Este trabalho, sendo pioneiro no Brasil, teve o intuito de efetuar uma investigação das nuvens cirrus na região Metropolitana de São Paulo (23,33ºS / 46,44ºW), SP, através do sistema MSP-Lidar para o período de Junho à Julho de 2007. Durante este período, foi verificada uma ocorrência de cirrus de aproximadamente 54% sobre o total de medidas efetuadas pelo sistema Lidar. Medidas com Lidar nos forneceram uma alta resolução espacial e temporal destas nuvens, permitindo assim caracterizá-las e classificá-las de acordo com as suas propriedades macro- e microfísicas. Para obter tais parâmetros, uma metodologia própria foi desenvolvida na recuperação dos dados de Lidar e uma robusta estatística foi aplicada para determinar as diferentes classes de cirrus. A metodologia adotada se resumiu basicamente (a) na determinação de períodos estacionários (ou observações) durante a evolução temporal de detecção de cirrus, (b) determinação da base e topo através de um valor limiar para o cálculo das variáveis macrofísicas (altitudes, temperaturas, espessuras geométricas), (c) aplicação do método da transmitância para cada camada de nuvem e a determinação das variáveis microfísicas (profundidade óptica e razão de Lidar). Neste processo, a razão de Lidar é calculada iterativamente até que haja a convergência da mesma. Análises estatísticas de multivariáveis foram efetuadas para a determinação das classes de cirrus. Estas classes são baseadas na espessura geométrica, altitude média e sua respectiva temperatura, a altitude relativa (diferença entre a altura da tropopausa e topo da nuvem) e a profundidade óptica. O uso sucessivo da Análise de Componentes Principais (PCA), do Método de Cluster Hierárquico (MCH) e da Análise de Discriminantes (AD) permitiu a identificação de 4 classes. Vale ressaltar que tais métodos foram aplicados somente para os casos identificados como camadas únicas de nuvens, pois não se observou significativamente a ocorrência de nuvens com multicamadas. A origem de formação das classes de cirrus encontradas, embora apresentando propriedades macro- e microfísicas distintas, foi identificada basicamente como a mesma, isto é, provenientes da injeção de vapor dágua na atmosfera por meio de sistemas frontais e seu respectivo resfriamento para a formação dos cristais de gelo. O mesmo mecanismo de formação também é atribuído aos jatos subtropicais. Uma análise em relação ao perfil de temperatura e a comparação com a literatura mostrou que as cirrus classificadas apresentam possivelmente cristais em forma de placas e colunas hexagonais. As razões de lidar (RL) calculadas também estão de acordo com a literatura. / This pioneer work in Brazil, aimed at investigating cirrus clouds in the metropolitan region of São Paulo (23.33 ºS / 46.44 ºW), SP, observed by the MSP-Lidar system in June and July 2007. During this period, cirrus clouds were observed during approximately 54% of the time of all Lidar measurements available. The Lidar provided measurements with high spatial and temporal resolution measurements of these clouds that allowed characterizing and classifying them according to their macro-and microphysical properties. For such parameters, a unique methodology was developed for the Lidar data retrieval and a robust statistic was applied to determine the different classes of cirrus. The following steps were adopted to characterize the observations: (a) the determination of stationary periods (or observations) during the time evolution of cirrus detection, (b) determination of the base and top of clouds through a so called threshold value to derive the macrophysical variables (altitude, temperature, geometrical thickness), (c) the application of the transmittance method for each layer and the determination of cloud microphysical variables (optical depth and Lidar ratio). In this process, the Lidar ratio is calculated iteratively until a convergence of this value is achieved. Multivariate statistical analyses were performed to determine the classes of cirrus. These classes are based on geometric thickness, average altitude and the respective temperature, relative altitude (difference between tropopause height and cloud top) and optical depth. The successive use of Principal Component Analysis (PCA), Hierarchical Clustering Method (HCM) and Discriminant Analysis (DA) allowed the identification of four classes of cirrus. It is important to point out here that such methods were applied only to cases identified as single layers of clouds, due to the rare occurrence of multilayered clouds. The origin of formation for the four cirrus classes, though they have distinct macro-and microphysical properties, was found to be basically the same, i.e., from the injection of water vapor in the atmosphere provided by frontal systems, followed by the cooling process to form ice crystals. The same formation mechanism is also attributed to the subtropical jet. An analysis of the temperature profile and comparison with the literature showed that the cirrus crystals possibly have the form of hexagonal plates and columns. The Lidar Ratio (LR) was also found to be in accordance with the literature.

