Im Rahmen der vorliegenden Arbeit wurden die Eigenschaften von atmosphärischen Aerosolpartikeln im tropischen Regenwald des Amazonasgebietes bestimmt. Dazu wurden die Daten einer fast einjährigen Lidarmesskampagne ausgewertet und diskutiert. Die Messungen wurden mit einem automatischen Mehrwellenlängen-Polarisations-Raman-Lidar im zentralen Amazonasbecken nahe Manaus, Brasilien, im Zeitraum von Januar bis November 2008 durchgeführt. Somit konnten erstmalig optische und mikrophysikalische Aerosoleigenschaften im Amazonasgebiet während der Regenzeit (ca. Dezember-Mai) und Trockenzeit (ca. Juni-November) höhenaufgelöst charakterisiert werden. Einleitend werden die meteorologischen Bedingungen im Amazonasgebiet erläutert und eine Literaturübersicht über Aerosolforschung in dieser Region gegeben. Das Messgerät sowie verschiedene Kalibrier- und Korrekturschemen, die zur Datenauswertung notwendig sind, werden vorgestellt. Auch Vergleiche mit anderen Messgeräten werden diskutiert. Diese zeigen, dass die aus den Lidarmessungen abgeleiteten Parameter von hoher Qualität sind. Anhand von Fallstudien werden mit Hilfe von Rückwärtstrajektorien und Satellitenmessungen typische Aerosolbedingungen am Messstandort diskutiert. Um die generellen Unterschiede zwischen Regen- und Trockenzeit zu quantifizieren, wird eine statistische Auswertung aller analysierten Lidarmessungen präsentiert. Die Analyse der Lidardaten zeigt, dass während der Regenzeit im Amazonasgebiet in ca. der Hälfte aller Fälle sehr saubere Bedingungen mit einer Aerosol Optischen Dicke (AOD) von weniger als 0.05 (bei 532 nm) vorherrschen können. Allerdings wurde in ca. 30% aller analysierten Fälle im Zeitraum von Januar bis Mai auch afrikanisches Aerosol, vornehmlich Saharastaub und Biomasseverbrennungsaerosol (BBA), am Messstandort detektiert. Dabei dominierte meist BBA die Aerosolpopulation, wie die Depolarisationsmessungen zeigten. In der Trockenzeit ist die Atmosphäre im Amazonasbecken hauptsächlich mit BBA aus Südamerika belastet. Daher ist die AOD im Durchschnitt um einen Faktor drei größ er als in der Regenzeit. BBA wurde zu dieser Jahreszeit regelmäßig bis zu einer Höhe von 4-6 km detektiert. Basierend auf den vorgestellten Langzeitmessungen werden erstmalig die optischen Eigenschaften von südamerikanischem BBA statistisch analysiert und diskutiert. / Continuous lidar measurements were performed in the Amazon rain forest for almost one year in 2008. The results of the automated multiwavelength-Raman-polarization lidar observations were presented in this dissertation. These measurements are the first long-term observations of the vertical aerosol structure ever made in the Amazon Basin. The advanced lidar observations were conducted 60 km north of Manaus in the central northern part of Amazonia. The area is widely covered with pristine rain forest. A HYSPLIT backward-trajectory analysis showed that the observations were representative on a regional scale for the central northern part of the Amazon rain forest. The general weather conditions in this region are characterized by a wet (December-June) and a dry season (July-November). During the dry season, a high fire activity occurs in Amazonia, which heavily influences the atmospheric conditions. With the lidar instrument, vertical profiles of the particle backscatter coefficient at 355, 532, and 1064 nm, of the particle extinction coefficient at 355 and 532 nm, and of the particle linear depolarization ratio at 355 nm can be determined. The results from the long-term lidar observations performed in Brazil contain a lot of new information about the aerosol conditions in the central northern Amazon Basin and corroborate certain findings from former aerosol measurements in Amazonia. It was shown for the first time that advection of Saharan dust together with biomass burning aerosol (BBA) from Africa occurred regularly throughout the wet season. In about one third (32%) of all lidar observations during the wet season, African aerosol was dominating the optical aerosol properties in Amazonia. The analysis of the vertical aerosol structure during such events revealed that the African aerosol arriving in the central northern Amazon Basin was usually trapped in the lowermost 3-3.5 km of the troposphere. To quantify the amount of Saharan dust and African smoke transported towards the lidar site, the dust contribution to the measured optical aerosol properties was separated by means of the measured particle depolarization ratio. This study led to the result that in about one half of the cases with African aerosol advection, smoke particles contributed to more than 50% to the total Aerosol Optical Depth (AOD). The smoke transport from Africa towards Amazonia occurred predominantly between January and April when the fire activity in Central Africa was highest. BBA is thus a major constituent of the aerosol plumes that are regularly transported from Africa towards Amazonia. This is a key finding of the presented study. During clean conditions, an AOD (532 nm) of less than 0.05 was observed and the aerosol was trapped in the lowermost 2 km of the troposphere. However, the analysis of the long-term data set revealed that these clean atmospheric conditions occurred in only 48% of all wet-season cases. One example for such background conditions was intensively discussed and it was shown that a major meso-scale rain event occurred in the Amazon region