Analysis of full waveform LIDAR data for the classification of deciduous and coniferous trees
Top Cited Papers
- 25 February 2008
- journal article
- research article
- Published by Taylor & Francis Ltd in International Journal of Remote Sensing
- Vol. 29 (5), 1407-1431
- https://doi.org/10.1080/01431160701736448
Abstract
The paper describes a methodology for tree species classification using features that are derived from small‐footprint full waveform Light Detection and Ranging (LIDAR) data. First, 3‐dimensional coordinates of the laser beam reflections, the intensity, and the pulse width are extracted by a waveform decomposition, which fits a series of Gaussian pulses to the waveform. Since multiple reflections are detected, and even overlapping pulse reflections are distinguished, a much higher point density is achieved compared to the conventional first/last‐pulse technique. Secondly, tree crowns are delineated from the canopy height model (CHM) using the watershed algorithm. The CHM posts are equally spaced and robustly interpolated from the highest reflections in the canopy. Thirdly, tree features computed from the 3‐dimensional coordinates of the reflections, the intensity and the pulse width are used to detect coniferous and deciduous trees by an unsupervised classification. The methodology is applied to datasets that have been captured with the TopEye MK II scanner and the Riegl LMS‐Q560 scanner in the Bavarian Forest National Park in leaf‐on and leaf‐off conditions for Norway spruces, European beeches and Sycamore maples. The classification, which groups the data into two clusters (coniferous, deciduous), leads in the best case to an overall accuracy of 85% in a leaf‐on situation and 96% in a leaf‐off situation.Keywords
This publication has 17 references indexed in Scilit:
- Classifying individual tree species under leaf-off and leaf-on conditions using airborne lidarISPRS Journal of Photogrammetry and Remote Sensing, 2007
- Range determination with waveform recording laser systems using a Wiener FilterISPRS Journal of Photogrammetry and Remote Sensing, 2006
- Airborne laser scanning: Exploratory data analysis indicates potential variables for classification of individual trees or forest stands according to speciesISPRS Journal of Photogrammetry and Remote Sensing, 2005
- Identifying species of individual trees using airborne laser scannerRemote Sensing of Environment, 2004
- Practical large-scale forest stand inventory using a small-footprint airborne scanning laserScandinavian Journal of Forest Research, 2004
- The Laser Vegetation Imaging Sensor: a medium-altitude, digitisation-only, airborne laser altimeter for mapping vegetation and topographyISPRS Journal of Photogrammetry and Remote Sensing, 1999
- Use of Large-Footprint Scanning Airborne Lidar To Estimate Forest Stand Characteristics in the Western Cascades of OregonRemote Sensing of Environment, 1999
- Surface Lidar Remote Sensing of Basal Area and Biomass in Deciduous Forests of Eastern Maryland, USARemote Sensing of Environment, 1999
- The quickhull algorithm for convex hullsACM Transactions on Mathematical Software, 1996
- Watersheds in digital spaces: an efficient algorithm based on immersion simulationsIEEE Transactions on Pattern Analysis and Machine Intelligence, 1991