Stephanie Bohlman
Papers
1
Total Citations
70
H-Index
1
About
Stephanie Bohlman is an ecologist whose research bridges remote sensing, forest ecology, and data accessibility. Her work focuses on developing and democratizing tools for individual tree detection and forest monitoring, particularly using UAV-based lidar and structure-from-motion (SfM) data. Her most-cited paper, "Individual tree detection using UAV-lidar and UAV-SfM data: A tutorial for beginners" (2021, 70+ citations), exemplifies her commitment to lowering technical barriers for researchers and practitioners, providing clear, reproducible workflows for extracting tree-level information from aerial imagery. Beyond this tutorial, Bohlman has made significant contributions to understanding tropical forest dynamics, including tree species distribution, carbon cycling, and the impacts of disturbance. Her research often integrates field measurements with high-resolution remote sensing to scale ecological insights from individual trees to landscapes. With a career spanning over two decades, she has published extensively on forest structure and function, influencing both conservation strategies and methodological standards in forest ecology. Bohlman’s work is widely cited for its practical utility and rigorous ecological grounding, making her a key figure in the intersection of technology and forest science.
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Top Papers
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