at the same time. This precipitation event was possibly partly responsible for the very low aerosol load. Two case studies from the dry season were presented for which BBA dominated the optical properties. In the first case, a comparable high aerosol load (AOD of 0.41) prevailed while in the second one, a medium aerosol load (AOD of 0.15) was observed. Aged BBA advected from regions south of the lidar site were identified to be the dominant aerosol species for both cases. However, very different geometrical, optical and microphysical properties of BBA (e.g., vertical layering, lidar ratio, Ångström exponent, effective radius, SSA) were observed on both days. In the first case, aerosol was present up to about 4.5 km. Extinction-related Ångström exponent s of about 1 and lidar ratios between 70 and 90 sr were found at different heights for the smoke aerosol. The BBA was highly absorbing (SSA of 0.81) at heights of the highest RH (85%), whereas above under dry conditions (RH=50%) only moderate absorption (SSA of 0.93) was detected. In the second case, smoke was detected up to 4.5 km, and Ångström exponent of about 2 and lidar ratios of 45-55 sr were measured in the aerosol layers. The BBA was only moderately absorbing indicated by SSA values between 0.92 and 0.94. The reason for the differences in the smoke properties could be the shorter travel time to the lidar site (<24 h), different aging processes (e.g., cloud/rain processing), or different burning conditions. In both cases, no depolarizing effects of the BBA could be observed. The strong contrast between the aerosol conditions in the dry season and the wet season were confirmed by the statistical analysis of all lidar observations in 2008. Due to the high BBA concentration in the atmosphere, the mean AOD of the dry season was found to be a factor of 3 higher than the mean AOD of the wet season (0.26 compared to 0.08 at 532 nm). Maximum AOD values were less than 0.55 (at 532 nm) and hence show that the lidar location was not in the direct vicinity of fire events. In only 7% of all cases in the dry season 2008, an AOD below 0.1 was observed. Also the maximum extinction and backscatter coefficient values in the dry season 2008 were 2-3 times higher than during the wet season of this year. The vertical aerosol distributions differ also significantly between the two seasons. In the wet season, the aerosol was mostly trapped in the lowermost 2.5 km, while in the dry season aerosol typically reached up to 4.5 km. Aerosol was occasionally detected up to 6.14 km in the dry season. The majority of the aerosol (95% of the AOD), however, was found to be on average below 2.3 km in the wet season and below 3 km in the dry season. During the wet season, lofted aerosol layers and multiple aerosol stratification was less frequent than in the dry season. The extent of BBA plumes during the dry season showed no correlation to the ML top height. Virtually uniform smoke haze layers were observed up to the AL top. Thus, pyro-convection and/or cloud-related mixing seem to be the major processes for the vertical distribution of BBA.

Geografinei informacijai apie erdvinį žemės paviršių kaupti pastaruoju metu vis dažniau naudojamas vietovės skenavimo lazeriu iš orlaivio metodas LIDAR (Light Detection and Ranging). Šiuo metodu gaunama nereguliari taškinė labai tanki trijų dimensijų žemės paviršiaus objektų išsidėstymą sumodeliuojanti geometrinė ir radiometrinė informacija. Tai gana neseniai atsiradęs būdas, naudojamas žemės topografijos duomenims užrašyti, kuris Lietuvoje dar tik pradedamas naudoti. Dėl to naudinga ištirti šio metodo patikimumą, palyginant su įprastais duomenų surinkimo metodais (GPS), ir įvertinti šio metodo panaudojimo galimybes. Darbe nagrinėjama nuotolinių tyrimų metodais (LIDAR) gautų duomenų patikimumo problema. Tyrimo tikslas – nustatyti įvairiais metodais gautų reljefo aukščių duomenų patikimumą, analizuojant Riešės upelio baseino reljefą. Tyrimo eigoje buvo surinkti įvairiais metodais gauti Riešės upelio baseino reljefo duomenys; atlikti natūriniai matavimai pasirinktuose kontroliniuose ploteliuose, naudojantis geodeziniais instrumentais; pagal nuotolinių tyrimų gautus rezultatus sudarytas skaitmeninis reljefo modelis ir įvertintas jų tikslumas. Darbe palyginus natūrinių matavimų ir nuotolinių tyrimų metodais gautus rezultatus įrodyta, jog nuotoliniais tyrimų metodais gauti duomenys yra patikimi ir juos galima naudoti baseino tūriui ir plotui skaičiuoti. / LIDAR terrain laser scanning technique is increasingly used in digital terrain model creation. This method provides dense uneven three-dimensional scatter geometric and radiometric information that simulates objects on earth’s surface. This is a relatively recent method used to record topographic data of the land. One of the key issues still associated with remote sensing methods is its reliability, which is why it is relevant to analyze and evaluate this aspect. This thesis aims at evaluating LIDAR data reliability, comparing them with data obtained by field measurements carried out at selected control areas using geodesic instruments. Riešės river basin area was selected as an object for the study and its elevation data have been investigated in the research. It was concluded that LIDAR data are reliable and can be used for the basin volume calculation. However, the size of the grid should be selected according to terrain relief.

