Radiometric information offers valuable insights into the surface and material properties of remote targets. Such information can be obtained along with the surface geometry by laser scanning. However, local variations in the surface geometry and orientation can introduce a bias in the radiometric data, related to the angle of incidence (AoI). We demonstrate a supercontinuum-based hyperspectral laser scanning approach for high-precision distance measurements, and its applicability to mitigate the AoI effect by enabling an enhanced data-driven radiometric correction of the acquired intensities. Our experiments utilize a supercontinuum (SC) spectrally broadened to 570 to 970 nm from a 780 nm frequency comb. Distance measurements are derived from the differential phase delay of the intermode beat notes, while the backscattered reflection spectrum is captured using a commercial spectrometer over the spectral range of the SC output. We obtain hyperspectral point clouds with sub-mm range noise on natural targets (gypsum board and leaves of a plant used herein) placed at a distance of 5 m. The high-precision range measurements allow for correctly estimating the surface orientation and modeling the impact of the AoI on the acquired radiometric data. The estimated model is applied to correct the acquired hyperspectral signatures, which are further exploited to compute various vegetation indices commonly used as plant health indicators. Our results illustrate enhanced information content on the direct three-dimensional mapping of such spectral data of plant leaves with a reduced AoI bias. These results highlight new opportunities for future research into remote sensing of vegetation and material probing with increased sensitivity.
Multispectral light detection and ranging (LiDAR) is an emerging active remote sensing technique that combines distance and spectroscopy measurements. The reflectance spectrum is known to enable material classification. However, the spectrum also depends on other surface parameters, particularly roughness. Herein, we propose an extension of multispectral to polarimetric multispectral LiDAR and introduce unpolarized and linearly polarized reflectance spectra as additional features for classifying materials and roughness. Using a bench-top prototype instrument, we demonstrate the feasibility and benefit of acquiring unpolarized and linearly polarized reflectance spectra. We analyze and interpret the spectra obtained with two different spectral resolutions (10 and 40 nm) from measurements on test specimens consisting of five different materials with two different levels of surface roughness. Using a linear support vector machine, we demonstrate the potential of the different features for enabling material and roughness classification. We find that the unpolarized reflectance spectrum is well suited for classifying materials, and the linearly polarized one for classifying roughness. In both cases, the performance is much better than using a standard reflectance spectrum offered by multispectral LiDAR. We identify polarimetric multispectral LiDAR as a technology that may significantly enhance surface and material probing capabilities for remote sensing applications.
We demonstrate a supercontinuum-based hyperspectral laser scanning technique that provides high-precision distance measurements of natural surfaces along with their reflectance signature over the broad spectral range of the supercontinuum (SC) output. The SC used in our experiments is spectrally broadened to 570-970 nm from a 780 nm mode-locked femtosecond laser. Distance measurements are carried out by monitoring the differential phase delay of the intermode beat notes obtained from direct photodetection of the SC, while the backscattered reflection spectrum is acquired using a commercial spectrometer. We achieve a single-point range precision below 10 μm on natural targets (gypsum board and leaves of a plant used herein) placed at a stand-off distance of 5 m. Our results demonstrate the acquisition of hyperspectral point clouds together with sub-mm range noise on the scanned surface. This range performance is comparable to commercial state-of-the-art terrestrial laser scanners which traditionally employ a monochromatic laser source.We show the benefit of enhanced range precision toward correctly estimating the surface orientation and for radiometric calibration of the acquired intensities. Initial results illustrate the direct 3D mapping of spectral data of plant leaves with a reduced angle of incidence-related bias, highlighting new opportunities for future research into remote sensing of vegetation.
Multispectral LiDAR is an emerging active remote sensing technique that combines distance and spectroscopy measurements on light reflected from the surface at the respective measurement point. It is known that the reflectance spectrum can be used for material classification. However, the spectrum also depends on other surface parameters, particularly surface roughness. Herein, we propose an extension of multispectral to polarimetric multispectral LiDAR and introduce polarized and unpolarized reflectance spectra as additional features for classifying materials and roughness. We demonstrate the feasibility and the benefit using a bench-top prototype instrument which allows acquiring standard, polarized and unpolarized reflectance spectra, in addition to distance, in 33 spectral channels with 10 nm bandwidth between 580 and 900 nm. We analyze and interpret the raw spectra obtained from measurements on test specimens consisting of five different materials (PE, PVC, PP, sandstone, limestone) with two different levels of surface roughness. Using a linear support vector machine (SVM) we demonstrate the potential of the different features for independent material and roughness classification. The results indicate that the unpolarized reflectance spectrum increases the material classification accuracy by 50% as compared to a standard spectrum, and that the polarized spectrum actually allows classifying roughness. We interpret the results as a strong indication that multispectral polarimetric LiDAR enables deriving practically relevant additional information on surfaces with high spatial resolution through remote sensing.
