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®. 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.

Ce travail présente une nouvelle méthode de télédétection à distance de la concentration d’un gaz trace dans l’atmosphère basée sur le couplage de la méthode spectroscopique de corrélation optique (Optical Correlation Spectroscopy, OCS) et la technologie de télédétection lidar dans lequel une source laser de large étendue spectrale est considérée. Les premiers travaux furent consacrés au développement d’un nouveau formalisme pour estimer la concentration d’un gaz trace dans l’atmosphère à partir des signaux OCS-lidar. Pour évaluer les performances d’une telle méthode, un modèle numérique simulant des signaux OCS-lidar pour la mesure de la concentration de méthane et de vapeur d’eau a été réalisé. L’influence de la pression et la température sur les propriétés spectroscopiques de ces gaz sur les mesures de concentration a également été étudiée. En plus de ce travail théorique, la première démonstration expérimentale de l’OCS-lidar est présentée en utilisant un lidar basé sur une source laser femtoseconde. Les mesures OCS-lidar ont été réalisées au moyen d’un nouveau système expérimental entièrement élaboré et construit pendant cette thèse. Pour réaliser les mesures consacrées à la teneur en vapeur d’eau de l’atmosphère, la bande d’absorption de la molécule de H2O 4ν à 720 nm a été utilisée. Ainsi les résultats obtenus ont montré le potentiel de la méthode OCS5 lidar pour mesurer la concentration de vapeur d’eau. Par la suite, le développement de la méthodologie OCS-lidar dédiée à la mesure du méthane est présenté. La bande d’absorption 2ν3 à 1,66 μm est exploitée et les premières mesures des signaux lidar sont exposées. Ce travail se termine par la présentation des possibles perspectives d’évolution / In this thesis, a new active remote sensing methodology is proposed to evaluate the content of atmospheric trace gases. The new methodology is based on laser spectroscopy and consists in coupling a spectrally broadband lidar with optical correlation spectroscopy (OCS-lidar). As a first step, a new formalism has been developed to remotely evaluate the target gas concentration from the OCS-lidar signals. To evaluate the performance of this new methodology, a numerical model simulating OSC-lidar signals for methane and water vapor measurement has been developed. Moreover, the influence of the absorption spectroscopic line parameters, such as atmospheric pressure and temperature, on the retrieved gas mixing ratio has been assessed within the OCS-lidar methodology. In addition to this theoretical work, the first experimental demonstration of the OCS-lidar methodology has been performed using a femtosecond lidar system. The latter has been entirely designed, developed and implemented in the framework of this thesis. Results show the ability of the OCS-lidar methodology to monitor the water vapor using the 4ν 720 nm absorption band. Moreover, two different experimental configurations have been proposed, depending on whether the amplitude modulation is operated on the laser pulse or on the backscattered light, i.e. at the emission, with an active amplitude modulator or at the reception, with passive optical filters. The advances in developing the corresponding infrared OCS-lidar system for methane mixing ratios measurements are described and possible outlooks are given

La Guyane française est une région située sur le Plateau des Guyanes en Amérique du sud. Elle présente à la fois une grande originalité en termes de biodiversité, un bon état de conservation et une forte contribution au stock de carbone Amazonien. Les connaissances sur l’évolution de la structure forestière de la Guyane française restent cependant insuffisantes pour offrir une gestion optimale à l’échelle du territoire. La disponibilité sans précédent de données de télédétection à très haute résolution spatiale telles que le LiDAR , sur de larges couvertures nous offre l'opportunité d’évaluer la ressource forestière de la Guyane Française. Les travaux réalisés dans le cadre de cette thèse visent prioritairement à étudier la structure et les variations de la hauteur de canopée, les facteurs déterminant sa variabilité ainsi que les