Mobile Terrestrial LiDAR (MTL) is an active remote sensing technology that uses laser-based ranging and global positioning systems (GPS) to record 3D point location measurements on surfaces within and near transportation corridors, such as along a railroad track or a street. This thesis examines geovisualization for improving user-oriented workflows and also examines geographic object-based image analysis (GEOBIA) for the development of automated feature extraction. A LiDAR sensor-centric perspective during the data acquisition phase is used to organize data for the user and to transform the data into a 2D reference frame for object-oriented image analysis of MTL data. Organizing the display of MTL data relative to the scanner presented new opportunities for visualization techniques and was an effective method for communicating space that was scanned, or not, in an urban scene. It offers new avenues for quality assessment of MTL survey of urban environments by explicitly displaying gaps in data coverage. A number of techniques for navigating and visualizing data from a sensor-perspective are examined. A novel sensor-perspective transformation of MTL data from three to two dimensions enables analysis of MTL data in common GIS and image-processing environments. GEOBIA software (Definiens’ eCognition) is used to construct a procedural feature extraction workflow. The procedures are constructed with semantic classes, data processing rules and functions that drive geometric segmentation and feature recognition. Geometric regularities in urban scenes and knowledge about spatial and semantic relationships are incorporated into the rule set. The results are fluidly integrated back into a GIS environment. Investigation of alternative approaches to handling MTL data such as those carried out in this thesis are essential if this technology is to see widespread use. / Thesis (Master, Geography) -- Queen's University, 2011-05-24 13:10:15.198

Ces travaux s'articulent autour de la détection et de la prévision des phénomènes turbulents dans la couche limite atmosphérique. Nous proposons tout d'abord une méthode stochastique innovante de reconstruction locale de l'atmosphère. Nous utilisons des systèmes de particules pour modéliser l'écoulement atmosphérique et sa variabilité interne. L'apprentissage des paramètres turbulents et la mise à jour des particules se font à l'aide d'observations mesurées par un lidar Doppler 3D. Nous présentons ensuite une nouvelle méthode de descente d'échelle stochastique pour la prévision de la turbulence sous-maille. A partir du modèle en points de grille Meso-NH, nous forçons un système de particules qui évolue à l'intérieur des mailles. Notre méthode de descente d'échelle permet de modéliser des champs sous-maille cohérents avec le modèle en points de grille. Dans un troisième et dernier temps nous introduisons les problèmes de remontée d'échelle. La reconstruction de l'atmosphère modélise la turbulence dans un volume restreint qui couvre au plus quelques mailles des modèles météorologiques en points de grille. L'objectif de la remontée d'échelle est de construire une méthode d'assimilation de l'atmosphère reconstruite. En utilisant l'algorithme de nudging direct et rétrograde, nous explorons les problèmes liés à la taille du domaine observé. Nous proposons finalement un algorithme de nudging avec apprentissage de paramètre, illustré sur un cas simple. / Our work aims to improve the turbulent phenomena detection and forecast in the atmospheric boundary layer. First, we suggest a new stochastic method to reconstruct locally the turbulent atmosphere. Particle systems are used to model the atmospheric flow and its internal variability. To update particles and lean the turbulent parameters 3D Doppler lidar measurements are used. Then, a new stochastic downscaling technic for sub-grid turbulence forecast is presented. From the grid point model Meso-NH, a sub-grid particle system is forced. Here, the particles evolve freely in the simulated domain. Our downscaling method allows to model sub-grid fields coherent with the grid point model. Next, we introduce the upscaling issue. The atmosphere reconstruction covers at best few cells of meteorological grid point models. The issue is to assimilate the reconstructed atmosphere in such models. Using the back and forth nudging algorithm, we explore the problems induced by the size of the observed domain. Finally we suggest a new way to use the back and forth nudging algorithm for parameter identification.

Dans les bassins versants abrupts de montagne, de larges quantités de sédiments provenant des pentes escarpées viennent se déposer dans la partie supérieure des torrents et sont remobilisées par les laves torrentielles ou par charriage. Le but de ce travail était d'étudier le transport des sédiments grossiers dans les petits bassins versants torrentiels et d’analyser l’influence du stockage de ces sédiments dans le chenal sur les laves torrentielles. Cela a requis sur le terrain une intense surveillance géomorphologique des événements d'écoulement dans les bassins versants des torrents du Manival et du Réal, susceptibles de produire des laves torrentielles et du transport solide par charriage chaque année.Le bilan sédimentaire du Manival a été réalisé grâce à des mesures topographiques répétées entre les événements importants d’écoulements (sections transversales et relevés au scan laser terrestre). Deux évènements de laves torrentielles et plusieurs évènements de charriage ont été observés. La reconstitution de leur budget sédimentaire a révélé que la majeure partie de leurs volumes a été apportée par l'érosion du chenal. Les évènements de charriage de l’automne ont contribué à la recharge sédimentaire du chenal principal par le dépôt de grands bancs de gravier. Ce processus est fondamental au déclenchement de laves torrentielles lors des printemps et été suivants. Un décalage dans le temps des séquences érosion /dépôt a été observé entre les parties supérieure et inférieure du chenal, révélant un transfert discontinu de sédiments dans le bassin versant. Un modèle conceptuel de transfert des sédiments est proposé pour les différentes magnitudes