Multispectral terrestrial lidar : State of the Art and Challenges

The development of multispectral terrestrial laser scan-ning (TLS) is still at the very beginning, with only four instruments worldwide providing simultaneous three-dimensional (3D) point cloud and spectral measurement. Research on multiwavelength 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. Alt-hough the current number of applications is sparse, they already show that multispectral lidar technology has po-tential to disrupt many fields of science and industry due to its robustness and the level of detail available

Supercontinuum Lidar for Spectroscopic Sensing Applications

Light detection and ranging (lidar) is a well established optical remote sensing technique with varying applications including atmospheric, environmental, automotive and other industrial applications. Lidar generally employs a monochromatic light source, which typically restricts its measurement capability to one observable at a time. The advent of a broadband light source termed supercontinuum (SC), also known as "white laser", offers novel possibilities for simultaneous multispectral analysis owing to its broad spectral bandwidth and laser like properties such as spatial coherence. This thesis presents a new lidar system employing spectrally tailored SC light sources. The system exploits differential absorption between specific wavelength bands of the SC spectrum, enabling the first experimental demonstration of real-time simultaneous monitoring of flue gas parameters (including aerosol particle distribution, water vapor temperature and concentration) in an industrial biomass boiler. In the context of combustion diagnostics, this is particularly of great interest as real-time analysis of flue gas parameters is central to the optimization of the process efficiency and reduction of pollutants emission. The technique is extended towards a more generic hyperspectral remote sensing in the mid-infrared wavelength range, where molecules possess characteristic absorption features known as the molecular fingerprints. Robust hypersepctral identification of black plastic waste is demonstrated with the aid of a micro-electro-mechanical system (MEMS) tunbale Fabry-Pérot interferometer filter. This is significant for recycling processes, as detection of black plastics with conventional near infrared sensors is tedious due to their strong absorption. The results reported herein demonstrate excellent versatility and unique capability of supercontinuum lidar for robust diagnosis in combustion units and other industrial environments. Opening up novel perspective for real-time 3D analysis of industrial processes and other hyperspectral sensing applications

Hyperspectral LiDAR-Based Plant Spectral Profiles Acquisition : Performance Assessment and Results Analysis

In precision agriculture, efficient fertilization is one of the most important pursued goals. Vegetation spectral profiles and the corresponding spectral parameters are usually employed for vegetation growth status indication, i.e., vegetation classification, bio-chemical content mapping, and efficient fertilization guiding. In view of the fact that the spectrometer works by relying on ambient lighting condition, hyperspectral/multi-spectral LiDAR (HSL/MSL) was invented to collect the spectral profiles actively. However, most of the HSL/MSL works with the wavelength specially selected for specific applications. For precision agriculture applications, a more feasible HSL capable of collecting spectral profiles at wide-range spectral wavelength is necessary to extract various spectral parameters. Inspired by this, in this paper, we developed a hyperspectral LiDAR (HSL) with 10 nm spectral resolution covering 500~1000 nm. Different vegetation leaf samples were scanned by the HSL, and it was comprehensively assessed for wide-range wavelength spectral profiles acquirement, spectral parameters extraction, vegetation classification, and the laser incident angle effect. Specifically, three experiments were carried out: (1) spectral profiles results were compared with that from a SVC spectrometer (HR-1024, Spectra Vista Corporation); (2) the extracted spectral parameters from the HSL were assessed, and they were employed as the input features of a support vector machine (SVM) classifier with multiple labels to classify the vegetation; (3) in view of the influence of the laser incident angle on the HSL reflected laser intensities, we analyzed the laser incident angle effect on the spectral parameters values. The experimental results demonstrated the developed HSL was more feasible for acquiring spectral profiles with wide-range wavelength, and spectral parameters and vegetation classification results also indicated its great potentials in precision agriculture application

Ultra-Efficient On-Chip Supercontinuum Generation from Sign-Alternating-Dispersion Waveguides

Fully integrated supercontinuum sources on-chip are critical to enabling applications such as portable and mechanically-stable medical imaging devices, chemical sensing and LiDAR. However, the low-efficiency of current supercontinuum generation schemes prevent full on-chip integration. In this letter, we present a scheme where the input energy requirements for integrated supercontinuum generation is drastically lowered by orders of magnitude, for bandwidth generation of the order of 500 to 1000 nm. Through sign-alternating the dispersion in a CMOS compatible silicon nitride waveguide, we achieve an efficiency enhancement by factors reaching 3800. We show that the pulse energy requirement for large bandwidth supercontinuum generation at high spectral energy (e.g., 1/e level) is lowered from nanojoules to 6 picojoules. The lowered pulse energy requirements enables that chip-integrated laser sources, such as mode-locked heterogeneously or hybrid integrated diode lasers, can be used as a pump source, enabling fully integrated on-chip high-bandwidth supercontinuum sources

