Conference Agenda

Crown-level mapping and persistence of emergent tropical trees in fragmented tropical landscapes

Felipe Saad, Matthew Fagan

University of Maryland Baltimore County, United States of America

Assessing forest naturalness using airborne laser scanning (ALS)

Randel Rainer Lille, Diana Laarmann, Mait Lang, Tauri Arumäe

Estonian University of Life Sciences, Estonia

Extracting Ecological Variables from The Brazilian Atlantic Forest Using UAV Images

Marcos Benedito Schimalski, Veraldo Liesenberg, Cindy Fernandes Mendes, João Victor Schimalski

Santa Catarina State University, Brazil

Beyond Climate and Soil: LiDAR-Derived Forest Structure Unlocks Species Habitat Signatures Across the Temperate–Boreal Ecotone

João Paulo Czarnecki de Liz^1,3, Hamid Ghanbari¹, Nelson Thiffault^2,3, Nicholas C. Coops⁴, Alexandre Morin-Bernard^1,3, Alexis Achim^1,3

1: Research Center on Renewable Materials, Laval University, Quebec City, QC, G1V 0A6, Canada; 2: Laurentian Forestry Centre, Canadian Forest Service, Natural Resources Canada, Sainte-Foy, Quebec City; 3: Centre for Forest Research, Faculty of Forestry, Geography, and Geomatics, Laval University, Quebec City, QC, G1V 0A6, Canada; 4: Integrated Remote Sensing Studio, Department of Forest Resources Management, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.

Characterizing the vertical structure of forests in the Brazilian Amazon

Denis Valle¹, Leo Haneda¹, Ismael Brack¹, Jean Ometto², Ovidiu Csillik³, Marcos Longo⁴, Michael Keller^5,6, Danilo Almeida^7,8

1: School of Forest, Fisheries, and Geomatics Sciences, University of Florida, Gainesville, Florida, USA.; 2: Instituto Nacional de Pesquisas Espaciais (INPE), São José dos Campos, Sao Paulo, Brazil.; 3: Environment and Sustainability Studies Program, Wake Forest University, Winston Salem, North Carolina, USA.; 4: Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California, USA.; 5: Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA.; 6: International Institute of Tropical Forestry, United Stated Department of Agriculture Forest Service, Rio Piedras, Puerto Rico; 7: BRCarbon, Piracicaba, Sao Paulo, Brazil.; 8: Bioflore, Belo Horizonte, Minas Gerais, Brazil.

Enhanced Detection of Forest Disturbances in the Pan-Amazon through Integration of Sentinel-2 and Landsat Time Series

Clement Bourgoin¹, Christelle Vancutsem¹, Rene Beuchle¹, Julie Betbeder², Damien Arvor³, Silvia Carboni⁴, Dario Simonetti⁵, Joao Carreiras⁶, Rene Colditz¹, Frederic Achard¹

1: European Commission, Joint Research Centre, Ispra, Italy; 2: CIRAD, Forêts et Sociétés, Montpellier, France; 3: LETG Rennes UMR 6554 LETG, Université Rennes 2, 35042 Rennes, France; 4: European Dynamics Luxembourg S.A., Milan, 20121, Italy; 5: GIS and Remote Sensing Consultant, Varese, Italy; 6: VASS Italy, Torino, 10100, Italy

deFOREST: Fusing Optical and Radar satellite data for Enhanced Sensing of Tree-loss

Julio Castrillon¹, Hanfeng Gu¹, Caleb Meredith¹, Xiaojing Tang², Pontus Olofsson³, Mark Kon¹

1: Boston University, United States of America; 2: James Madison University; 3: NASA Marshall Space Flight Center

Evaluating endmember specificity for SMA-based disturbance detection across Pinus sylvestris provenance regions in Spain

Saioa Munuera¹, Cristina Gómez^1,2, Beatriz Águeda¹, Francisco Rodríguez-Puerta¹

1: University of Valladolid, Spain; 2: University of Aberdeen, Scotland

Augmenting Training data for Individual Tree Biomass Estimation using UAV LiDAR in Dense Forest and Urban Environments

Sina Jarahizadeh¹, Bahram Salehi¹, Eddie Bevilacqua²

1: State University of New York College of Environmental Science and Forestry, Department of Environmental Resources Engineering; 2: State University of New York College of Environmental Science and Forestry (SUNY ESF) Department of Sustainable Resources Management

Estimating tree-level aboveground biomass using Unmanned Aerial Vehicle (UAV)-based multispectral imagery in mixed-species forests of the southeastern United States

Favour Onyido, Lana L. Narine, Adam Maggard, Richard Cristan, John S. Kush

College of Forestry, Wildlife and Environment, Auburn University, United States of America

Estimating aboveground biomass loss from tree cover to cropland conversion

Shi Jun Wee, Xiao-Peng Song

University of Maryland, College Park, United States of America

Addressing The Small Data Problem in Forestry: Self-Supervised Learning for Aboveground Biomass Estimation

