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Extraction of landscape features from LiDAR data has been studied widely in the past few years. These feature extraction methodologieshave been focussed on certain types of features only, namely the bare earth model, buildings principally containing planar roofs,trees and roads. In this paper, we present a methodology to process LiDAR data through DBSCAN, a density based clustering method,which extracts natural and man-made clusters. We then develop heuristics to process these clusters and simplify them to be sent to avisualization engine

the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences

HEURISTICAL FEATURE EXTRACTION FROM LIDAR DATA AND THEIR VISUALIZATION