Radiometric Calibration of the Finnish Geospatial Research Institute Hyperspectral LiDAR

The algorithmic processing of multiwavelength sampled radiance data recorded by multispectral and hyperspectral LiDAR-instruments improves upon the accuracy of reflectance retrieval and target material characterization capabilities of the instrument. A simulation script was written to study different algorithmic waveform reconstruction procedures for intensity calibration of the Finnish Geodetic Research Institute hyperspectral LiDAR, considering environment of operation, processing speed, and digitization frequency. A Gaussian parametrization, a polynomial least squares, a cubic spline, and a Levenberg-Marquardt algorithm were analyzed in terms of acquiring waveform peak amplitude, spatio-temporal peak location, FWHM, and area parameters from the samples of an approximately 1 ns FWHM Gaussian pulse. The results show that the cubic spline algorithm is best suited for implementation with FGI-HSL, as it provides an error of $0.2575 \pm 0.191$\% in waveform peak amplitude retrieval at a sampling frequency of 4 GHz, and real-time processing capabilities at a pulse repetition frequency of 2 MHz. Based on the insight of this study, suggestions are given for algorithm choice depending on the spatio-temporal shape of the full-waveform and the required accuracy of waveform parameter retrieval as function of sampling frequency

Recovery of forest canopy parameters by inversion of multispectral LiDAR data

We describe the use of Bayesian inference techniques, notably Markov chain Monte Carlo (MCMC) and reversible jump MCMC (RJMCMC) methods, to recover forest structural and biochemical parameters from multispectral LiDAR (Light Detection and Ranging) data. We use a variable dimension, multi-layered model to represent a forest canopy or tree, and discuss the recovery of structure and depth profiles that relate to photochemical properties. We first demonstrate how simple vegetation indices such as the Normalized Differential Vegetation Index (NDVI), which relates to canopy biomass and light absorption, and Photochemical Reflectance Index (PRI) which is a measure of vegetation light use efficiency, can be measured from multispectral data. We further describe and demonstrate our layered approach on single wavelength real data, and on simulated multispectral data derived from real, rather than simulated, data sets. This evaluation shows successful recovery of a subset of parameters, as the complete recovery problem is ill-posed with the available data. We conclude that the approach has promise, and suggest future developments to address the current difficulties in parameter inversion

Empirical Studies on Multiangular, Hyperspectral, and Polarimetric Reflectance of Natural Surfaces

