ForestVis: Visualization of 3D Forestry Point Clouds
Authors
Benjamin Powley (Linnaeus University), Petra Horváth (Linnaeus University), Basam Dahy (Linnaeus University), Nivan Ferreira (Universidade Federal de Pernambuco), Johan E.S. Fransson (Linnaeus University), Andreas Kerren (Linköping University), Claudio D. G. Linhares (Linnaeus University), Amilcar Soares (Linnaeus University)
Presentation
- Session
- Let's dig into the data (from France)
- Time
- Wednesday, Nov 11, 08:24 – 08:36 (US/Eastern) · session 08:00 – 09:30
- Location
- Hall America north
Keywords
Forestry Visualization, 3D Point Clouds, LiDAR, NDVI, Vegetation Monitoring.
Abstract
Forestry presents complex, irregular environments that are underrepresented in the visualization literature, despite the increasing availability of large-scale LiDAR and multispectral datasets. Extracting meaningful information from this data requires analyzing subtle structural and physiological variations among individual trees, a task that remains challenging due to the irregular, multi-layered nature of forests. In this paper, we present a visualization-driven approach for the interactive exploration and analysis of 3D forestry point clouds at the tree level, enriched with Normalized Difference Vegetation Index (NDVI) metrics. Our web-based system, entitled ForestVis, enables users to navigate dense forest environments, query individual tree attributes, and analyze vegetation metrics within their spatial context. The system design is informed by a semi-structured interview with forestry domain experts, from which we derive a set of analytical tasks emphasizing tree-centric abstractions, interactive exploration, and scalability to large datasets.} Through illustrative use cases, we show how the system supports applications such as precision forestry, biodiversity monitoring, and detection of tree stress. More broadly, this work highlights the potential of interactive visualization providing novel tools and frameworks for ecological research and sustainable forest management. We evaluate ForestVis through two expert studies: a qualitative study of usability and analytical reasoning, and a quantitative study reporting objective task measures together with benchmarks of rendering, streaming, and interaction performance across two hardware configurations. Our evaluation suggested that our tool is effective in helping domain experts explore specific forest tasks, in large forest point cloud datasets, while maintaining computational performance. Our findings suggest that different point cloud rendering styles are suited to different tasks, whether analyzing individual trees or groups of trees, and interactive filtering helped experts relate vegetation indices to the point-cloud instance segmentation and to tree height.
For Practitioners
ForestVis is a 3D interactive web-based visualization system for tree-level forestry analysis. Our research could be of interest to practitioners in fields such as forest management, ecological research, biodiversity monitoring, data science and forest science. This paper provides a qualitative and quantitative evaluation of a visualization system for forest point clouds that could help to inform practitioners on developing, or selecting their own visualizations for forest data. Practitioners could apply the performance testing metrics to evaluate which visualization techniques are suitable for their own data and better understand the performance implications of techniques such as interactive filtering of point clouds for web-based visualization.