David Harding is an emeritus member of the Biospheric Sciences Laboratory at NASA Goddard Space Flight Center. He has 30 years of experience developing and utilizing advanced airborne and spaceflight laser altimeter systems, in particular for characterizing forest canopy structure. He was the NASA representative to the Puget Sound Lidar Consortium which conducted one of the first large-area ALSM projects. He has been the science lead for several NASA airborne lidars that established new measurement capabilities including SLICER, SIMPL and most recently CASALS. He has also contributed to the SLA, ICESat and ICESat-2 spaceflight lidar missions.

Géza Király was graduated as forest engineer, but specialised to remote sensing and GIS in an early carrier. He introduced many remote sensing methods in forestry, especially in Hungary. Ha was involved in several European and international projects. He started dealing with terrestrial and airborne laser scanning in the very early years, at the beginning of 2000, especially in Hungary. He have educated many forestry students for remote sensing and photogrammetry. He also educated surveying students in the last five years. He especially interested in forestry and nature conservation application of remote sensing, especially laser scanning.

Dr. Ran Meng is a professor at Harbin Insititue of Technology. Dr. Meng got his Ph.D. from the University of Utah and worked as a postdoctoral fellow at Brookhaven National Laboratory in the United States. He has long been engaged in the application research of remote sensing science and technology in Agroforestry informatisation, and his research interests include forest disturbance, plant stress, and smart agriculture. He was invited to serve as the Associate Editor of Remote Sensing of Environment, the Review Editor of Frontiers in Ecology and Evolution, the Guest Editor of Remote Sensing and Sensors.

Mr. Jeyavanan Karthigesu obtained his B.Sc. degree in Agricultural Science from the University of Jaffna, Sri Lanka, and his M.Phil. degree in Environmental Forestry from the University of Peradeniya, Sri Lanka. At present, he is pursuing a Ph.D. programme at the University of Tokyo, Japan in forest management using Unmanned Aerial Vehicle remote sensing technology. His special interest is to estimate the forest structural parameters in a complex mixed conifer-broadleaf forest in the University of Tokyo Hokkaido Forest, Northern Japan. He is a Senior Lecturer in the Faculty of Agriculture, University of Jaffna, Sri Lanka.

Dr. Dingfan Xing is a Postdoctoral Research Associate in the Department of Geography & Sustainability at the University of Tennessee, Knoxville, she earned her PhD degree in 2023 in Environmental Science at the College of Environmental Science and Forestry, State University of New York. Dingfan Xing’s research is directed to the application and development of statistical methods and the uncertainty evaluation for area estimation of forest characteristics and land cover. Specifically, her current research topics include: (1) Small area estimation of forest characteristics; (2) Uncertainty evaluation of sample-based area estimates. The first topic of her research focuses on applying model-assisted estimators to estimate the forest characteristics and improve the precision of the estimation by developing new statistical methods. The second topic of her research focuses on developing the advanced methods for estimating confidence intervals and total variance of the area estimation of land cover and land cover change.

Johannes Rahlf is aresearcher at the Norwegian National Forest Inventory (NFI), with a PhD from the Norwegian University of Life Sciences. He specializes in remote sensing and large-scale mapping of forest resources using both airborne and satellite 3D and optical data. Johannes is particularly interested in incorporating artificial intelligence into remote and proximal sensing for forestry and forest monitoring. As part of NIBIOs SmartForest center, he oversees the project's cloud service, ForestSens.com, facilitating the application of AI algorithms for sensor data processing.

Dr. Alexandra (Sasha) Tyukavina is an Associate Research Professor at the University of Maryland, College Park, USA. Sasha has over a decade of experience in mapping and sample-based estimation of forest disturbance dynamics, regionally and globally. The majority of her work is funded by and supports the Global Forest Watch program. Sasha's most notable research projects include sample-based estimation of forest loss drivers in the tropics and global mapping of forest loss due to fire. She is currently continuing to work on all things sample-based and forest loss-related, and leading a NASA-funded research project characterizing the global hotspots of forest loss using high-resolution data.

Dr. Michael Förster is a scientist in Vegetation Remote Sensing at the Technical University Berlin. He did his PhD on "„Integration of Geo-Information in Classification Processes of Satellite Imagery for NATURA 2000 Monitoring“. He worked as guest scientist at the University of Utrecht, the Joint Research Centre in Ispra, Italy. His work primarily explores ecosystem dynamics and plant properties through remote sensing data, aiming to develop innovative environmental indicators. He co-organized the last ForestSAT 2022 in Berlin.