Realistic virtual forests for understanding forest disturbances and recovery from space

作者：Kim Calders, Martin Herold, Jennifer Adams, John Armston, Benjamin Brede, Wout Cherlet, Zane Cooper, Karun Dayal, Pieter De Frenne, Shaun R. Levick, Patrick Meir, Niall Origo, Cornelius Senf, Luna Soenens, Louise Terryn, Wouter A.J. Van den Broeck, Mikko Vastaranta, Hans Verbeeck, Ludovic Villard, Mathias Disney · 发表于：ISPRS Journal of Photogrammetry and Remote Sensing · 年份：2025 · DOI：10.1016/j.isprsjprs.2025.06.031 · 被引用次数：3 · 研究领域：Remote Sensing and LiDAR Applications、Forest Management and Policy、Fire effects on ecosystems

Forests worldwide are undergoing large-scale and unprecedented changes in terms of structure and composition due to land use change and natural disturbances. We have some understanding of how disturbances impact forest structure. Still, we lack knowledge of the structural impact at fine spatial and temporal resolution, as well as across large spatial extents. Here, we provide a perspective on new approaches to observe, quantify and understand forest disturbances and recovery from space by using time series of the most detailed 3D virtual forest models that aim to digitise real-life forests fully. These virtual forests are important for enhancing our fundamental understanding of how we observe forest disturbance and recovery monitoring from space. We define virtual forests in the context of this paper as explicit 3D reconstructed models that are parameterised so they can be used and manipulated for radiative transfer modelling. Realistic virtual forests can be created through empirical reconstruction of explicit forest structure measured by terrestrial laser scanning, coupled with radiometric parameterisation. We argue that these realistic virtual forests, capturing the temporal dimension of forest disturbances, combined with physically-based radiative transfer modelling, provide a critical link between detailed in situ observations and large spatial coverage from satellite observations.