conséquences des activités d’exploitation forestière. Les données utilisées au cours de la thèse proviennent d’un LiDAR aéroporté et des données de terrains de l'Office National des Forêts (ONF). Ce manuscrit de thèse est divisé en trois grandes parties. La première partie introduit la problématique et fixe les objectifs de la thèse. La seconde partie prend la forme dite « sur article », c'est-à-dire que les différents chapitres qui la compose sont des articles scientifiques publiés ou en cours de publication, elle est composée de trois études. (i) Une étude concernant la détection des trouées et des déterminants environnementaux sur la distribution de tailles des trouées en forêt non exploitée : Comment caractériser la distribution de taille des trouées et est-ce qu’il y a des déterminants environnementaux qui influencent la distribution statistique de taille de trouées? Cet article à été soumis dans Biogeoscience. (ii) Une étude du contrôle de l'environnement sur la structure et les variations de la hauteur de canopée à différentes résolutions spatiales. Quelles échelles spatiales sont pertinentes pour analyser les déterminants environnementaux des variations de hauteur de la canopée en forêt tropicale à partir des données de télédétection ? Comment l’environnement peut aider, ou pas, à cartographier la hauteur de la canopée en forêt tropicale ? Cet article à été accepté pour publication dans Remote Sensing. (iii) Une troisième étude où nous avons quantifié les effets de l’exploitation à faible impact (EFI) sur la structure et la variation de la hauteur de canopée. Quelles sont les effets de l’exploitation forestière sur les variations de hauteur de canopée et sur la distribution de taille des trouées ? Cet article sera soumis pour publication dans une revue scientifique (Forest Ecology and Management). Dans la dernière partie, après une synthèse des principaux résultats, nous proposons des pistes de développement. / French Guiana is a region located on the Guiana Shield in South America. Is presents at the same time a high originality in biodiversity, a good state of conservation and a strong correlation to Amazonian carbon stocks. Knowledge on evolution of the forest structure of French Guiana is however still insufficient to bring an optimal management at territory scale. Availability as never seen before of remote sensing data at high spatial resolution such as LiDAR, on large coverage, offers the opportunity to assess the forest resource in French Guiana. The work done during this thesis aim mostly to study the structure and the variations of the canopy height, the factors determining its variability and the consequences of forest logging activities. The data used during this thesis come from an airborne LiDAR and field data from Office National des Forêts (ONF). This thesis manuscript is divided in three parts. The first part introduces the problem and sets the objectives of the thesis. The second part takes the so-called "article" form, that is, the different chapters that compose it are scientific articles published or in the course of publication, it is composed of three studies (I) A study on the gaps detection and environmental determinants on the gap sizes distribution in natural forest: How to characterize the gap size distribution and are there environmental determinants that influence the statistical distribution of gap size? This article has been submitted in Biogeoscience. (ii) A study of the control of the environment on the canopy height structure and variations at different spatial resolutions. Which spatial scales are relevant for analyzing the environmental determinants of canopy height changes in tropical forests from remote sensing data? How can the environment help or not map the height of the canopy in the rainforest? This article was accepted for publication in Remote Sensing. (iii) a third study where we quantified the effects of Reduced Impact Logging (RIL) on the structure and variation of canopy height. What are the effects of logging on canopy height variations and gap size distribution? This article will be submitted for publication in a Forest Ecology and Management journal. In the last part, after a synthesis of the main results, we propose a conclusion.

