2016
DOI: 10.1109/jstars.2016.2546251
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Estimation of 2-D Clutter Maps in Complex Under-Canopy Environments From Airborne Discrete-Return Lidar

Abstract: Detection of near-ground objects occluded by above-ground vegetation from airborne lidar measurements remains challenging. Our hypothesis is that the probability of obstruction due to objects above ground at any location in the forest environment can be reasonably characterized solely from airborne lidar data. The essence of our approach is to develop a datadriven learning scheme that creates high-resolution 2D probability maps for obstruction in the under-canopy environment. These maps contain information abo… Show more

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