Data and code for: Identifying fine-scale habitat preferences of threatened butterflies using airborne laser scanning

Jan Peter Reinier De Vries, Zsófia Koma, Michiel F. WallisDeVries & W. Daniel Kissling
Aim: Light Detection And Ranging (LiDAR) is a promising remote sensing technique for ecological applications because it can quantify vegetation structure at high resolution over broad spatial extents. Using country-wide airborne laser scanning (ALS) data, we test to what extent fine-scale LiDAR metrics capturing low vegetation, medium-to-high vegetation and landscape-scale habitat structures can explain the habitat preferences of threatened butterflies at a national extent. Location: The Netherlands. Methods: We applied a machine learning (random forest)...
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