Du point de vue écologique, les efforts de tension ou de compression développés par la maturation du bois au cours de la croissance permettent à l'arbre de maintenir sa posture verticale face à la gravité. Ces efforts, appelés autocontraintes de maturation, résultent de la mise en place d'un bois particulier, le bois de réaction. Sur le plan mécanique, c'est la dissymétrie des autocontraintes entre les deux faces du tronc de l'arbre qui joue un rôle moteur dans le redressement, qui s'exprime par une courbure. Ce travail vise à développer de nouveaux outils théoriques et métrologiques pour étudier le lien entre morphologie de l'arbre et autocontraintes dans un cadre biomécanique et écologique. Une première approche vise à mettre en relation la dynamique de croissance et la compétition du peuplement avec la morphologie et la réaction de contrôle de la posture des arbres. Elle utilise des données issues d'un essai sylvicole de long terme (plantations de hêtres de différentes densités initiales laissées en croissance pendant 26 ans). L'analyse rétrospective de la production du bois de réaction sur des rondelles prélevées sur ces arbres a permis d'évaluer les différentes composantes du mouvement gravitropique au cours du temps. Une loi d'échelle, établie entre la vitesse de courbure et la circonférence des tiges, montre (i) l'effet prépondérant du diamètre de la tige dans sa capacité de réaction, et (ii) l'absence d'effet additionnel de la compétition. En fin d'expérience, l'évaluation de la morphologie des arbres a permis de confirmer le lien entre l'inclinaison et l'élancement de la tige avec les indicateurs de contraintes de croissance. D'un point de vue mécanique, la morphologie de l'arbre s'interprète (i) par la forme de sa tige (inclinaison et courbures), et (ii) par la distribution spatiale de sa biomasse, qui peuvent fournir des variables biomécaniques candidates pour élaborer des modèles de stimulus-réponse. Ainsi, un important travail méthodologique couplant la technologie LiDAR terrestre (un instrument de numérisation laser 3D très prometteur pour les mesures forestières) à des techniques de modélisation géométrique a permis d'obtenir des maquettes 3D précises de la structure ligneuse d'arbres de différentes espèces. Les maquettes ont permis de modéliser la contrainte de flexion exercée par la biomasse aérienne des arbres en vue d'une mise en relation avec les indicateurs de contraintes de croissance mesurées sur leur grume. Les résultats montrent que la contrainte de flexion est une variable très prometteuse pour évaluer le degré de réaction des arbres. La méthodologie ouvre également des perspectives originales pour le suivi temporel de la morphologie de l'arbre en lien avec son interprétation biomécanique. / From an ecological point of view, the tension or compression stresses developed by wood maturation during growth allow the tree to maintain its vertical posture against gravity. These stresses, called growth stresses, results from the formation of a particular wood called reaction wood. From a mechanical point of view, the asymmetry of growth stresses between the two opposite faces of the tree trunk causes its reorientation, characterised by a curvature. This work aims at developing new theoretical and metrological tools to assess the link between tree morphology and growth stresses in a biomechanical and ecological framework. The first approach aimed at establishing the link between growth dynamics and competition of the stand with tree morphology and reaction of posture control. It is based on data taken in a long-term forestry experiment (beech plantations of different initial planting densities that grew during 26 years). The retrospective analysis of reaction wood production on wood discs taken on the trees allowed to assess the variation of their gravitropic performance over time. The scaling law established between curvature rate and stem circumference showed (i) the leading effect of the diameter of a stem on its reactivity, and (ii) the absence of additional effects of competition. At the end of the experimentation, the assessment of the tree morphology allowed to confirm the link between stem leaning and slenderness with growth stresses indicators. From a mechanical point of view, tree morphology can be assess by (i) the shape of its stem (leaning, curvatures), and (ii) the spatial distribution of its biomass, that can provide biomechanical variables for stimulus-response models. Therefore, an important methodological work was performed, based on terrestrial LiDAR technology (a promising tool for forest measurements based on 3D laser digitisation) coupled to geometrical modelling. It allowed to obtain accurate 3D mocks-up representing the woody structure of trees of variables species. The mocks-up allowed to model the bending stress exerted by the aerial biomass of the trees with the aim of linking it to the growth stresses indicators. The results show that bending stress is a promising variable for assessing the degree of reaction of trees. The developed methodology also gives many perspectives for monitoring tree morphology over time with the aim of biomechanical interpretation.

