Abstract
Laser scanning systems that simultaneously measure multiple wavelength reflectances integrate the strengths of active spectral imaging and accurate range measuring. The Finnish Geodetic Institute hyperspectral lidar system is one of these. The system was tested in an outdoor experiment for detecting man-made targets from natural ones based on their spectral response. The targets were three camouflage nets with different structures and coloring. Their spectral responses were compared against those of a Silver birch (Betula pendula), Scots pine shoots (Pinus sylvestris L.), and a goat willow (Salix caprea). Responses from an aggregate clay block and a plastic chair were used as man-made comparison targets. The novelty component of the experiment was the 26-h-long measurement that covered both day and night times. The targets were classified with 80.9% overall accuracy in a dataset collected during dark. Reflectances of four wavelengths located around the 700 nm, the so-called red edge, were used as classification features. The addition of spatial aggregation within a 5-cm neighborhood improved the accuracy to 92.3%. Similar results were obtained using a set of four vegetation indices (78.9% and 91.0%, respectively). The temporal variation of vegetation classes was detected to differ from those in man-made classes.
Highlights
1.1 BackgroundOver the previous decade, new studies have begun to discuss the convergence of two popular and well-established remote sensing techniques, namely spectral imaging and light detection and ranging (LiDAR)
The Birch stem and the chair spectra that were separated with a priori thresholds in Normalized Difference Vegetation Index (NDVI) and red edge position linear interpolation (REP Li) clearly have a different median spectrum compared to other targets
This study tested the Finnish Geodetic Institute (FGI) Hyperspectral lidar (HSL) and its capability to discern man-made objects from natural ones based on their spectral response
Summary
New studies have begun to discuss the convergence of two popular and well-established remote sensing techniques, namely spectral imaging and light detection and ranging (LiDAR). Both techniques are being used in a wide range of different remote sensing applications. They both have limitations that prevent their effective use in all measurement settings. Some laser scanning instruments alter their transmission intensity so as to further improve their ranging accuracy, but this limits the usability of their intensity values.[1,2] Since the strengths of each of the two techniques complement the main weaknesses of the other, their combined usage offers clear synergies for obtaining the information, e.g., classification, required in an accurate analysis of complex environments
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