Harry Seely¹, Nicholas C. Coops¹, Joanne C. White², David Montwé³, Ahmed Ragab^3,4

1: University of British Columbia, Faculty of Forestry, Canada; 2: Canadian Forest Service (Pacific Forestry Centre), Natural Resources Canada, 506 West Burnside Road, Victoria, British Columbia V8Z 1M5, Canada; 3: CanmetENERGY, Natural Resources Canada, 1615 Lionel-Boulet Blvd, P.O. Box 4800, Varennes, Québec, J3X 1P7, Canada; 4: Department of Mathematics and Industrial Engineering, Polytechnique Montreal, Québec, H3T 1J4, Canada

Validating Handheld LiDAR for Single-Tree Volume and Aboveground Biomass Carbon: Quantifying the Impact of Height Uncertainty

Luke Dowd, Brian Tobin

University College Dublin, Ireland

Advancing the quantification of urban tree carbon content through the application of terrestrial laser scanning technology.

Georgios Arseniou, Samit Kafle

Auburn University, United States of America

A novel tree-height independent method for tree volume estimation based on TLS point clouds

Grzegorz Krok^1,2, Krzysztof Stereńczak^1,2, Bartłomiej Kraszewski², Marek Lisańczuk², Krzysztof Mitelsztedt², Miłosz Mielcarek^1,2

1: IDEAS Research Institute, Poland; 2: Forest Research Institute, Poland

Combined Impact of Semantic Segmentation and Quantitative Structure Modelling of Southern Pine Trees using Terrestrial Laser Scanning

Jinyi Xia¹, Timothy Martin¹, Gary Peter¹, Kody Brock¹, Jeff Atkins², Matthew Gitzendanner³, Inacio Bueno¹, Kim Calders⁴, Ana Paula Dalla Corte⁵, Andrew Hudak¹, Monique Bohora Schlickmann¹, Michael Andreu¹, Caio Hamamura⁶, Carine Klauberg¹, Carlos Silva¹

1: University of Florida, United States of America; 2: Department of Biology, Virginia Commonwealth University, Richmond, VA, 23284, USA; 3: Department of Biology, University of Florida, Gainesville, FL, 32611, USA; 4: Q-ForestLab – Laboratory of Quantitative Forest Ecosystem Science, Department of Environment, Ghent University, Ghent, 9000, Belgium; 5: Department of Forest Engineering, Federal University of Paraná (UFPR), Curitiba, PR, Brazil; 6: Federal Institute of Education, Science and Technology of São Paulo, São Paulo, 11533-160, Brazil

Using UAVs to understand stand-level drivers of hurricane susceptibility in southeastern Georgia’s pecan orchards

Leah Andino¹, Andrew Whelan¹, M. Lenny Wells², Jeffery Cannon¹

1: The Jones Center at Ichauway, United States of America; 2: University of Georgia, United States of America

Scaling tropical cyclone risk across the southeast to inform conservation planning

Nicole Zampieri^1,2,3, Jeffery Cannon³, William Platt^2,4, Christine Fortuin⁵, Frank Gilliam⁶, Ajay Sharma⁷

1: University of Central Florida; 2: Tall Timbers; 3: The Jones Center at Ichauway; 4: Louisiana State University; 5: Mississippi State University; 6: University of West Florida; 7: Auburn University

Mapping post-hurricane damage severity in southern U.S. forests using PlanetScope imagery, LiDAR, and deep learning

Alexander J. Gaskins, Adithi Anuga, Cesar Alvitez, Inacio T. Bueno, Carlos A. Silva

Forest Biometrics, Remote Sensing and Artificial Intelligence Laboratory (Silva Lab), School of Forest, Fisheries, and Geomatics Sciences, University of Florida, Gainesville, FL 32611, USA

Mapping damage and ecological recovery to guide forest management and recovery after Hurricane Ian

Inacio Bueno¹, Carlos Silva¹, Caio Hamamura², Victoria Donovan¹, Ajay Sharma³, Jiangxiao Qiu¹, Jinyi Xia¹, Kody Brock¹, Monique Schlickmann¹, Jeff Atkins⁴, Denis Valle¹, Jason Vogel¹, Andres Susaeta⁵, Mauro Karasinski⁶, Carine Klauberg¹

1: School of Forest, Fisheries, and Geomatics Sciences, University of Florida, Gainesville, FL 32611, USA; 2: Federal Institute of Education, Science and Technology of São Paulo, Capivari, SP, Brazil; 3: College of Forestry, Wildlife and Environment, Auburn University, Auburn, AL 36849, USA; 4: Virginia Commonwealth University, Richmond, VA 23284, USA; 5: Department of Forest Engineering, Resources and Management, Oregon State University, Corvallis, OR 97331, USA; 6: BIOFIX Research Center, Federal University of Paraná, Curitiba, PR 80210-170, Brazil

