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Insights from the Unseen - Occlusion in Forest Laser Scanning
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Abstract
Laser scanning is a powerful tool for assessing the structural complexity of forests and its role in ecosystem processes and functioning. Laser scans are however highly affected by occlusion (where objects block laser pulses), resulting in data gaps within the 3D representation of the forest. Although occlusion is a well-known and frequently discussed challenge for estimating forest structural information from laser scanning data, it is rarely quantified. Here, we describe the concept of occlusion and distinguish different types. We examine the primary causes of occlusion, discuss the role of forest structure, viewpoint arrangement, and laser system properties along with platform-specific challenges. We further present comprehensive strategies to mitigate and recent tools for detecting occlusion in laser scanning acquisitions. Finally, we highlight a broad range of research avenues for occlusion mapping ranging from uncertainty quantification, data completion, and intelligent autonomous laser scanning acquisition. By raising awareness of occlusion and showcasing its methodological and practical implications, this work aims to inspire new advances in the assessment of forest structure through laser scanning.
DOI
https://doi.org/10.31223/X5N16X
Subjects
Environmental Monitoring, Forest Sciences, Other Forestry and Forest Sciences
Keywords
LiDAR, Occlusion, point cloud quality, forest structure, raytracing, volume exploration, ULS, MLS, TLS
Dates
Published: 2025-09-24 00:33
Last Updated: 2025-09-24 19:31
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