Submitted by Fabio Sobreira Campos da Costa (fabio.sobreira@ufpe.br) on 2016-04-19T14:14:56Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Dissertacao_SidneySantana_2015.pdf: 7597504 bytes, checksum: bf6a44dd30bc34dca577bb38b4fb038f (MD5) / Made available in DSpace on 2016-04-19T14:14:56Z (GMT). No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Dissertacao_SidneySantana_2015.pdf: 7597504 bytes, checksum: bf6a44dd30bc34dca577bb38b4fb038f (MD5) Previous issue date: 2015-08-31 / As florestas têm um papel fundamental no sequestro de carbono da atmosfera. Dessa forma, este trabalho tem como principal objetivo quantificar e analisar a biomassa de um fragmento florestal de Pinus uncinata pertencente ao Espaço Natural da Montanha de Alinyà, por meio de ferramentas de sensoriamento remoto. O espaço natural está localizado no município de Figòls y Alinyà, na província Lleida, situada na Catalunha – Espanha. Assim, para realizar este estudo foram selecionadas 7 imagens do sensor TM do Landsat 5 correspondentes aos 1984, 2003, 2006, 2008, 2009, 2010 e 2011 com rota 198 e ponto 31. Seguidamente foram trabalhadas as bandas espectrais de cada imagem e calculados a calibração radiométrica, a reflectância e os índices de vegetação NDVI e SAVI. Com os dados LiDAR foram gerados os Modelos Digitais de Terreno (MDT) e realizados os cálculos estatísticos pertinentes para calcular a biomassa florestal, a área basal e o teor de carbono. As informações obtidas foram projetadas em mapas. Como resultado, o NDVI mostrou-se importante por proporcionar a análise temporal do comportamento da massa florestal. No entanto, o NDVI e o SAVI tiveram seus resultados prejudicados pela influência dos efeitos topográficos. Os modelos de regressão linear para biomassa, área basal e teor de carbono tiveram uma correlação satisfatória com os dados de inventário para duas das cinco zonas consideradas. Dessa forma, foi possível estimar estas variáveis florestais para a zona de estudo. O cálculo de biomassa florestal pelos dados LiDAR resultaram em 9.138,6 t para uma área de 69,04 ha, enquanto que os cálculos de inventário resultaram em 11.638,4 tn. O Teor de carbono o cálculo com os dados LiDAR resultaram em 5.425,04 t diante de 6.520,18 t resultantes dos cálculos com os dados de inventário. Portanto se pode afirmar que a tecnologia LiDAR traz ao estudo florestal uma série de aplicações necessárias para uma efetiva gestão dos sistemas florestais. Além disso, o LiDAR apresenta vantagens diante dos outros métodos convencionais, em relação à sua precisão, temporalidade e varredura, ainda mais diante da urgência de se obter resultados confiáveis no cenário atual de mudanças climáticas e vulnerabilidade dos ecossistemas. / The forests have a vital role in carbon capture from the atmosphere. Thus, this work has as its main objective to quantify and analyze biomass of a forest fragment of a Pinus uncinata that belongs to Alinyà Mountain Natural Space, through remote sensing tools. The natural area is located in the County of Figòls y Alinyà, in the Lleida province, located in Catalonia-Spain. In this sense, to conduct this study, 7 images were selected from the Landsat 5 TM sensor corresponding to 1984, 2003, 2006, 2008, 2009, 2010 and 2011 with path 198 and row 31. Subsequently, the spectral bands of each image were manipulated, and then the radiometric calibration, reflectance, and the NDVI and SAVI vegetation indexes were calculated. Using the LiDAR data, the Digital Terrain Models (DTM) were generated, and relevant statistical calculations were made to subsequently calculate the forest biomass, basal area, and carbon content. The information obtained was projected on maps. As a result, the NDVI has supported the study by temporally analyzing the behavior of the forest. However, this index, and even more the SAVI, suffered with the influence of topographic effects. The linear regression models for biomass, basal area, and carbon content had a satisfactory correlation with the inventory data for 2 of the 5 areas considered. In this sense, it was possible to estimate these forest variables for the study area. The calculation of forest biomass by LiDAR data resulted in 9,138.6 ton to an area of 69.04 ha, while the inventory calculations resulted in 11,638.4 ton. For the carbon content, the calculation with the LiDAR data resulted in 5,425.04 ton in comparison with the 6,520 .18 ton resulting from the calculations with the inventory data. Hence, it is safe to say that LiDAR technology brings to the forest study a series of applications that are required for an effective management of forest systems. In addition, the LiDAR presents advantages before other conventional methods, regarding its accuracy, temporality, and range, especially on the urgency of obtaining reliable results in the current scenario of climate change and vulnerability of ecosystems.