Forest Biomass Estimation Using Deep Learning and Multi-Source Remote Sensing Data in the Bohemian Forest Ecosystem

Christine Hechtl^1,2, Isabelle Klein^1,2, Jakob Ebenbeck¹, Christoph Schierghofer³, Lukas Lehnert³, Stanislav Grill^4,5, Martin Hais⁵, Marco Heurich^1,2,6

1: Department of National Park Monitoring and Animal Management, Bavarian Forest National Park, Freyunger Straße 2, D-94481 Grafenau, Germany; 2: Wildlife Ecology and Management, University of Freiburg, Tennenbacher Straße 4, D-79106 Freiburg, Germany; 3: Department of Geography, Ludwig-Maximilians-University Munich, Luisenstraße 37, D-80333 Munich, Germany; 4: Department of Geoinformatics, Faculty of Science, Palacký University Olomouc, 17. listopadu 50, Olomouc 77146, Czech Republic; 5: Department of Ecosystem Biology, Faculty of Science, University of South Bohemia in České Budějovice, Branišovská 1760, 370 05, České Budějovice, Czech Republic; 6: Institute for Forest and Wildlife Management, Campus Evenstad, University of Inland Norway, 2480 Koppang, Norway

Forest structure and carbon dynamics across the Amazon using GEDI and airborne lidar

Ovidiu Csillik¹, Michael Keller², Marcos Longo³

1: Environment and Sustainability Studies Program, Wake Forest University, Winston-Salem, NC, USA; 2: International Institute of Tropical Forestry, USDA Forest Service, San Juan, PR, USA; 3: Climate andEcosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA

Forest structure as a source of bias in remote sensing-based biomass estimates: insights from the validation of ESA’s CCI and NASA’s GEDI models

Juan Alberto Molina-Valero¹, Reza Mohammadi Asiyabi², Casey Ryan², Vítězslav Moudrý¹, Steven Hancock²

1: Czech University of Life Sciences Prague; 2: University of Edinburgh

Using destructive sampling to validate mangrove biomass estimates from terrestrial laser scanning and published allometries

Todd A. Schroeder¹, Charles A. Price², Benjamin Branoff¹, Eben Broadbent³, Mona Papeş², Humfredo Marcano-Vega¹, Skip J. Van Bloem⁴, Karen Cummins⁵, Danielle Ogurcak⁶

1: USDA Forest Service, Southern Research Station, USA; 2: University of Tennessee, Ecology & Evolutionary Biology, USA; 3: University of Florida, School of Forestry, Fisheries, and Geomatics Sciences, USA; 4: Clemson University, Forestry and Environmental Conservation Department, USA; 5: Tall Timbers Research Station, USA; 6: Florida International University, Institute of Environment, USA

Tree species mapping at regional scale with Planet data and weakly labelled training data

Michele Dalponte, Jana Annika Wicklein, Chiara Benedetti, Thomas Maffei, Davide Andreatta

Fondazione Edmund Mach, Italy

Pixel-based tree species detection using aerial hyperspectral imagery data in mid-Atlantic mixed hardwood forests

Faezeh Molaei, Douglas Miller, Jeffrey Catchmark, Paul Heinemann, Marc McDill

Pennsylvania State University, United States of America

Individual Tree Species Prediction and Area-Based Metrics in the Acadian Forest: New Brunswick's Unique and Highly Diverse Forest

Maurice LeBlanc

Forsite Consultants, Canada

Spectral response of plants to herbivore overabundance

Ramón Perea¹, Carmen Rello¹, Jesús Rodríguez-Calcerrada¹, Francisco García¹, Iolanda Filella², Josep Peñuelas², Emmanuel Serrano³

1: Universidad Politécnica de Madrid, Spain; 2: CSIC, Global Ecology Unit CREAF-CSIC-UAB, Bellaterra, Spain; 3: Wildlife Ecology & Health Group (WE&H) and Servei d’Ecopatologia de Fauna Salvatge (SEFaS), Departament de Medicina i Cirurgia Animals, UAB, Barcelona, Spain

Modeling the Regeneration of Aspen Using Remote Sensing, Machine Learning, and Field Validation in Post-Fire Ecosystems.

