Abstract
Abstract. Recently multispectral LiDAR became a promising research field for enhanced LiDAR classification workflows and e.g. the assessment of vegetation health. Current analyses on multispectral LiDAR are mainly based on experimental setups, which are often limited transferable to operational tasks. In late 2014 Optech Inc. announced the first commercially available multispectral LiDAR system for airborne topographic mapping. The combined system makes synchronic multispectral LiDAR measurements possible, solving time shift problems of experimental acquisitions. This paper presents an explorative analysis of the first airborne collected data with focus on class specific spectral signatures. Spectral patterns are used for a classification approach, which is evaluated in comparison to a manual reference classification. Typical spectral patterns comparable to optical imagery could be observed for homogeneous and planar surfaces. For rough and volumetric objects such as trees, the spectral signature becomes biased by signal modification due to multi return effects. However, we show that this first flight data set is suitable for conventional geometrical classification and mapping procedures. Additional classes such as sealed and unsealed ground can be separated with high classification accuracies. For vegetation classification the distinction of species and health classes is possible.
Highlights
Commercial airborne laser scanning (ALS) systems are commonly monochromatic systems recording either discrete echoes or the full waveform (FWF) of the reflected laser beam
Spectral patterns are used for a classification approach, which is evaluated in comparison to a manual reference classification
Based on the manual classification of the datasets, we looked at the 8 bit scaled channel histograms and the pseudo normalized difference vegetation index (NDVI) for the main classes
Summary
Commercial airborne laser scanning (ALS) systems are commonly monochromatic systems recording either discrete echoes or the full waveform (FWF) of the reflected laser beam. Douglas et al (2015) apply the so called dual wavelength Echidna LiDAR (DWEL), which is a TLS scanner operating with 1,064 nm and 1,548 nm wavelengths. They use the system for an outdoor experiment separating canopy (leafs) from tree trunks calculating a normalized difference of channel intensity. Puttonen et al (2015) present a study on an outdoor scanning experiment with different high vegetation species. They calculate several vegetation indices relating them to leaf area index, chlorophyll in leafs and biomass estimates. In a time series experiment of 26h, selected channels (545.5, 641.2, 675.0, 711.0, 741.5, 778.4, 978.0) are used to investigate the influence of sunlight on spectral and geometrical properties and the normalized difference vegetation index (NDVI)
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