d’écoulement.Dans le Réal, le volume de sédiment transporté est similaire à celui du Manival avec une augmentation importante du volume dans le chenal. La plus importante lave torrentielle observée a révélé une diminution en aval des hauteurs d'écoulement maximales, des contraintes de cisaillement, de la vitesse et de la résistance à l'écoulement. Cela suggère que le front de la lave torrentielle érode et déstabilise le chenal, mais qu’il ne peut pas transporter les matériaux en raison de sa concentration élevée en sédiments. La vague hyperconcentrée qui suit se charge des matériaux restants, croît en volume et fusionne avec la lave torrentielle en décélération. Le front et les vagues suivantes jouent un rôle essentiel pour l'érosion lors d'un événement de lave torrentielle.Les laves torrentielles ont créé une érosion significative à la variabilité spatiale importante alors que les déformations du lit induites par le charriage sont en équilibre. L’érosion du chenal par les laves torrentielles est contrôlée étroitement par la pente en amont et les conditions de stockage des sédiments et peut être prédite par une relation logarithmique. Les matériaux les plus sensibles à l'érosion dans le Manival sont les bancs de gravier non consolidés formés par le charriage. Ils constituent une surface lisse au sein du chenal rugueux qui peut être automatiquement cartographiée à partir de données de laser scan terrestre ou aérien. Ceci fournit une évaluation des zones sensibles à l'érosion dans un chenal au moment du relevé au scan laser.Cette étude a permis d’alimenter le domaine des laves torrentielles en observations quantitatives sur le terrain. Des bases de données détaillées ont été obtenues par l'intégration de multiples relevés des différentes sections transversales, des nombreux balayages laser et des données des stations de mesure à haute fréquence. Les mesures de transfert de sédiments, des interactions/contrôles dans le chenal, de la dynamique des laves torrentielles. La caractérisation des stockages dans ces bassins différents fournit une base solide pour le développement de modèles conceptuels et statistiques. Ces observations ont également mis en évidence les paramètres importants à mesurer sur le terrain qui ont une influence sur les laves torrentielles. / Steep mountain catchments typically experience large sediment pulses from hillslopes which are stored in headwater channels and remobilized by debris-flows or bedload transport. The purpose of this research was to investigate the coarse sediment transport through steep catchments and how channel storage can influence debris-flows. This required intensive field-based geomorphic monitoring of flow events in the Manival and Réal torrent catchments which can experience debris-flows and bedload transport every year.In the Manival Torrent, the sediment transfers were characterized at a seasonal time scale by a complete sediment budget of the catchment derived from multi-date topographic measurements between important flow events (cross-section surveying and terrestrial laser scanning). Sediment budget reconstitution of two debris-flows revealed that most of their volumes were supplied by channel scouring (more than 92%). Bedload transport during autumn contributed to the sediment recharge of high-order channels by the deposition of large gravel wedges. This process is recognized as being fundamental for debris-flow occurrence during the subsequent spring and summer. A time shift of scour-and-fill sequences was observed between low- and high-order channels, revealing the discontinuous sediment transfer in the catchment during common flow events. A conceptual model of sediment routing for different event magnitudes is proposed.In the Réal Torrent, post-event surveying and high-frequency monitoring stations were used to compare and compile measurements of flow events. Three debris-flow events and three periods of bedload transport with small headwater debris-flows were observed. Sediment transport volumes for debris-flows were very similar to the Manival with important volume growth in the channel. The largest observed debris-flow revealed a downstream decrease of maximum flow heights, shear stress, velocity, and flow resistance. We hypothesize that the debris-flow front scours and destabilizes the channel, but it cannot transport the material because of its high sediment concentration. Therefore, the trailing hyperconcentrated surge picks up the remaining material, grows in volume, and coalesces with the decelerating debris-flow. Both the front and following surges play an integral role for net erosion during a debris-flow event.Multi-date cross-sections in the Manival and Réal have shown that debris-flows have significant scouring with large spatial variability. Bedload transport was observed to be at equilibrium with little variability. Field observations of channel deformations show that debris-flow scouring is strongly controlled by upstream slope and storage conditions. A logarithmic relationship is proposed as an empirical fit for the prediction of channel erosion. The most susceptible materials for erosion in the Manival are the unconsolidated gravel wedges developed from bedload transport. This material has a smooth surface within the rugged channel which can be automatically mapped with a 20 cm digital elevation model from either terrestrial or airborne laser scans by calculating roughness with a one meter window. This provides an automatic assessment of erodible areas in a channel at the time of the laser scan survey.This study has contributed to the need of quantitative field observations in the realm of debris-flow research. Complete and thorough databases were obtained by integrating multi-date cross-section surveys, multi-date laser scans, and high-frequency monitoring stations. Quantified evidence revealing sediment transfers, channel interactions/controls, debris-flow dynamics, and storage characterizations in two different catchments provides a strong basis in the development of conceptual and statistical models. These observations also highlighted the significant field parameters that have an influence on debris-flows and steep catchment systems.

