Dr. Feng Zhao studies the interactive effects of natural (i.e., climate change and disturbances) and anthropogenic (i.e., forest management and socio-economic) drivers on the forest ecosystems, with an emphasis on the timely and accurate mapping of forest disturbances, as well as their long-term ecological consequences, in the face of climate change. She has extensive experiences in combining field data, multi-source remote sensing data, and deep learning models to characterize forest change dynamics across scales. Her email is fzhao@nefu.edu.cn

Alba Viana-Soto is a postdoctoral researcher at Earth Observation for Ecosystem Management at Technical University of Munich. She is a geographer by training with a specialization in remote sensing and her research focuses on understanding the disturbance and recovery dynamics of forest ecosystems using remote sensing data (optical and Lidar) and Artificial Intelligence, from local to large-scale analysis.

Wojciech Krawczyk is a Ph.D. candidate at Faculty of Forestry, University of Agriculture in Krakow (Poland) focused on applications of spaceborne remote sensing data in forest change monitoring.

Dr Paweł Hawryło works as an assistant professor in the Department of Forest Resources Management, Faculty of Forestry, University of Agriculture in Krakow, Poland. His scientific background is mainly in applications of remote sensing for forest resource inventory and monitoring. His previously published research focused primarily on using airborne laser scanning (ALS) and digital aerial photogrammetry (DAP) data for forest resources inventory and calibration of height growth models of forest stands. His scientific interests also include monitoring of forest health and modelling forest mortality with applications of remote sensing. Currently, he is focused on modelling tree- and stand-level growth and mortality in high temporal resolution by integrating various types of input data, including observations from real-time-monitoring sensors working in the Internet of Things infrastructure, weather and climatic observations, ALS data, and dense time series of multispectral satellite imagery.

Luiz Cosimo is a doctoral student at the Swedish University of Agricultural Sciences (SLU), based in the Department of Forest Resource Management - Division of Forest Remote Sensing. The focus of his research is to advance in the monitoring of forest disturbances using remote sensing technologies. His recent work is about early detection or bark beetle attack at the individual-tree level using multi- and hyperspectral drone images.

Daniele Marinelli is a researcher at the Forest Ecology Unit of Fondazione Edmund Mach. The research activity is devoted to the development of automatic methods for remote sensing data analysis with a focus on multispectral images and LiDAR point clouds, considering both airborne and spaceborne sensors. Currently, he is focusing on the analysis of optical time-series for forest monitoring and disturbances detection. He received the Ph.D. in Information and Communication Technologies (cum laude) from the University of Trento, Italy, in 2019. He is recipient of the prizes for the 2015 Best Italian master Thesis and 2020 Best Italian Ph.D. Thesis in the area of remote sensing awarded by the the Italy Chapter of the IEEE GRSS. He got the Second Place in the Student Paper Competition at the 2018 IEEE IGARSS held in Valencia (Spain). He was awarded the IEEE GRSS Letters Prize Paper Award in 2023.