Mateo Alliende

University of Washington, United States of America

Mapping Forest Vulnerability Across Europe Using the Composite2Change (C2C) Framework

Emma Bambagioni¹, Giovanni D'Amico², Txomin Hermosilla Gomez³, Saverio Francini¹

1: University of Bologna, Italy; 2: University of Florence, Italy; 3: Canadian Forest Service, Natural Resources Canada

Longterm index trends demonstrate canopy loss and possible link to hydrologic change in a barrier island forest

Christine Mutiti, Megan Martin, Sam Mutiti

Georgia College & State University, United States of America

Integrating field and high-resolution remote sensing data for comprehensive forest disturbance monitoring

Maciej Lisiewicz, Agnieszka Kamińska, Bartłomiej Kraszewski, Łukasz Kuberski, Krzysztof Stereńczak

Forest Research Institute, Poland

Connecting forest structural diversity and foliar trait diversity across spatial scales and climate gradients in the eastern United States

Zachary Horve¹, Songlin Fei¹, Dennis Choi^1,2, Jianmin Wang¹, Brady Hardiman^1,3

1: Department of Forestry and Natural Resources, Purdue University, West Lafayette, IN, USA; 2: Department of Environmental Horticulture, Dankook University, Cheonan, South Chungcheong, South Korea; 3: Environmental and Ecological Engineering, Purdue University, West Lafayette, IN, USA

Detecting deadwood from terrestrial laser scanning data using deep learning

Shaohui Zhang¹, Stefano Puliti², Tuomas Yrttima¹, Topi Tanhuanpää¹, Lauri Liikonen¹, Aapo Erkkilä¹, Tuomas Aakala¹, Ninni Saarinen³, Miiko Vastaranta¹

1: University of Eastern Finland (UEF); 2: Norwegian Institute for Bio-economy Research (NIBIO); 3: ELY Centres of North Karelia

Pristine forests approach maximum mean-independent entropy in every global climate

Cameron Pellett, Ruben Valbuena

Swedish University of Agricultural Sciences (SLU), Sweden

Essential Biodiversity Variables of Ecosystem Structure: Definitions and Operational Workflows

Ruben Valbuena

Swedish University of Agricultural Sciences, Sweden

Accurate and Dynamic Fuel Load Mapping Using Satellite Remote Sensing Across Canada

Gonzalo Gavilan, Joseph Rakofsky, Joanna Wand

Forsite, Canada

Coupling dead surface and ground fuel estimates to canopy biomass characterized using pre- and post-fire airborne laser scanning data in the western US

Nuria Sánchez López¹, Andrew T. Hudak², Benjamin C. Bright², Michael J. Campbell³, Ryan McCarley⁴, Astrid Sanna⁵, Russ Parsons⁶, Carlos Cabo⁷

1: Institute of Natural Resources and Spatial Planning (INDUROT), University of Oviedo, 33600 Mieres, Asturias, Spain; 2: US Department of Agriculture Forest Service, Rocky Mountain Research Station Moscow Forestry Laboratory, Moscow, Idaho, 83843, USA; 3: School of Environment, Society and Sustainability, University of Utah, Salt Lake City, UT, 84112, USA; 4: American Forests, Washington, DC, 20005, USA; 5: School of Environmental and Forest Sciences, University of Washington, Seattle, WA, 98195, USA; 6: USDA Department of Agriculture Forest Service, Fire Sciences Lab, Missoula, Montana, 59808, USA; 7: Department of Mining Exploitation and Prospecting, University of Oviedo, 33600 Asturias, Spain

Spatially explicit fuel distribution models from neighborhood methods

Seth Bigelow¹, Andrew Hudak², Benjamin Bright², Nuria Sanchez Lopez³, Louise Loudermilk⁴, Christie Hawley⁴

1: Tall Timbers, United States of America; 2: USDA-FS Rocky Mountain Research Station; 3: University of Oviedo, Spain; 4: USDA-FS Southern Research Station

Deep Learning of Snags and Coarse Woody Bebris (CWD) using VHR UAS imagery and LiDAR point clouds at FuelCraft Selected sites in United States

Nadeem Fareed¹, Carlos Alberto Silva¹, Susan Prichard²

1: School of Forest, Fisheries, and Geomatics Sciences, University of Florida; 2: School of Environmental and Forest Sciences University of Washington

Novel DBH Estimation in Highly Dense Understory Environments Using LiDAR Fusion Data

Seitaro Yamada, Akira Kato

Chiba University, Japan

Scalable monitoring of deforestation-free supply chains via cloud-native remote sensing

Fatemé Ghafarian, Juliana Freitas Beyer, Margret Köthke, Melvin Lippe

Thünen-Institute for Forestry, Germany

A Multi-Source Remote Sensing Pipeline for Individual-Tree Phenotyping in Eucalyptus Breeding: Integrating UAV-LiDAR, MLS and Spectral Data

Natiele Caumo Mezacasa¹, Ricardo Cavalheiro², Aurélio Mendes Aguiar², Juan Acosta², Ana Dalla Corte¹

1: Universidade Federal do Paraná, Brazil; 2: North Carolina State University, United States of America

Combining MODIS and ASTER Data for Satellite based Super-Resolution with Generative Deep Learning

Simon Mueller, Paul Hagemann, Philipp Benner

Federal Institute for Materials Research and Testing (BAM), Germany

Effect of ratio between point cloud clipping size and field plot size on goodness-of-fit of forest attributes models based on LiDAR metrics