Large area detectors for time correlated single photon counting (TCSPC) are nowadays being implemented in CMOS technology to benefit a large variety of applications including positron emission tomography (PET) and 3D laser ranging (LiDAR), exploiting the advanced timing and counting capabilities inside single chips. Single photon avalanche diodes (SPADs) and silicon photomultipliers (SiPMs) represent a great option to realise such detectors thanks to their exceptional timing resolution and the ability to be arranged into arrays. Recently, digital SiPMs (dSiPMs) have been introduced to improve the integration with CMOS technology overcoming limitations on the readout of analogue SiPMs and thus improving the photon resolution of the detector. This work presents a 14GSamples=s time-to-digital converter (TDC) to improve the throughput of dSiPM sensors commonly limited by the sampling rate of the timing/counting readout circuitry. The converter has been demonstrated on a test chip in 130nm CMOS imaging technology paired with a novel XOR-based 32 32 SPAD array single-channel detector. The overall achieved throughput equals 1GEvents=s demonstrated in a direct time-of-flight LiDAR experiment. By acquiring a number of photons significantly higher than one per laser pulse, this approach represents the first example in TCSPC of an input rate and conversion rate both higher than the excitation rate. The following part of the work presents a modelling analysis on how to match the achieved high sampling rate / throughput of the single-channel TDC to the performance of a SPAD array. The impact of a selection of dSiPM design parameters, such as photon detection efficiency, dead time and size of the SPAD cell, number of cells per single-channel, digital N-to-1 combining network and channel bandwidth, on the overall sensor throughput and the dynamic range has been characterised thanks to a computational Monte-Carlo simulator and useful equations describing each of the processes in the sensing chain. The pile-up effect, i.e. the event-loss causing non-linear distortions on the output signal, has been characterised on each element of the dSiPM and optimisations have been proposed. Event losses in the SPAD cells due to dead time, in the digital combining network due to network dead time and single-channel bandwidth have all been identified, simulated and described by analytical equations. All the results coming from the theoretical analysis have been reproduced in real dSiPM design thanks to a reconfigurable test chip realised in the same 130nm CMOS imaging technology specifically to validate the proposed theory. The manufactured test chip provides the very first direct comparison between OR-based and XOR-based single-channel dSiPM sensors highlighting the promising timing and counting performance of the newly introduced XOR-based dSiPM. Direct evidence of pile-up distortions and subsequent reduction through design optimisations are demonstrated. A recommended design flow for next generation dSiPMs is proposed at the end of the publication.

In an effort to investigate the role of turbulence in near-forward scattering, laboratory measurements of scattering on turbulent flow were carried out in a Rayleigh-Bénard convective tank. Particle Image Velocimetry and profiling thermistor temperature measurements are used to characterize the turbulent flow through determination of the large scale flow features, turbulent kinetic energy dissipation rates, and thermal dissipation rates. Polarized diffractometer measurements allow for determination of the turbulence-induced depolarization rate, which is comparable to that observed with polarimetric lidar. Measurements were made over a range of turbulent strengths, with Rayleigh number between 10^8 and 3*10^9, and with turbulent parameters corresponding to those characteristic of the oceanic mixed layer. Results show that the turbulence-induced depolarization rate is indirectly proportional to the strength of the turbulent flow, suggesting that light beam depolarization from turbulent flow may contain useful information regarding the smallest length scales of turbulent flow.

I denna rapport har mätningar från en lidar och mätningar från en meteorologisk mätmast jämförts. En undersökning har även gjorts för vilka atmosfäriska tillstånd som lidarn mäter bra och för vilka förhållanden den mäter mindre bra. Som referens används data från en mätmast, som antas vara korrekta. Platsen för mätningarna är över skog vilket medför mer komplex terräng än över plan mark. Olika filter har utvecklats för de atmosfäriska tillstånd då lidarn mäter sämre, för att filtrera bort de mest extrema förhållandena. Dessa filter filtrerar bort data med för mycket turbulens, låg eller negativ vertikal vinddifferens och liten återspridning. När återspridningen är liten blir antalet mätningar även litet, därför har data med litet antalet mätningar också filtrerats. Lidarn har en inbyggd korrektion för moln, denna har också undersökts och ett filter har utvecklats för data som korrigeras fel. Efter att data har filtrerats visar jämförelser mellan lidarns uppmätta horisontella vindhastighet och mastens uppmätta horisontella vindhastighet en bättre korrelation och ett mindre relativt fel. För högre höjder fås en mindre skillnad i vindhastighet mellan lidarn och masten än för lägre höjder. Jämförelse av turbulensintensitet visar också en bättre korrelation. Antalet data som blivit bortfiltrerat p.g.a. atmosfäriska tillstånd är ca 12 % för 70 m, 96 m och 138 m, för 39 m har 22 % blivit bortfiltrerat. Utifrån filtrerade data har även två olika metoder för att bestämma friktionshastigheten undersökts. Det visade sig att metoderna gav olika resultat. Den ena metoden gav sämre korrelation men bättre 1:1 förhållande medan den andra metoden gav en bättre korrelation men lidarn visade något lägre friktionshastighet än mastens mätningar.

Thèse de doctorat--Signal et images--Paris--ENST, 2006. / Bibliogr. p. 153-166. Résumé en français et en anglais.

