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Fusion of aerial optical and LiDAR data has been a popular problem in remote sensing as they carry complementary information for object detection. We describe a stratified method that involves separately thresholding the normalized digital surface model derived from LiDAR data and the normalized difference vegetation index derived from spectral bands to obtain candidate image parts that contain different object classes, and incorporates spectral and height data with spatial information in adoi:10.1109/igarss.2016.7730879 dblp:conf/igarss/TasarA16 fatcat:xncsg3bsuvdonhedhwigqfinuq