Abstract

In the work, a fully automatic approach for vegetation delineation using ALS data is presented. Nowadays, in Slovakia, aerial images and satellite scenes are used for this purpose. For vegetation identification, the measurement of local transparency and roughness directly in 3D point cloud was used. The aim was the identification of groups of trees with area bigger than 0.1 ha and individual trees. On the experimental area, 33 polygons representing groups of trees and 120 individual trees were identified. For groups of trees the accuracy of identification was 100%. For comparison, an area with reference polygons, which were manually vectorised by the operator on the orthophotos with spatial resolution 30 cm, was used. The average difference in the area was –0.26%, with standard deviation ±8.17%. The distance of borders of reference polygons and polygons derived from ALS data was also compared, average distance for border parts that fall inside the reference polygons was 2.24 m with standard deviation of ±2.8 m. The average distance for borders parts that fall outside of the reference polygons was 1.84 m with standard deviation ±2.04 m. The accuracy of individual trees identification was 98%.

Highlights

  • The development of airborne laser scanning (ALS) took place during the 1970s and 1980s, and suitable scanning mechanisms were derived during the 1990s

  • Airborne laser scanning is an active method of remote sensing (RS) which measures the time of laser pulse between the sensor and target

  • It was shown that the automated method of ALS data processing presented in the paper can be used for vegetation mapping

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Summary

Introduction

The development of airborne laser scanning (ALS) took place during the 1970s and 1980s, and suitable scanning mechanisms were derived during the 1990s. Airborne laser scanning is an active method of remote sensing (RS) which measures the time of laser pulse between the sensor and target. High point density of ALS allows the creation of highly accurate digital surface models (DSM), and digital terrain models (DTM) (Hollaus et al 2005). The ALS can be considered as the most accurate method for mapping land surface by RS; it provides rapid and dense collection of data points up to subdecimeter measurement precision (Gallay et al 2012). The big advantage of ALS, according to applications in forestry, is the partial penetration of laser pulses through the canopy cover

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