Made available in DSpace on 2016-12-12T20:12:29Z (GMT). No. of bitstreams: 1 PGEF14MA008.pdf: 3688775 bytes, checksum: 4a40e070e65e6367243d2ef1f2414666 (MD5) Previous issue date: 2014-07-25 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / This paper aimed to automatic extract crowns of Araucaria angustifolia using LiDAR data and indirectly obtain dendrometric variables. To conduct the project, a LiDAR point cloud was used with an average density of 7 points/m², located in the city of Painel in Santa Catarina. Four subareas were selected so that only isolated trees would be considered. The laser scanning survey was conducted by the company Aeroimagem S/A from Curitiba, in January 2011 using a Leica ALS-60 system. In the fieldwork, isolated trees of A. angustifolia were measured to give the DBH, total height and 4 crown radius in the direction of the cardinal points. The fieldwork occurred in September and August 2013. To delineate the crowns, it was employed the segmentation methodology of Thiessen polygons. Each segment was measured in order to obtain the canopy diameter for each tree. For the calculation of dendrometric variables, linear regression was used to obtain the DBH as a function of the crown diameter. The total height was obtained directly from LiDAR data. Because of the seasonality between the LiDAR survey and fieldwork, it was necessary to apply a correction in LiDAR data using increment data of the species. Segmentation by Thiessen polygons reached an accuracy ranging between 75.2% and 91.7%. Estimating the 14 DBH the difference between the field was 3,1mm. For total height 0,19m was the difference between the data field and the LiDAR. Using the proposed methodology, it was possible to perform the measurement of the crowns of A. angustifolia and estimate dendrometric variables with satisfactory accuracy / Este trabalho tem como objetivo a medição automática de copas de Araucaria angustifolia utilizando dados LiDAR e indiretamente a obtenção de variáveis dendrométricas. Para a realização da pesquisa utilizou-se uma nuvem de pontos LiDAR com uma densidade média de 7 pontos/m², localizada no município de Painel em Santa Catarina. Quatro subáreas foram selecionadas para que fosse possível trabalhar apenas com árvores isoladas. O levantamento por varredura a LASER foi efetuado pela empresa Aeroimagem S/A de Curitiba, em janeiro de 2011 utilizando um sistema Leica ALS-60. No levantamento a campo, foram medidas árvores isoladas de A. angustifolia obtendo-se o DAP, altura total e 4 raios da copa na direção dos pontos cardeais. O levantamento à campo ocorreu em setembro e agosto de 2013. Para o delineamento das copas foi empregada a metodologia de segmentação de polígonos de Thiessen. Para o cálculo das variáveis dendrométricas, foi utilizado regressão linear para obter o DAP em função do diâmetro da copa. A altura pôde ser obtida diretamente dos dados LiDAR. Devido a sazonalidade entre o levantamento LiDAR e a coleta de dados a campo, foi necessário aplicar uma correção nos dados LiDAR utilizando dados de incremento da espécie. A segmentação por 12 polígonos de Thiessen atingiu uma acurácia que variou entre 75,2% e 91,7%. Na estimativa do DAP chegou-se a uma diferença de 3,1mm em relação ao campo. Para a altura total, 0,19m foi a diferença entre os dados a campo e o LiDAR. Utilizando a metodologia proposta, foi possível realizar a medição das copas de A. angustifolia e estimar as variáveis dendrométricas com precisão satisfatória

Made available in DSpace on 2014-12-17T14:09:18Z (GMT). No. of bitstreams: 1 AndreLSS_TESE.pdf: 5521921 bytes, checksum: f9408bc166edc779a453c6cc730acf4f (MD5) Previous issue date: 2014-04-04 / The objective of this Doctoral Thesis was monitoring, in trimestral scale, the coastal morphology of the Northeastern coast sections of Rio Grande do Norte State, in Brazil, which is an area of Potiguar Basin influenced by the oil industry activities. The studied sections compose coastal areas with intense sedimentary erosion and high environmental sensitivity to the oil spill. In order to achieve the general objective of this study, the work has been systematized in four steps. The first one refers to the evaluation of the geomorphological data acquisition methodologies used on Digital Elevation Model (DEM) of sandy beaches. The data has been obtained from Soledade beach, located on the Northeastern coast of Rio Grande Norte. The second step has been centered on the increasing of the reference geodetic infrastructure to accomplish the geodetic survey of the studied area by implanting a station in Corta Cachorro Barrier Island and by conducting monitoring geodetic surveys to understand the beach system based on the Coastline (CL) and on DEM multitemporal analysis. The third phase has been related to the usage of the methodology developed by Santos; Amaro (2011) and Santos et al. (2012) for the surveying, processing, representation, integration and analysis of Coastlines from sandy coast, which have been obtained through geodetic techniques of positioning, morphological change analysis and sediment transport. The fourth stage represents the innovation of surveys in coastal environment by using the Terrestrial Laser Scanning (TLS), based on Light Detection and Ranging (LiDAR), to evaluate a highly eroded section on Soledade beach where the oil industry structures are located. The evaluation has been achieved through high-precision DEM and accuracy during the modeling of the coast morphology changes. The result analysis of the integrated study about the spatial and temporal interrelations of the intense coastal processes in areas of building cycles and destruction of beaches has allowed identifying the causes and consequences of the intense coastal erosion in exposed beach sections and in barrier islands / O objetivo da Tese de Doutorado foi o monitoramento da morfologia costeira em escala trimestral de trechos do Litoral Setentrional do Estado do Rio Grande do Norte, ?rea da Bacia Potiguar sob a influ?ncia das atividades petrol?feras. Trata-se de setores costeiros marcados por intensa eros?o sedimentar e de alta sensibilidade ambiental ao derramamento de ?leo. Para atingir o objetivo geral deste estudo, o trabalho foi sistematizado em quatro etapas. A primeira etapa apresenta a avalia??o das metodologias de aquisi??o de dados geomorfol?gicos utilizada na modelagem digital de eleva??o de praias arenosas a partir de dados obtidos na praia de Soledade, localizada no Litoral Setentrional do Rio Grande do Norte. A segunda etapa foi a amplia??o da infraestrutura geod?sica de refer?ncia para a realiza??o dos levantamentos geod?sicos da ?rea de estudo atrav?s da implanta??o de uma esta??o na ilha barreira de Corta Cachorro e de levantamentos geod?sicos de monitoramento para o entendimento do sistema praial com uso de an?lises multitemporal de LC e MDE. A terceira etapa consistiu na utiliza??o da metodologia geod?sica para o levantamento, processamento, representa??o, integra??o e an?lises de Linhas de Costa (LC) de litorais arenosos obtidos por t?cnicas geod?sicas de posicionamento, an?lise das altera??es morfol?gicas e transporte de sedimentos A quarta etapa foi definida pela inova??o de levantamentos em ambientes costeiros com a utiliza??o do Laser Esc?ner Terrestre (LiDAR) para avalia??o de um trecho submetido a intensa eros?o na praia de Soledade onde est?o instaladas infraestruturas da ind?stria petrol?fera, por meio de MDE de alta precis?o e acur?cia no modelamento das modifica??es na morfologia costeira. As an?lises dos resultados do estudo integrado das interrela??es espaciais e temporais dos intensos processos costeiros atuantes na ?rea ao longo de ciclos de constru??o e destrui??o das praias permitiram identificar as causas e consequ?ncias da intensa eros?o costeira em setores de praias expostas e ilhas barreiras