Joel Rodriguez-Ruiz¹, Adela Martínez-Calvo¹, Juan Alberto Molina-Valero^2,3, Peter Surový³, César Pérez-Cruzado¹

1: Proyectos y Planificación (PROEPLA), Departamento de Producción Vegetal y Proyectos de Ingeniería, Escuela Politécnica Superior de Ingeniería, Campus Terra, Universidade de Santiago de Compostela, 27002 Lugo, Spain; 2: Department of Spatial Sciences, Faculty of Environmental Sciences, Czech University of Life Sciences Prague, Kamýcká 129, 165 00 Prague, Czech Republic; 3: Faculty of Forestry and Wood Sciences, Czech University of Life Sciences Prague, Kamýcká 129, 165 00 Prague, Czech Republic

Improvement forest biodiversity assessment through Handheld Laser Scanning for precision forestmanagement

Serena Sofia¹, Marcello Miozzo¹, Serena Buscarini¹, Giovanna Sala²

1: D.R.E.AM. ITALIA company, Italy; 2: Università degli studi di Palermo, Italy

The Best Tool for the Fuel: Comparing 3D characterization approaches for forest understories

Iris Mire, Jessie Thoreson, Susan Prichard

University of Washington, College of the Environment, School of Environmental and Forest Sciences (SEFS), Seattle, WA, USA

Spatio-temporal analysis of the ecological characteristics of mountainous forests in the Republic of Korea

Peter Lee, Kyungmin Bien, Boyun Kang, Lin Yang

Hanyang University, Korea, Republic of (South Korea)

Understanding Wildfire Dynamics Using ECOSTRESS and Machine Learning

Swati Suman¹, Mark A. Cochrane¹, W. Matt Jolly², Patrick H. Freeborn²

1: University of Maryland Center for Environmental Science, Frostburg 21532,MD,USA; 2: USFS RMRS, Missoula Fire Science Laboratory, Missoula 59803, MT, USA

How close can we get? Comparing drone-based lidar and QSM estimates of tree dbh and biomass against in-situ measurements and allometric scaling models.

Derek T. Robinson, Chenxi Liu, Brandon Giura

University of Waterloo, Canada

Fusion of GEDI and ICESat-2 for Mapping Forest Canopy Height and Aboveground Biomass

Janaki Sandamali, Lana L. Narine

Auburn University, United States of America

Improving Biomass Estimates in Heterogeneous Rangelands

Hailey Schmidt Melzow^1,2, Javier Osorio Leyton^1,2, Sorin Popescu³, Horia Olariu³, X. Ben Wu³

1: Dept. of Rangeland, Wildlife, & Fisheries Management, Texas A&M University, United States of America; 2: Blackland Research and Extension Center, Texas A&M AgriLife Research, United States of America; 3: Dept. of Ecology and Conservation Biology, Texas A&M University, United States of America

Large-scale aboveground carbon mapping from multi-source remote sensing and AI in tropical savanna

Cesar Alvites Diaz¹, Carlos Alberto Silva¹, Denis Valle², Ana Paula Dalla Corte³, Inacio Bueno¹, Fabiano Rodrigues Pereira³, Veraldo Liesenberg⁴, Lucas Bielak Rezende³, Gabriel Máximo da Silva⁵, Carine Klauberg¹, Andrew Hudak⁶

1: Forest Biometrics, Remote Sensing and Artificial Intelligence Lab (SilvaLab). School of Forest, Fisheries and Geomatics Science, University of Florida, PO Box 110410 Gainesville, FL, USA 32611; 2: School of Forest, Fisheries, and Geomatics Sciences, University of Florida, Gainesville, FL, USA; 3: BIOFIX, Universidade Federal do Paraná, Avenida Prefeito Lothario Meissner, 632, Jardim Botânico, Curitiba, PR, BR 80210-170,; 4: Department of Forest Engineering, Santa Catarina State University (UDESC), Lages 88520-000, SC, Brazil; 5: Instituto Nacional de Pesquisas Espaciais (INPE), Av. Dos Astronautas, 1758 Jardim da Granja, São José Dos Campos, SP 12227-010, Brazil; 6: USDA Forest Service Rocky Mountain Research Station, Moscow, ID 83843

Assessing the accuracy of changepoint algorithms and vegetation index in detecting beetles related forest mortality.

