Light Detection And Ranging (LiDAR) instruments make use of the extreme directionality of laser light, which enables measurement of distances with high spatial accuracy. Airborne Laser Scanning (ALS) is based on LiDAR range measurements conducted between an aircraft and the object of study [1
]. Recent ALS instruments mostly use monochromatic lasers to measure surface topography and for object characterization. ALS produces a 3D point cloud (x,y,z) of the surveyed target area, and the cloud represents the coordinates of the object. The intensity (I) value is also recorded for each point, either as the echo amplitude (proportional to the number of photons received by the detector over a given period of time) or as the complete echo waveform [2
]. Traditionally, the intensity data has mainly been used for matching images and laser strips, and rough classification and recognition of points and objects. However, recent the improvements in radiometric calibration [2
] have significantly improved the use of the data. The use of Terrestrial Laser Scanners (TLS) has also increased, and the number of applications, as well as information on TLS performance and range-data accuracy, is constantly increasing [7
Recent advances in nonlinear fibre optics and compact pulsed lasers have brought to the market light sources that are extremely broadband, yet as directional as laser light. These supercontinuum laser sources produce directional broadband light by making use of cascaded nonlinear optical interactions in an optical fibre [8
], and they can be used to simultaneously measure distance and the reflectance spectrum, which has been the basis for recent efforts at developing hyperspectral LiDAR [10
Current techniques for producing 3D point clouds with spectral intensity information are based on combining the laser-scanner data with passive spectroscopic sensing, e.g., aerial images or passive imaging spectrometry [11
], or using separated semiconductor laser diodes as the laser source [12
]. These approaches enable the classification of laser points for object recognition, but there are several practical problems. These include discrete spectral band, inaccuracy in registration, and time-based variation between measurements. Also, active hyperspectral imaging applications without range information have been developed [10
]. The idea behind hyperspectral LiDAR is that it would enable simultaneous hyperspectral imaging and laser scanning by the same instrument without any registration problems arising between the data sets, and it would produce a point cloud combined with hyperspectral intensity [x,y,z,I(λ)], where I(λ) represents intensity (I) as a continuous function of wavelength (λ).
The objective of this paper is to demonstrate the use of a spectral range-finding system using two channels in two different applications: determination of the Normalized Difference Vegetation Index (NDVI) of a Norway Spruce (Picea abies) tree, and obtaining the target range. The NDVI is defined as: NDVI = [NIR-RED]/[NIR+ RED], where NIR is the target reflectance within the near-infrared wavelength range, and RED is the reflectance within the visible wavelength range. The system is different from the currently available dual or multi wavelength LiDAR applications because the wavelengths can be selected from within the supercontinuum (or detector) wavelength range. The system configuration is presented in Section 2. The experiments are outlined in Section 3, and the Results and Discussion are provided in Section 4.