Sensors based on LiDAR (Light Detection and Ranging) technology have the potential to provide accurate 3D models of the trees retrieving information such as canopy volume and height. This information can be used for diagnostics and prescriptions of fertilizers and plant protection products on a site-specific basis. This research aimed to investigate the use of LiDAR sensors in orange crops. Orange is one of the most important tree crop in Brazil. So far, research have developed and tested LiDAR based systems for several tree crops. However, usually individual trees or small field plots have been used. Therefore, several aspects related to data acquisition and processing must still be developed for large-scale application. The first study reported in this document (Chapter 3) aimed to develop and test a mobile terrestrial laser scanner (MTLS) and new data processing methods in order to obtain 3D models of large commercial orange groves and spatial information about canopy geometry. A 2D laser sensor and a RTK-GNSS receiver (Real Time Kinematics - Global Navigation Satellite System) were mounted on a vehicle. The data processing was based on generating a georeferenced point cloud, followed by the filtering, classification and surface reconstruction steps. A 25 ha commercial orange grove was used for field validation. The developed data acquisition and processing system was able to produce a reliable point cloud of the grove, providing high resolution canopy volume and height information. The choice of the type of point cloud classification (by individual trees or by transversal sections of the row) and the surface reconstruction algorithm is discussed in this study. The second study (Chapter 4) aimed to characterize the spatial variability of canopy geometry in commercial orange groves. Understanding such variability allows sensor-based variable rate application of inputs (i.e, applying proportional rates of inputs based on the variability of canopy size) to be considered as a suitable strategy to optimize the use of fertilizers and plant protection products. Five commercial orange groves were scanned with the developed MTLS system. According to the variability of canopy volume found in those groves, the input savings as a result of implementing sensor-based variable rate technologies were estimated in about 40%. The second goal of this study was to understand the relationship between canopy geometry and several other relevant attributes of the groves. The canopy volume and height maps of three groves were analyzed against historical yield maps, elevation, soil electrical conductivity, organic matter and clay content maps. The correlations found between canopy geometry and yield or soil maps varied from poor to strong correlations, depending on the grove. When classifying the groves into three classes according to canopy size, the yield performance and soil features inside each class was found to be significantly different, indicating that canopy geometry is a suitable variable to guide management zones delineation in one grove. Overall results from this research show the potential of MTLS systems and subsequent data analysis in orange crops indicating how canopy geometry information can be used in site-specific management practices. / Sensores baseados em tecnologia LiDAR (Light Detection and Ranging) têm o potencial de fornecer modelos tridimensionais de árvores, provendo informações como o volume e altura de copa. Essas informações podem ser utilizadas em diagnósticos e recomendações localizadas de fertilizantes e defensivos agrícolas. Este estudo teve como objetivo investigar o uso de sensores LiDAR na cultura da laranja, uma das principais culturas de porte arbóreo no Brasil. Diversas pesquisas têm desenvolvido sistemas LiDAR para culturas arbóreas. Porém, normalmente tais sistemas são empregados em plantas individuais ou em pequenas áreas. Dessa forma, diversos aspectos da aquisição e processamento de dados ainda devem ser desenvolvidos para viabilizar a aplicação em larga escala. O primeiro estudo deste documento (Capítulo 3) focou no desenvolvimento de um sistema LiDAR (Mobile Terrestrial Laser Scanner - MTLS) e nova metodologia de processamento de dados para obtenção de informações acerca da geometria das copas em pomares comerciais de laranja. Um sensor a laser e um receptor RTK-GNSS (Real Time Kinematics - Global Navigation Satellite System) foram instalados em um veículo para leituras em campo. O processamento de dados foi baseado na geração de uma nuvem de pontos, seguida dos passos de filtragem, classificação e reconstrução da superfície das copas. Um pomar comercial de laranja de 25 ha foi utilizado para a validação. O sistema de aquisição e processamento de dados foi capaz de produzir uma nuvem de pontos representativa do pomar, fornecendo informação sobre geometria das plantas em alta resolução. A escolha sobre o tipo de classificação da nuvem de pontos (em plantas individuais ou em seções transversais das fileiras) e sobre o algoritmo de reconstrução de superfície, foi discutida nesse estudo. O segundo estudo (Capítulo 4) buscou caracterizar a variabilidade espacial da geometria de copa em pomares comerciais. Entender tal variabilidade permite avaliar se a aplicação em taxas variáveis de insumos baseada em sensores LiDAR (aplicar quantias de insumos proporcionais ao tamanho das copas) é uma estratégia adequada para otimizar o uso de insumos. Cinco pomares comerciais foram avaliados com o sistema MTLS. De acordo com a variabilidade encontrada, a economia de insumos pelo uso da taxa variável foi estimada em aproximadamente 40%. O segundo objetivo desse estudo foi avaliar a relação entre a geometria de copa e diversos outros parâmetros dos pomares. Os mapas de volume e altura de copa foram comparados aos mapas de produtividade, elevação, condutividade elétrica do solo, matéria orgânica e textura do solo. As correlações entre geometria de copa e produtividade ou fatores de solo variaram de fraca até forte, dependendo do pomar. Quando os pomares foram divididos entre três classes com diferentes tamanhos de copas, o desempenho em produtividade e as características do solo foram distintas entre as três zonas, indicando que parâmetros de geometria de copa são variáveis úteis para a delimitação de unidades de gestão diferenciada em um pomar. Os resultados gerais desta pesquisa mostraram o potencial de sistemas MTLS para pomares de laranja, indicando como a geometria de copa pode ser utilizada na gestão localizada de pomares de laranja.

