Multispectral terrestrial lidar

The development of multispectral terrestrial laser scanning (TLS) is still at the very beginning, with only four instruments worldwide providing simultaneous three-dimensional (3D) point cloud and spectral measurement. Research on multi wavelength laser returns has been carried out by more groups, but there are still only about ten research instruments published and no commercial availability. This chapter summarizes the experiences from all these studies to provide an overview of the state-of-the art and future developments needed to bring the multispectral TLS technology into the next level. Although the current number of applications is sparse, they already show that multispectral lidar technology has potential to disrupt many fields of science and industry due to its robustness and the level of detail available. important input for analyzing the multispectral laser returns, the main focus of this chapter is in the simultaneous capture of spectra and target 3D geometry. The most obvious advantage of multispectral lidar has already been shown in the pioneering studies (cf. Wichmann et al., 2015): no time gaps or registration errors exist between different colors (or spectral channels) or between geometric (topography) and spectral features, which improves the results compared to the traditional approach of combining point clouds with hyperspectral imagery (e.g., Guo et al., 2011). Also, the target identification capability of active hyperspectral imaging enables a wide variety of applications. But the prospect of mapping spectral properties in 3D over the target and in the same spatial resolution as conventional lidars have not yet been fully utilized or even understood. Many of the studies on multispectral laser scanning have so far focused on spectral performance without including the spatial interpretation of the point clouds. For example, Du et al. (2016) present leaf nitrogen retrieval with a 32 channel lidar, but the topographic aspect is not considered. A similar approach was presented in Li et al., (2014), who also focused on leaf spectral indices rather than point clouds. However one-shot acquisition of point cloud and spectral data will crucially increase the level of detail and information content available from the measurements. There is also the prospect of getting non-destructive and large scale data on the properties that have so far been measurable with destructive means only (Hakala et al., 2015), but this idea still needs comprehensive studies with improved instruments, as well as systematic laboratory reference to be established as a method. Radiometric calibration of lidar intensity has been studied for more than a decade by now. A comprehensive review on radiometric calibration methods, along with the basic physical concepts is provided in Kashani et al. (2015). They classify the levels of intensity processing according to the accuracy and information quality of the calibrated laser returns, starting from the digital numbers (raw intensity) available directly from the detector (level 0). Level 1 comprises the range or incidence angle correction, while in level 2, scaling or normalization, such as histogram correction, is carried out. Full radiometric calibration (level 3) results in values comparable to target reflectance, and requires the use of reference targets with known reflectance. The level 3 process is also termed as absolute radiometric calibration (Briese et al., 2012). Kashani et al. (2015) also identified some important knowledge gaps, such as difficulty in comparison with intensities obtained with different lidar instruments or variation between different wavelengths. That, plus the fact that lidar intensity is still somewhat underutilized, especially for TLS (Li et al., 2016, Schofield et al., 2016) has been one of the drivers for the development of multiple wavelength laser scanners. Radiometric calibration has sometimes been seen as a preliminary step towards multispectral lidar (Matikainen et al., 2017). Using multiple channels also enables the use of spectral ratios, which may in some cases help overcome the problem that the laser backscatter intensity does not directly represent the hemispherical reflectance and hence the target physical properties. Simultaneous data acquisition at different wavelengths enables the comparison of spectral differences or trends, which can sometimes be done without absolute radiometric calibration using only the range-corrected or normalized return intensity (Kashani et al., 2015, Li et al., 2016). This kind of approach usually works when changes in target properties are observed within the same experiment or with the same instrument. However, even the relative measurements are prone to errors caused by inaccuracy in sampling or calibration of the laser beam at different wavelengths. It has also turned out that the radiometric calibration is instrument specific (Calders et al., 2017). In any case, rigorous radiometric calibration is necessary to be able to interpret physically the reflectance measurements available from multispectral TLS. It is also critical for combining and comparing results from different experiments. This chapter aims to provide a comprehensive overview on the status of multispectral TLS so far. It also discusses some important challenges related to multispectral laser scanning in particular, although many of these problems are familiar to monochromatic TLS as well. Even though the number of currently existing multispectral TLS instruments is sparse, those few available already indicate the vast potential of this new technology. The chapter is organized as follows: Section 2 reviews the state-of-the-art in multispectral TLS and identifies some difficulties commonly met in instrument development and data analysis. Applications are summarized in Section 3, while Section 4 highlights some future aspects related to the technology. 2 MULTISPECTRAL TERRESTRIAL LIDAR: STATE-OF-THE-ART AND CHALLENGES Even though the idea of active hyperspectral sensing has been available for almost two decades (Johnson et al., 1999), the first multi-wavelength terrestrial laser scanner instruments were presented by Douglas et al. (2012), Powers and Davis, 2012, Hakala et al., (2012), and Gaulton et al., (2013). Research efforts for multispectral TLS technologies are slowly increasing. Some applications have been previously summarized by Eitel et al., (2016) and Hancock et al., (2017). Much of the research has focused on vegetation (Wichmann et al., 2015). 2.1 State-of-the-art Dualor multi-wavelength 3D TLS point clouds have been published so far by four projects: the Dual-Wavelength Echidna Lidar (DWEL) (Douglas et al., 2012) and the Salford Advanced Laser Canopy Analyser (SALCA) (Danson et al., 2014) are dual wavelength instruments. The Finnish Geospatial Research Institute Hyperspectral Lidar (FGI HSL) (Hakala et al., 2012), and the spectral LADAR by Powers and Davis (2012) have multiple channels. All these are full waveform digitizing scanning lidars. In addition to these four, there are multispectral lidar studies that have mainly focused on spectral or waveform analysis of the laser return. Table 1 lists all these research efforts, followed by a more detailed description on each project in this section. Table. 1: Summary of multispectral lidar projects. The top four provide one-shot multispectral point clouds, whereas the others focus on spectral analysis of pointwise or two-dimensional depth images. Project Laser Source Channels (nm) Detector/Sampling Application