This research analyzes the sensitivity of watershed attributes, and hydrological outputs to LiDAR derived DEM uncertainty introduced through spatial resolution, and LiDAR measurement errors. Sensitivity of watershed attributes to spatial resolution was determined through a scaling analysis at three sites; Mosquito Creek, Scotty Creek and Thomas Brook, with DEMs ranging from 1 to 50 m. Results at Scotty Creek showed the highest sensitivity of watershed area to spatial resolution, due to subtle changes in elevation which were below DEM uncertainty. Validation of the stream length at Thomas Brook showed discrepancies of 3.7 to 24.1% for the 1 to 50 m DEMs, compared to independent field observations. Sensitivity of SWAT derived hydrological outputs to DEM spatial resolution were determined through a scaling analysis of DEMs (1 - 50 m) at Thomas Brook watershed, over a five year simulation period. Results indicated monthly water yield was insensitive to DEM resolution, unless a change in area was also present. Sediment yield from the 50 m DEM showed a 24% reduction compared to the 1 m DEM. The 5 - 50 m DEMs also showed a reduction in channel deposition of 45 - 90 t, compared to the 1 m DEM. Sensitivity of terrain attributes, watershed attributes and hydrological outputs to LiDAR measurement errors were determined at the Thomas Brook watershed through the propagation of LiDAR sensor measurement errors with Monte Carlo simulations. Results showed that the uncertainty in the DEM, slope, and aspect were below 0.06 cm, 1.5° and 24.1° in 97.5% of grid cells, respectively. Watershed area and stream length resulted in relative standard deviations of <1% and 1.5%, respectively. However, sensitivity of watershed area increased in regions with elevation changes below DEM uncertainty and stream length uncertainty increased with decreasing stream length. SWAT simulated flow and sediment showed minor sensitivity to LiDAR measurement error in high flow months, and increased as flow decreased. Simulated sediment showed higher sensitivity to LiDAR measurement errors than flow, due to changes in the HRU slope class, which can shift the dominant HRU (Hydrological Response Unit) if a minimum HRU threshold area is implemented.

The recently commissioned CANDAC Rayleigh?Mie?Raman Lidar (CRL) in Eureka, Nunavut, finished its first winter measurement campaign in 2010, during which over 900 hours of data was collected. A comparison of several inversion techniques are shown to de- termine which one is most appropriate for the CRL aerosol and cloud analyses. Results of a newly implemented automatic beam steering program are shown and discussed. Measure- ments of water vapour and aerosols showed a distinct layering effect in the troposphere. Back trajectories of these layers are compared to the CRL measurements to determine origins of these layers. Measurements of significant aerosol concentrations in the lower stratosphere were seen during the campaign, which were from the Sarychev eruption in June of 2009. The aerosol evolution over Eureka is shown by using different ground-based and satellite-based instruments. Calculations using multi-wavelength aerosol and cloud measurements are used to give insight on aerosol and cloud particle properties.

Riparian areas are ecologically and economically critical habitats in the Canadian Prairies. An estimated 80% of riparian zones in North America are threatened by anthropogenic development. While riparian conservation is integrated into agricultural, watershed, and forestry best management practices across Canada, existing riparian health assessments are reliant on resource-intensive field surveys. The objective of this thesis was to develop a riparian health assessment using high-resolution remotely sensed imagery. Riparian health surveys were conducted along the La Salle River. High-resolution imagery and LiDAR data were integrated into an object-based image analysis of vegetation. Topographic analysis was conducted using a high-resolution DEM. These data were input into a linear discriminant classifier to model riparian health. Riparian health models containing both vegetation and topographic variables, and only vegetation variables, produced good agreement with field assessments. LiDAR data and the object-based image analysis method were successfully used to develop a remote riparian health assessment.

Due to infrequent and imprecise maintenance inspection in power-line corridors, accidents can be caused by interferences, for instance, surrounding trees. Transmission power-line inspection conventionally relies on the participation of ground personnel and airborne camera to patrol power-lines, and is limited by intensive labour, and difficult working conditions and management. Airborne light detection and ranging (LiDAR) has proven a powerful tool to overcome these limitations to enable more efficient inspection. Active airborne LiDAR systems directly capture the 3D information of power infrastructure and surrounding objects. This study aims at building a semi-automatic 3D reconstruction workflow for power-lines extracted from airborne LiDAR data of 138 kV transmission line corridors (500 m by 340 m) in Nanaimo, BC, Canada. The proposed workflow consists of three components: detection, extraction, and fitting. The power-lines are automatically detected with regular geometric shape using a set of algorithms, including density-based filtering, Hough transform and concatenating algorithm. The complete power-lines are then extracted using a rectangular searching technique. Finally, the 3D power-lines are reconstructed through fitting by a hyperbolic cosine function and least-squares fitting. A case study is carried out to evaluate the proposed workflow for hazard tree detection in the corridor. The results obtained demonstrate that power-lines can be reconstructed in 3D, which are useful in detection of hazard trees to support power-line corridor management.

Zugl.: Bayreuth, Univ., Diss., 2006