair of the SAF A-1 Community of Interest.
Key:
Complete
Next
Failed
Available
Locked