Ogonna Eli¹, Paul Arellano¹, Monica Gaylord², Revanth Munugala¹, Michael Gowanlock¹, Chris Doughty¹, Christopher Hakkenberg¹, Scott Goetz¹, Alexander Shenkin¹

1: Northern Arizona University, United States of America; 2: Forest Health Protection, USDA Forest Service

Aspen leafminer detection in Interior Alaska from high-resolution satellite data using deep learning

Sumana Sahoo, Santosh Panda

Institute of Agriculture Natural Resources and Extension,University of Alaska Fairbanks

An Evaluation of UAV Lidar for Assessing Brown Spot Needle Blight Disease in Loblolly Pine

Swati Singh, Lana L. Narine, Richard Cristan

Auburn university

Evaluating superpixel algorithms for standing dead tree dealineation using aerial orthoimagery

Igor Pawelec, Pawel Hawrylo, Pawel Netzel, Jaroslaw Socha

University of Agriculture in Krakow, Poland

Structural Quality Recovery of Amazon Tropical Forests using Spaceborne LiDAR

Leo Haneda, Denis Valle

University of Florida, United States of America

Monitoring Post-Disturbance Forest Recovery across the Brazilian Amazon

Na Chen¹, Sherrie Wang^1,2

1: Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; 2: Institute for Data, Systems, and Society, Massachusetts Institute of Technology, Cambridge, MA 02139, USA

The (mis)measurement of forest edge effects using remote sensing

Matthew E. Fagan¹, Naomi B. Schwartz², Michael Alonzo³, Hasan Ahmed¹, Felipe Saad¹

1: University of Maryland, Baltimore County, United States of America; 2: University of British Columbia, Canada; 3: American University, United States of America

Using the proportion of primary forest in the landscape to model forest degradation in the tropics

Diana Parker¹, Matthew Hansen¹, Amy Pickens¹, Xinyuan Li¹, Svetlana Turubanova¹, Peter Potapov²

1: University of Maryland, United States of America; 2: World Resources Institute

Improving the attribution of forest canopy loss drivers using time series remote sensing and multi-modal foundation model

Feng Zhao

Northeast Forestry University, China, People's Republic of

Integrating Multi-Source Remote Sensing, Machine Learning and Policy Pathways for Forest Conservation in the Brazilian Amazon

Carlos Souza Jr

Imazon, Brazil

linking in situ, airborne and satellite measurements of biophysical variables in tropical forests

Hao Tang, Elizabeth Rodríguez-Ronderos, Yi Li, Yuan Sun

National University of Singapore, Singapore

Quantifying tropical tree cover loss driven by cropland conversion

Xiao-Peng Song, Shi Jun Wee

University of Maryland, United States of America

Tracking forest aboveground biomass recovery following wind disturbance using PlanetScope-derived canopy structure and spectral data

Nisham Thapa, Lana L. Narine

College of Forestry, Wildlife and Environment, Auburn University, Auburn, AL, USA

Terrestrial LiDAR and Forest Inventory Integration for Improved Estimates of Wildfire Impacts on Forest Carbon

Christopher Tsz Hin Choi^1,2, Wade Tinkham³, Atticus Stovall^4,5, Anthony Grant Vorster^1,2

1: Graduate Degree Program in Ecology, Colorado State University, United States of America; 2: Natural Resource Ecology Laboratory, Colorado State University, United States of America; 3: Rocky Mountain Research Station, United States Forest Service; 4: NASA Goddard Space Center; 5: University of Maryland

UAS lidar enables quantification of forest coarse woody debris to support forest carbon management plans

Sarah Graves, Elliott Marsh, Philip Townsend

University of Wisconsin-Madison, United States of America

Recent changes in global forest biomass as viewed from space

Nezha Acil¹, Richard Lucas², Maurizio Santoro³, Heiko Balzter¹

1: University of Leicester, United Kingdom; 2: Aberystwyth University, United Kingdom; 3: GAMMA Remote Sensing, Switzerland

Sentinel-2 and Machine Learning Approaches for Early Detection of Forest Pest Outbreaks in Croatia

Luka Raspović, Branimir Radun, Ivan Tomljenović, Ivan Tekić

Oikon Ltd. – Institute of Applied Ecology, Croatia

Cloud-based forest health monitoring in Europe

Tamás Molnár¹, Svein Solberg², Mirela Beloiu-Schwenke³

1: University of Sopron, Hungary; 2: Norwegian Institute of Bioeconomy Research, Norway; 3: ETH Zürich, Switzerland

Forests from Space: Fusing Satellite Embeddings with NEON Field Data to Map Tree Mortality

Olivia Zhang, Di Yang

University of Florida, United States of America

Modeling the spatial distribution of southern pine beetle outbreaks across the southeastern United States

Ebere Loretto Anozie¹, Bo Song², David Coyle¹, Shaowu Bao³, Thomas Williams², Steven McNulty⁴, Carlyle Brewster¹, Brian Williams², Michael Gavazzi⁴

1: Department of Forestry and Environmental Conservation, Clemson University, SC, USA; 2: Baruch Institute of Coastal Ecology and Forest Science, Clemson University, SC, USA; 3: Coastal Carolina University, SC, USA; 4: USDA Forest Services, Southeast Climate Hub, Eastern Forest Environmental Threat Assessment Center, USA