As condições climáticas do Brasil aliadas ao desenvolvimento tecnológico favorecem a obtenção de sucessivos incrementos em produção florestal e estimulam a expansão de área cultivada com povoamentos voltados para a produção madeireira. Com o objetivo de contribuir para o processo de quantificação das florestas plantadas em uma escala regional, este estudo propõe utilizar informações combinadas de imagens de satélites e dados obtidos do LiDAR (Light Detecting and Ranging) para a construção de modelos determinísticos capazes de distinguir em duas categorias de idade agrupamentos de florestas plantadas no Vale do Paraíba, estado de São Paulo. A primeira etapa constitui utilizar informações de parcelas de campo como resposta para modelos gerados com variáveis de escaneamento a laser aeroembarcado (ALS) e extrapolar os parâmetros para toda a região da plantação; em um segundo momento, utilizar as informações extrapoladas para gerar um modelo composto por variáveis de índice de vegetação (IV) calculados das imagens de satélite. As informações LiDAR (Light Detecting and Ranging) foram obtidas de sete fazendas da região do Vale do Paraíba, estado de São Paulo, em 2012, mesmo ano em que foram coletados os dados das parcelas de campo dos inventários florestais e que as imagens foram obtidas pela constelação de satélites RapidEye. Como variáveis de dados ALS foram utilizados o cálculo de todos os pontos por célula de 5 x 5 m avaliados, alturas máxima, mínima, média, desvio padrão e percentis de altura, calculados pelo programa de análise de dados LASTools&reg;. Foram incluídas também métricas de diferença de alturas do percentil 90 e o percentil 10 (p9010) e a medida dessa diferença relativa à altura do percentil 90 (p9010r). Na modelagem dos dados LiDAR para imagens de satélite foram utilizadas como variáveis, de forma individual ou conjuntamente, os índices NDVI, NDVI705, EVI, GNDVI, SAVI, Red-Green ratio e SRI. Os modelos foram avaliados quanto ao seu desempenho no coeficiente de determinação (R2) e na raíz do erro quadrático médio (RMSE) e em uma análise final predizendo as fazendas em categorias de idade jovem e maduro. O modelo com melhores estimativas (R2 e RMSE) para idade na primeira etapa foi o que possuía variáveis Hp90 e Hp9010r, com R2=0,85 e RMSE=11,736 meses, e para a segunda etapa foi o modelo contendo como variáveis os índices de vegetação NDVI705, Red-Green índex e SAVI, com R2=0,49 e RMSE=0,378 meses. Apesar dos resultados melhores, o modelo contendo índices de vegetação GNDVI e Red-Green índex foi o que melhor representou a distribuição das florestas quanto a sua maturidade. / Brazil\'s climate conditions combined with the technological development promote the obtaining of successive increments in forest production and stimulate the expansion of cultivated area with stands for timber production. In order to contribute to the process of quantification of planted forests at regional scale, this study proposes to use combined information from satellite images and data obtained from the LiDAR (Light Detecting and Ranging) for the construction of deterministic models able to distinguish two categories of age groupings of planted forests in the Paraíba Valley, State of São Paulo in Brazil. The first step is to use field plots information in response to models generated with airborne laser scanning (ALS) variables and extrapolate the parameters for the whole region of the plantation; in a second moment, use the information extrapolated to generate a model composed of vegetation index variables (IV) calculated from satellite images. The information LiDAR (Light Detecting and Ranging) were obtained from seven farms in the region of the Paraíba Valley, State of São Paulo, in 2012, the same year in which the data were collected from plots of field forest inventories and that the images were obtained by the RapidEye satellite constellation. As data variables ALS were used the calculation of all points by cell size of 5 x 5 m evaluated, maximum height, minimum, mean, standard deviation and height percentiles, calculated by the data analysis program called LASTools®. Also included height difference metrics 90th percentile and percentile 10th (p9010) and the extent of this difference relative of the 90th percentile (p9010r). In the modeling of data LiDAR data for satellite images were used as variables, individually or jointly, the NDVI index, NDVI705, EVI, GNDVI, SAVI, Red-Green index and SRI. The models were evaluated regarding their performance on the coefficient of determination (R2) and root mean square error (RMSE) and a final analysis predicting the farms into categories of age, young and mature. The model with best estimates (R2 and RMSE) for age at first stage was what possessed variables Hp90 and Hp9010r, with R2 = 0.85 and RMSE = 11.736 months, and the second stage was the model containing as variables the NDVI705 vegetation, Red-Green index and SAVI, with R2 = 0.49 and RMSE = 0.378 months. Despite the better results, the model containing GNDVI and Red-Green vegetation indices was the best represented distribution of forests about your maturity.