The reflectance factor is a quantity describing the efficiency of a surface to reflect light and affecting the observed brightness of reflected light. It is a complex property that varies with the view and illumination geometries as well as the wavelength and polarization of the light. The reflectance factor response is a peculiar property of each target surface. In optical remote sensing, the observed reflectance properties of natural surfaces are used directly for, e.g., classifying targets. Also, it is possible to extract target physical properties from observations, but generally this requires an understanding and modeling of the reflectance properties of the target. The most direct way to expand our understanding of the reflectance properties of natural surfaces is through empirical measurements. This thesis presents three original measurement setups for obtaining the reflectance properties of natural surfaces and some of the results acquired using them. The first instrument is the Finnish Geodetic Institute Field Goniospectrometer (FIGIFIGO); an instrument for measuring the view angle dependency of polarized hyperspectral reflectance factor on small targets. The second instrument is an unmanned aerial vehicle (UAV) setup with a consumer camera used for taking measurements. The procedure allows 2D-mapping of the reflectance factor view angle dependency over larger areas. The third instrument is a virtual hyperspectral LiDAR, i.e. a setup for acquiring laser scanner point clouds with 3D-referenced reflectance spectra ([x,y,z,R(λ)]). During the research period 2005 2011, the FIGIFIGO was used to measure the angular reflectance properties of nearly 400 remote sensing targets, making the acquired reflectance library one of the largest of its kind in the world. These data have been exploited in a number of studies, including studies dealing with the vicarious calibration of airborne remote sensing sensors and satellite imagery and the development and characterization of reflectance reference targets for airborne remote sensing sensors, and the reflectance measurements have been published as a means of increasing the general understanding of the scattering of selected targets. The two latter instrument prototypes demonstrate emerging technologies that are being used in a novel way in remote sensing. Both measurement concepts have shown promising results, indicating that, in some cases, it can be beneficial to use such a methodology in place of the traditional remote sensing methods. Thus, the author believes that such measurement concepts will be used more widely in the near future. Heijastuskerroin on kullekin kohteelle yksilöllinen ominaisuus joka kuvaa kohteesta heijastuneen valon määrää. Heijastuskertoimen arvo riippuu havainto- ja valaistusgeometriasta sekä valon aallonpituudesta ja polarisaatiosta. Useimmissa optisen kaukokartoituksen menetelmissä mitataan kohteiden heijastuskerrointa. Näitä heijastuskerroinhavaintoja käytetään suoraan esim. kohteiden luokittelussa. Kehittyneemmissä menetelmissä havainnoista on myös mahdollista irrottaa joitain kohteen fysikaalisia ominaisuuksia, mutta yleensä tämä edellyttää kohteen ymmärtämistä sekä valonsironnan mallintamista. Suorin tapa laajentaa ymmärrystä luonnon pintojen valonsironnasta on tehdä empiirisiä mittauksia. Tässä väitöskirjassa esitellään kolme mittalaitetta luonnon pintojen valonsironnan mittaamiseksi sekä näillä laitteilla kerättyjä tuloksia. Ensimmäinen esiteltävä mittalaite on Finnish Geodetic Institute Field Goniospectrometer (FIGIFIGO), jolla voidaan mitata kohteen sirottaman valon suuntariippuvuutta valon aallonpituuden sekä polarisaation funktiona. Toinen mittalaite on automaattinen miehittämätön helikopteri. Kopteriin asennetun kameran sekä kuvien yhdistämismenetelmän avulla maaston valonsironnan suuntariippuvuutta voidaan kartoittaa laajemmilla alueilla kuin FIGIFIGO:a käyttäen. Kolmas mittalaite on virtuaalinen valkean valon LiDAR, jolla voidaan mitata laboratoriokohteen 3D rakenne yhdessä heijastusspektrien kanssa ([x,y,z,R(λ)]). Tutkimusjakson (2005 2011) aikana FIGIFIGO:a on käytetty lähes 400 kaukokartoituskohteen sironnan suuntariippuvuuden mittaamiseen. Näillä mittauksilla kerätty datakirjasto on yksi maailman suurimmista ja kattavimmistaan lajissaan. FIGIFIGO-mittauksia on hyödynnetty useissa tutkimuksissa esim. satelliitti havaintojen ja kaukokartoitus sensoreiden lennonaikaisessa kalibroinnissa ja validoinnissa, sekä ilmakuvauksen heijastuskerroinreferenssikohteiden kehittämisessä. Mittaustulokset on myös julkaistu tieteellisissä julkaisuissa laajentaen yleistä ymmärrystä kaukokartoituskohteiden valonsironnasta. Kaksi jälkimmäistä mittalaitetta ovat prototyyppejä joilla on testattu ja demonstroitu uutta tekniikkaa jota ei ole aiemmin hyödynnetty kaukokartoituksessa tällä tavoin. Molemmat mittauskonseptit tuottivat lupaavia tuloksia mahdollistaen uudentyyppisten mittausten tekemisen. Saadut tulokset antavat ymmärtää että mittauskonseptien kehittämistä kannattaa jatkaa ja on todennäköistä että tämän kaltaiset mittausmenetelmät tulevat jo lähitulevaisuudessa leviämään laajempaan käyttöön kaukokartoituksessa

Empirical Studies on Multiangular, Hyperspectral, and Polarimetric Reflectance of Natural Surfaces