Development Update on MOLI : Spaceborne Lidar Mission

Rei Mitsuhashi

JAXA, Japan

GEDI and the Path from Sampling to Monitoring: Forest Structure in the Next Generation of Active Missions

Ralph Dubayah

University of Maryland, United States of America

The BIOMASS mission: status and first results after 1 year in orbit

Klaus Scipal, Clement Albinet, Cristiano Lopes, Muriel Pinheiro, Bjorn Rommen

European Space Agency

The Earth Dynamics Geodetic Explorer (EDGE) mission: Tracking change in the 3D structure of terrestrial ecosystems using satellite laser altimetry

John Armston¹, Helen Amanda Fricker², J. Bryan Blair³, Scott Luthcke³

1: University of Maryland, College Park, MD, USA; 2: Scripps Institution of Oceanography, La Jolla, CA, USA; 3: NASA Goddard Space Flight Center, Greenbelt, MD, USA

Characterizing fuels in 3D: scaling measurements and inputs for fire behavior and smoke modeling

Susan Prichard¹, Iris Mire¹, Maureen Kennedy¹, Krakoff Noah¹, Redford Hannah¹, Parsons Russell², Silva Carlos³, Skowronski Nicholas⁴, Thoreson Jessica¹

1: University of Washington, USA; 2: Missoula Fire Sciences Laboratory, USDA Forest Service Rocky Mountain Research Station, USA; 3: University of Florida, USA; 4: USDA Forest Service Washington Office

From Planar Intercepts to Point-Based Insights: 3D Fuel Characterization for Southwestern Forests and Woodlands

Andrew Sánchez Meador, Meagan Dreher

Ecological Restoration Institute, Northern Arizona University

TreeFlow: Generative Modeling of 3D Tree Structure for Canopy Fuel Characterization

Anthony Marcozzi

New Mexico Consortium, United States of America

Evaluating a novel understory vegetation segmentation method on airborne and terrestrial lidar point clouds

Hannah Redford, Susan Prichard, Rachel Deininger, Deborah Nemens, Chad Anderson, Lacey Hankin, Van R. Kane

University of Washington, United States of America

Monitoring the circumpolar boreal forest’s structure and shifts with ICESat-2 & HLS

Paul Montesano^1,2, Christopher Neigh¹, Laura Duncanson³, Joseph Sexton⁵, Min Feng⁵, Ali Zarringhalam³, Amy Neuenschwander⁴, Margaret Wooten^1,6, Mark Carroll¹

1: NASA Goddard Space Flight Center; 2: ADNET Systems, Inc; 3: U. Maryland-College Park Dept. of Geographical Sciences; 4: U. of Texas at Austin Center for Space Research; 5: TerraPulse, Inc.; 6: Science Systems and Applications, Inc.

Northward advance of the boreal forest confirmed by the Landsat record

Joseph Sexton, Min Feng, Panshi Wang, Paul Montesano, Leonardo Calle, Nuno Carvalhais, Benjamin Poulter, Matthew Macander, Michael Wulder, Margaret Wooten, William Wagner, Akiko Elders, Saurabh Channan, Christopher Neigh

terraPulse, Inc., United States of America

Mapping aboveground biomass and canopy height recovery following stand-replacing forest disturbances in Japan

Katsuto Shimizu, Shingo Obata, Keiko Fukumoto

Forestry and Forest Products Research Institute, Japan

Rapid operational monitoring of global tree cover change

Amy Pickens, Matthew Hansen, Zhen Song, Andrew Poulson, Anna Komarova, Antoine Baggett, Theodore Kerr, Aleksandra Mikus, Carolina Ortiz Dominguez, Alexandra Tyukavina, André Lima

University of Maryland, College Park; United States of America

Multi-temporal Lidar Workflow for Forest Change Mapping

Chelsea Scott¹, Sreeja Krishnamari¹, Viswanath Nandigam², Minh Phan², Cesar Alvites³, Carlos Alberto³

1: Arizona State University, United States of America; 2: University of California San Diego; 3: University of Florida

OpenForest4D - Cyberinfrastructure for Next-Generation Forest Structure and Biomass Monitoring

Viswanath Nandigam¹, Carlos Silva², Chelsea Scott³, Kai Lin¹, Minh Phan¹, Cesar Alvites², Inacio Bueno²

1: University of California San Diego; 2: University of Florida; 3: Arizona State University

Spaceborne remote sensing and AI highlight asymmetric canopy height change across southeastern US forests

Cesar Alvites Diaz¹, Carlos Alberto Silva¹, Jeffery B. Cannon², Jeff Atkis³, Ajay Sharma⁴, Viswanath Nandigam⁵, Chelsea Scott⁶, Inacio Bueno¹, Kody Brock¹, Alex Gaskin¹, Carine Klauberg¹, Marcos Longo⁷, Caio Hamamura⁸, Andrew Hudak⁹

