Characterizing local forest structural complexity based on multi-platform and -sensor derived indicators

作者：Patrick Kacic, Ursula Geßner, Christopher R. Hakkenberg, Stefanie Holzwarth, Jörg Müller, Kerstin Pierick, Dominik Seidel, Frank Thonfeld, Michele Torresani, Claudia Kuenzer · 发表于：Ecological Indicators · 年份：2025 · DOI：10.1016/j.ecolind.2025.113085 · 被引用次数：16 · 研究领域：Forest Ecology and Biodiversity Studies、Remote Sensing and LiDAR Applications、Forest ecology and management

Global climate change, biodiversity decline, and increasing disturbances are challenging the health and resilience of forests. In this regard, forest managers have sought to promote enhanced structural complexity (ESC) which utilizes the positive correlation between structural complexity and biodiversity or resilience to inform management practices. In light of these concerns, we integrated remote sensing data from multiple platforms and sensors to test the potential for quantifying different levels of structural complexity in temperate forests. This analysis was conducted in the context of the BETA-FOR project, where silvicultural manipulations of forest structure replicate silvicultural or natural disturbances. BETA-FOR includes a wide-range of standardized treatments across representative Central European broad-leaved forests, which are sub-divided into aggregated (gap felling) and distributed treatments (selective thinning) in combination with varying deadwood structures. This study provides a novel analysis of ESC from complementary remote sensing perspectives in order to bridge scales among structural complexity indicators. Remotely sensed observations comprise in-situ measurements (mobile and terrestrial laser scanning), as well as spaceborne observations from various sensors (including Sentinel-1 radar, Sentinel-2 multispectral, and GEDI lidar). We found moderate to strong inter-platform correlations among structural complexity metrics (|r| > = 0.6) between mobile las...