Polarimetric LiDAR combines polarimetry and non-coherent optical ranging techniques to complement the acquisition of geometrical information with material characteristics. In recent decades, polarimetric LiDAR has been widely explored in material probing, target detection, and object identification. These approaches have so far mainly relied on implementations using a single or very few wavelengths. In this work, we propose, develop and evaluate a polarimetric femtosecond-laser LiDAR that enables extracting multispectral polarization signatures on 7 spectral channels of 40 nm spectral bandwidth and 33 spectral channels of 10 nm spectral bandwidth in the visible and near-infrared range. Multispectral polarization signatures of five material specimens (cardboard, foam, plaster, plastic, and wood board) are obtained and used as input features on a linear support vector machine classification algorithm. The results show that extending polarimetric probing to multiple spectral channels improves the classification capabilities with respect to single-wavelength approaches. The combination of different spectral signature dimensions (polarization, reflectance, and distance) that can be derived from LiDAR measurements is also analyzed, with results indicating their capability to support challenging classification tasks.
Reflectorless electro-optical distance measurement (RL-EDM) relies on measuring the round-trip time of optical signals transmitted from the instrument and reflected by natural surfaces. It is the backbone of laser scanning technology, which allows easily digitizing the environment and obtaining 3d models that represent the geometry of the scanned objects. However, the measured distances do not refer to single, well-defined target points at the object surface but rather correspond to a weighted average of effective distances within the respective footprint of the laser beam. This increases the uncertainty of the measurements and may cause systematic deviations significantly exceeding the mm-or sub-mm level precision that would otherwise be attainable with EDM technology. In this paper we introduce a numerical simulation of the measurement process for phase-based RL-EDM with I/Q-demodulation assuming a Gaussian beam profile. The beam is discretized into a fixed number of rays for each of which the corresponding phase delay and attenuation are calculated. The I- and Q-components are obtained by integration over the footprint taking the beam profile into account. By deflection of the beam into incrementally changed spatial directions we extend the simulation to one of the 3d scanning process. The scanned surfaces are represented by triangular irregular meshes (TINs) with high spatial resolution. Each triangle is associated with a reflectivity, as a starting point for the modelling of surface properties. The simulation takes the interplay between the energy distribution within the laser footprint, the surface geometry and the surface reflectivity into account. Herein, we use the simulation framework to study the effects of the angle of incidence, of surface curvature and of mixed pixels in absence of measurement noise. The results indicate that the angle of incidence at a planar surface and the surface curvature within the footprint are on the order of 0.1 mm or less for small footprint and angles of incidence below about 60 deg. If the footprint and the angle of incidence are very large the biases may reach mm-level, however even then the impact of measurement noise and surface roughness will typically exceed these biases, such that they are negligible. On the other hand we show using simulations and real scans of a cylinder in front of a planar background, that the impact of mixed pixels or beams only partially hitting an object may introduce large biases and is practically relevant.
Measuring the propagation delay of optical signals reflected by the illuminated surfaces is an established approach to non-mechanical distance estimation and the basis for 3d laser scanning. We have in the past extended a technique using the intermode beat notes obtained from a femtosecond laser to a coherent ultra-broadband source. Using cooperative targets, we have shown that this may enable inline correction of atmospheric delays by using a multispectral configuration and exploiting atmospheric dispersion. In this work, we enhance the scope by providing a first demonstration of successful application to reflectorless measurements on natural targets. This extension is relevant because of two aspects: (i) the field of applications of reflectorless distance measurement is much wider (in particular through laser scanning) than for highly accurate measurements to prisms, and (ii) the approach offers the opportunity to simultaneously acquire delay and spectral signatures of both delay and power thus allowing to combine distance measurement with material probing. We present a table-top experimental set-up that uses a coherent femtosecond laser supercontinuum to probe the displacement and multispectral relative distance of various material samples on 5 spectral bands of 50 nm in the visible and near-infrared regions. Using integration times of about 30 ms, we have achieved a distance measurement accuracy of better than 50 μm with promising perspectives regarding scalability to practical distances. Comparative measurements on 5 different materials additionally yielded repeatable material-dependent profiles in the multispectral relative distances, whose combination with reflectance estimations may allow mitigating surface related uncertainties and remotely identifying materials.
The intermode beats generated by direct detection of a mode-locked femtosecond laser represent inherent high-quality and high-frequency modulations suitable for electro-optical distance measurement (EDM). This approach has already been demonstrated as a robust alternative to standard long-distance EDM techniques. However, we extend this idea to intermode beating of a wideband source obtained by spectral broadening of a femtosecond laser. We aim at establishing a technological basis for accurate and flexible multiwavelength distance measurement. Results are presented from experiments using beat notes at 1 GHz generated by two bandpass-filtered regions from both extremes of a coherent supercontinuum ranging from 550 to 1050 nm. The displacement measurements performed simultaneously on both colors on a short-distance setup show that noise and coherence of the wideband laser are adequate for achieving accuracies of about 0.01 mm on each channel with a potential improvement by accessing higher beat notes. Pointing and power instabilities have been identified as dominant sources of systematic deviations. Nevertheless, the results demonstrate the basic feasibility of the proposed technique. We consider this a promising starting point for the further development of multiwavelength EDM enabling increased accuracy over long distances through dispersion-based integral refractivity compensation and for remote surface material probing along with distance measurement in laser scanning.
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