Individual Tree Crown Segmentation and Classification of 13 Tree Species Using Airborne Hyperspectral Data

Mapping Individual Tree Species in an Urban Forest Using Airborne Lidar Data and Hyperspectral Imagery

0099-1112/12/7810–1079/$3.00/0 © 2012 American Society for Photogrammetry and Remote Sensing Abstract We developed a neural network based approach to identify urban tree species at the individual tree level from lidar and hyperspectral imagery. This approach is capable of modeling the characteristics of multiple spectral signatures within each species using an internally unsupervised engine, an...

Tree-Species Classification in Subtropical Forests Using Airborne Hyperspectral and LiDAR Data

Accurate classification of tree-species is essential for sustainably managing forest resources and effectively monitoring species diversity. In this study, we used simultaneously acquired hyperspectral and LiDAR data from LiCHy (Hyperspectral, LiDAR and CCD) airborne system to classify tree-species in subtropical forests of southeast China. First, each individual tree crown was extracted using ...

Forest Species Classification and Tree Crown Delineation Using Quickbird Imagery

Efficient forest management requires detailed knowledge of forest stands, including species information and individual tree parameters. Remote sensing data are increasingly being used to investigate forest classification at both coarse and fine levels. In this paper, we first examined the capability of QuickBird multispectral imagery for species level forest classification using eCognition soft...

Individual tree species identification using LIDAR- derived crown structures and intensity data

Individual tree species identification using LIDAR-derived crown structures and intensity data

Urban tree species mapping using hyperspectral and lidar data fusion