1: Forest Biometrics, Remote Sensing and Artificial Intelligence Lab (SilvaLab). School of Forest, Fisheries and Geomatics Science, University of Florida, PO Box 110410 Gainesville, FL, USA 32611; 2: The Jones Center at Ichauway, Newton, GA, United States 39870; 3: USDA Forest Service, Vaudreuil-Dorion, Canada; 4: Auburn University, Auburn, United States; 5: San Diego Supercomputer Center, University of California San Diego; 6: Arizona State University; 7: Lawrence Berkeley National Laboratory, Berkeley, CA, United States; 8: Federal Institute of Education, Science and Technology of São Paulo, São Paulo, Brazil; 9: USDA Forest Service Rocky Mountain Research Station, Moscow, ID 83843

Mapping forest canopy height across the western United States using spaceborne lidar and multi-sensor data

Inacio Thomaz Bueno¹, Carlos Silva¹, Viswanath Nandigam², Chelsea Scott³, Cesar Alvites¹, Kai Lin², Minh Phan²

1: School of Forest, Fisheries, and Geomatics Sciences, University of Florida, Gainesville, FL 32611, USA; 2: San Diego Supercomputer Center, University of California San Diego, La Jolla, California 92093, USA; 3: School of Earth and Space Exploration, Arizona State University, Tempe, Arizona 85287, USA

How deep learning can enhance and expand forest resource mapping in Norway

Zsofia Koma¹, Oleg Antropov², Jukka Miettinen², Johannes Breidenbach¹

1: Norwegian Institute of Bioeconomy Research, Norway; 2: VTT Technical Research Centre of Finland

Joint development of remote sensing-based tools for forest management planning –Project “VorratAktuell”

Petra Adler¹, Philipp Eisnecker¹, Linus Wiestler¹, Arno Mattes²

1: Forest Research Institute Baden-Württemberg, Germany; 2: Regional Council Freiburg

Barriers in the Implementation of Close-Range Remote Sensing Technologies in Forestry

Krzysztof Stereńczak^1,2, Ahmet Öztürk³, Carlos Cabo⁴, Markus P. Eichhorn^5,6, Markus Hollaus⁷, Anna Iglseder⁷, Martin Mokroš⁸, Chiara Torresan⁹, Yunsheng Wang¹⁰

1: Forest Research Institute (IBL); 2: IDEAS Research Institute; 3: Karabük University; 4: University of Oviedo; 5: School of Biological, Earth and Environmental Sciences, University College Cork; 6: Sustainability Institute, University College Cork; 7: TU Wien; 8: University College London; 9: National Research Council of Italy; 10: Finnish Geospatial Research Institute FGI

Practical Forestry Insights from ALS, Sentinel and NFI

Mitja Skudnik^1,2, Jaka Križaj^1,2, Klemen Čotar³, Urša Kanjir⁴

1: University of Ljubljana, Biotechnical Faculty, Slovenia; 2: Slovenian Forestry Institute, Slovenia; 3: Flai d.o.o, Slovenia; 4: ZRC SAZU, Slovenia

Direct assessment of forest water status and water stress from satellite-based microwave measurements

Arthur Endsley

University of Montana, United States of America

Improved estimation of the interannual variability of dryland carbon and water fluxes

Matthew Dannenberg¹, Mallory Barnes², Joel Biederman³, Miriam Johnston^1,4, Susan Meerdink¹, Sophie Ruehr⁵, Russell Scott³, William Smith⁶, Park Williams⁷

1: School of Earth, Environment, and Sustainability, University of Iowa, Iowa City, IA, USA; 2: O'Neill School of Public and Environmental Affairs, Indiana University, Bloomington, IN, USA; 3: Agricultural Research Service, U.S. Department of Agriculture, Tucson, AZ, USA; 4: Appalachian Laboratory, University of Maryland Center for Environmental Science, Frostburg, MD, USA; 5: Carnegie Institution for Science, Stanford University, Stanford, CA, USA; 6: School of Natural Resources and Environment, University of Arizona, Tucson, AZ, USA; 7: Department of Geography, University of California, Los Angeles, CA, USA

Evaluating Carbon Uptake and Evaporative Cooling in Temperate Forests Using Remote Sensing and Flux Tower Data

Mallory Barnes, Xian Wang, Kim Novick

O'Neill School of Public and Environmental Affairs, Indiana University

Characterizing relationships between vegetation traits and land-atmosphere exchanges of CO2, CH4, and H2O across Mid-Atlantic coastal wetlands

Brandon Alveshere¹, Lisa Haber¹, Kelsey Huelsman², Mindy Priddy¹, Ryan Pavlick³, Shawn Serbin², Bruce Cook², Chris Gough¹

1: Virginia Commonwealth University; 2: NASA Goddard Space Flight Center; 3: NASA Headquarters