The reflectance factor is a quantity describing the efficiency of a surface to reflect light and affecting the observed brightness of reflected light. It is a complex property that varies with the view and illumination geometries as well as the wavelength and polarization of the light. The reflectance factor response is a peculiar property of each target surface. In optical remote sensing, the observed reflectance properties of natural surfaces are used directly for, e.g., classifying targets. Also, it is possible to extract target physical properties from observations, but generally this requires an understanding and modeling of the reflectance properties of the target. The most direct way to expand our understanding of the reflectance properties of natural surfaces is through empirical measurements. This thesis presents three original measurement setups for obtaining the reflectance properties of natural surfaces and some of the results acquired using them. The first instrument is the Finnish Geodetic Institute Field Goniospectrometer (FIGIFIGO); an instrument for measuring the view angle dependency of polarized hyperspectral reflectance factor on small targets. The second instrument is an unmanned aerial vehicle (UAV) setup with a consumer camera used for taking measurements. The procedure allows 2D-mapping of the reflectance factor view angle dependency over larger areas. The third instrument is a virtual hyperspectral LiDAR, i.e. a setup for acquiring laser scanner point clouds with 3D-referenced reflectance spectra ([x,y,z,R(λ)]). During the research period 2005 2011, the FIGIFIGO was used to measure the angular reflectance properties of nearly 400 remote sensing targets, making the acquired reflectance library one of the largest of its kind in the world. These data have been exploited in a number of studies, including studies dealing with the vicarious calibration of airborne remote sensing sensors and satellite imagery and the development and characterization of reflectance reference targets for airborne remote sensing sensors, and the reflectance measurements have been published as a means of increasing the general understanding of the scattering of selected targets. The two latter instrument prototypes demonstrate emerging technologies that are being used in a novel way in remote sensing. Both measurement concepts have shown promising results, indicating that, in some cases, it can be beneficial to use such a methodology in place of the traditional remote sensing methods. Thus, the author believes that such measurement concepts will be used more widely in the near future. Heijastuskerroin on kullekin kohteelle yksilöllinen ominaisuus joka kuvaa kohteesta heijastuneen valon määrää. Heijastuskertoimen arvo riippuu havainto- ja valaistusgeometriasta sekä valon aallonpituudesta ja polarisaatiosta. Useimmissa optisen kaukokartoituksen menetelmissä mitataan kohteiden heijastuskerrointa. Näitä heijastuskerroinhavaintoja käytetään suoraan esim. kohteiden luokittelussa. Kehittyneemmissä menetelmissä havainnoista on myös mahdollista irrottaa joitain kohteen fysikaalisia ominaisuuksia, mutta yleensä tämä edellyttää kohteen ymmärtämistä sekä valonsironnan mallintamista. Suorin tapa laajentaa ymmärrystä luonnon pintojen valonsironnasta on tehdä empiirisiä mittauksia. Tässä väitöskirjassa esitellään kolme mittalaitetta luonnon pintojen valonsironnan mittaamiseksi sekä näillä laitteilla kerättyjä tuloksia. Ensimmäinen esiteltävä mittalaite on Finnish Geodetic Institute Field Goniospectrometer (FIGIFIGO), jolla voidaan mitata kohteen sirottaman valon suuntariippuvuutta valon aallonpituuden sekä polarisaation funktiona. Toinen mittalaite on automaattinen miehittämätön helikopteri. Kopteriin asennetun kameran sekä kuvien yhdistämismenetelmän avulla maaston valonsironnan suuntariippuvuutta voidaan kartoittaa laajemmilla alueilla kuin FIGIFIGO:a käyttäen. Kolmas mittalaite on virtuaalinen valkean valon LiDAR, jolla voidaan mitata laboratoriokohteen 3D rakenne yhdessä heijastusspektrien kanssa ([x,y,z,R(λ)]). Tutkimusjakson (2005 2011) aikana FIGIFIGO:a on käytetty lähes 400 kaukokartoituskohteen sironnan suuntariippuvuuden mittaamiseen. Näillä mittauksilla kerätty datakirjasto on yksi maailman suurimmista ja kattavimmistaan lajissaan. FIGIFIGO-mittauksia on hyödynnetty useissa tutkimuksissa esim. satelliitti havaintojen ja kaukokartoitus sensoreiden lennonaikaisessa kalibroinnissa ja validoinnissa, sekä ilmakuvauksen heijastuskerroinreferenssikohteiden kehittämisessä. Mittaustulokset on myös julkaistu tieteellisissä julkaisuissa laajentaen yleistä ymmärrystä kaukokartoituskohteiden valonsironnasta. Kaksi jälkimmäistä mittalaitetta ovat prototyyppejä joilla on testattu ja demonstroitu uutta tekniikkaa jota ei ole aiemmin hyödynnetty kaukokartoituksessa tällä tavoin. Molemmat mittauskonseptit tuottivat lupaavia tuloksia mahdollistaen uudentyyppisten mittausten tekemisen. Saadut tulokset antavat ymmärtää että mittauskonseptien kehittämistä kannattaa jatkaa ja on todennäköistä että tämän kaltaiset mittausmenetelmät tulevat jo lähitulevaisuudessa leviämään laajempaan käyttöön kaukokartoituksessa