Cette thèse propose des modèles cartographiques à grande échelle d'environnements urbains et ruraux à l'aide de données en 3D acquises par plusieurs robots. La mémoire contribue de deux manières principales au domaine de recherche de la cartographie. La première contribution est la création d'une nouvelle structure, CoMapping, qui permet de générer des cartes 3D de façon collaborative. Cette structure s’applique aux environnements extérieurs en ayant une approche décentralisée. La fonctionnalité de CoMapping comprend les éléments suivants : Tout d’abord, chaque robot réalise la construction d'une carte de son environnement sous forme de nuage de points.Pour cela, le système de cartographie a été mis en place sur des ordinateurs dédiés à chaque voiture, en traitant les mesures de distance à partir d'un LiDAR 3D se déplaçant en six degrés de liberté (6-DOF). Ensuite, les robots partagent leurs cartes locales et fusionnent individuellement les nuages de points afin d'améliorer leur estimation de leur cartographie locale. La deuxième contribution clé est le groupe de métriques qui permettent d'analyser les processus de fusion et de partage de cartes entre les robots. Nous présentons des résultats expérimentaux en vue de valider la structure CoMapping et ses métriques. Tous les tests ont été réalisés dans des environnements extérieurs urbains du campus de l’École Centrale de Nantes ainsi que dans des milieux ruraux. / This thesis proposes large-scale mapping model of urban and rural environments using 3D data acquired by several robots. The work contributes in two main ways to the research field of mapping. The first contribution is the creation of a new framework, CoMapping, which allows to generate 3D maps in a cooperative way. This framework applies to outdoor environments with a decentralized approach. The CoMapping's functionality includes the following elements: First of all, each robot builds a map of its environment in point cloud format.To do this, the mapping system was set up on computers dedicated to each vehicle, processing distance measurements from a 3D LiDAR moving in six degrees of freedom (6-DOF). Then, the robots share their local maps and merge the point clouds individually to improve their local map estimation. The second key contribution is the group of metrics that allow to analyze the merging and card sharing processes between robots. We present experimental results to validate the CoMapping framework with their respective metrics. All tests were carried out in urban outdoor environments on the surrounding campus of the École Centrale de Nantes as well as in rural areas.

Les cours d’eau font l’objet de prescriptions législatives encourageant leur restauration, et l’arasement de barrages est une des solutions utilisées actuellement en France pour y parvenir. La végétation riparienne participe à l’intégrité et à la stabilité des systèmes fluviaux, Elle est donc une composante majeure à évaluer dans le cadre des actions de restauration .Les objectifs de la thèse sont d'analyser la dynamique de colonisation des berges exondées à court terme dans le contexte de l’arasement des barrages de la Sélune (Normandie) et de développer des indicateurs de suivi à long terme des zones ripariennes. Dans un premier temps, une analyse des dynamiques de colonisation aux échelles intra et interannuelles réalisée à l’aide d’images drone et de relevés terrain a révélé la pertinence de l’utilisation d’images drones pour cartographier la végétation, ainsi que des dynamiques successionnelles rapides, avec un potentiel de restauration passive et de stabilisation des sédiments. Dans un second temps, l’analyse de nuages de points LiDAR en trois dimensions acquis en hiver et en été a montré la complémentarité des deux dates d’acquisition pour cartographier des indicateurs de statut des ripisylves à large échelle tels que les essences principales, l’ombrage ou la densité de strates herbacées et arbustives. Ces résultats permettent de discuter les dimensions méthodologiques et opérationnelles de l’utilisation des approches par télédétection pour le suivi des ripisylves. / Rivers are the object of legislation encouraging their restoration, and dam removal operations represent one of the solution to achieve it in France. Riparian vegetation plays a fundamental role in stabilizing and maintaining fluvial systems, being at the interface between terrestrial and aquatic environments. It is therefore a very important component which has to be evaluated in river restoration operations. One of the consequences of dam removal on riparian vegetation is the colonization of the dewatered sediments in the reservoir. The objective of the thesis are to define short term colonization dynamics of vegetation in context of dam removal (Sélune River, Normandy), and to develop long term indicators for the monitoring of riparian vegetation. First, an analysis of intra and interannual colonization dynamics revealed the potential of using drone images to map riparian vegetation, and fast successional dynamics with high passive restoration and sediment stabilization potential. Secondly, the analysis of 3D point clouds extracted from LiDAR data acquired in winter and summer highlighted the complementarity of the two acquisition dates to map indicators of riparian status at large scale, such as main riparian species, shading or density of herbaceous and shrubby strata. These results make it possible to discuss the methodological and operational dimensions of the use of remote sensing approaches for the monitoring of riparian vegetation