La capacité des robots mobiles à se localiser précisément par rapport à leur environnement est indispensable à leur autonomie. Pour ce faire, les robots exploitent les données acquises par des capteurs qui observent leur état interne, tels que centrales inertielles ou l’odométrie, et les données acquises par des capteurs qui observent l’environnement, telles que les caméras et les Lidars. L’exploitation de ces derniers capteurs a suscité le développement de solutions qui estiment conjointement la position du robot et la position des éléments dans l'environnement, appelées SLAM (Simultaneous Localization and Mapping). Pour gérer le bruit des données provenant des capteurs, les solutions pour le SLAM sont mises en œuvre dans un contexte probabiliste. Les premiers développements étaient basés sur le filtre de Kalman étendu, mais des développements plus récents utilisent des modèles graphiques probabilistes pour modéliser le problème d’estimation et de le résoudre grâce à techniques d’optimisation. Cette thèse exploite cette dernière approche et propose deux techniques distinctes pour les véhicules terrestres autonomes: une utilisant la vision monoculaire, l’autre un Lidar. L’absence d’information de profondeur dans les images obtenues par une caméra a mené à l’utilisation de paramétrisations spécifiques pour les points de repères qui isolent la profondeur inconnue dans une variable, concentrant la grande incertitude sur la profondeur dans un seul paramètre. Une de ces paramétrisations, nommé paramétrisation pour l’angle de parallaxe (ou PAP, Parallax Angle Parametrization), a été introduite dans le contexte du problème d’ajustement de faisceaux, qui traite l’ensemble des données en une seule étape d’optimisation globale. Nous présentons comment exploiter cette paramétrisation dans une approche incrémentale de SLAM à base de modèles graphiques, qui intègre également les mesures de mouvement du robot. Les Lidars peuvent être utilisés pour construire des solutions d’odométrie grâce à un recalage séquentiel des nuages de points acquis le long de la trajectoire. Nous définissons une couche basée sur les modèles graphiques au dessus d’une telle couche d’odométrie, qui utilise l’algorithme ICP (Iterative Closest Points). Des repères clefs (keyframes) sont définis le long de la trajectoire du robot, et les résultats de l’algorithme ICP sont utilisés pour construire un graphe de poses, exploité pour résoudre un problème d’optimisation qui permet la correction de l’ensemble de la trajectoire du robot et de la carte de l’environnement à suite des fermetures de boucle.Après une introduction à la théorie des modèles graphiques appliquée au problème de SLAM, le manuscrit présente ces deux approches. Des résultats simulés et expérimentaux illustrent les développements tout au long du manuscrit, en utilisant des jeux des données classiques et obtenus au laboratoire. / A strong requirement to deploy autonomous mobile robots is their capacity to localize themselves with a certain precision in relation to their environment. Localization exploits data gathered by sensors that either observe the inner states of the robot, like acceleration and speed, or the environment, like cameras and Light Detection And Ranging (LIDAR) sensors. The use of environment sensors has triggered the development of localization solutions that jointly estimate the robot position and the position of elements in the environment, referred to as Simultaneous Localization and Mapping (SLAM) approaches. To handle the noise inherent of the data coming from the sensors, SLAM solutions are implemented in a probabilistic framework. First developments were based on Extended Kalman Filters, while a more recent developments use probabilistic graphical models to model the estimation problem and solve it through optimization. This thesis exploits the latter approach to develop two distinct techniques for autonomous ground vehicles: oneusing monocular vision, the other one using LIDAR. The lack of depth information in camera images has fostered the use of specific landmark parametrizations that isolate the unknown depth in one variable, concentrating its large uncertainty into a single parameter. One of these parametrizations, named Parallax Angle Parametrization, was originally introduced in the context of the Bundle Adjustment problem, that processes all the gathered data in a single global optimization step. We present how to exploit this parametrization in an incremental graph-based SLAM approach in which robot motion measures are also incorporated. LIDAR sensors can be used to build odometry-like solutions for localization by sequentially registering the point clouds acquired along a robot trajectory. We define a graphical model layer on top of a LIDAR odometry layer, that uses the Iterative Closest Points (ICP) algorithm as registration technique. Reference frames are defined along the robot trajectory, and ICP results are used to build a pose graph, used to solve an optimization problem that enables the correction of the robot trajectory and the environment map upon loop closures. After an introduction to the theory of graphical models applied to SLAM problem, the manuscript depicts these two approaches. Simulated and experimental results illustrate the developments throughout the manuscript, using classic and in-house datasets.