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A graph cut approach to 3D tree delineation, using integrated airborne LiDAR and hyperspectral imagery
[article]
2017
arXiv
pre-print
Recognising individual trees within remotely sensed imagery has important applications in forest ecology and management. Several algorithms for tree delineation have been suggested, mostly based on locating local maxima or inverted basins in raster canopy height models (CHMs) derived from Light Detection And Ranging (LiDAR) data or photographs. However, these algorithms often lead to inaccurate estimates of forest stand characteristics due to the limited information content of raster CHMs. Here
arXiv:1701.06715v1
fatcat:53v6tlbokng5hlklp5ohqnu7eu