La modélisation et la simulation de dynamiques spatiales, en particulier pour l'étude de l'évolution de paysages ou de problématiques environnementales pose la question de l'intégration des différentes formes de représentation de l'espace au sein d'un même modèle. Ocelet est une approche de modélisation de dynamiques spatiales basée sur le concept original de graphe d'interaction. Le graphe porte à la fois la structure d'une relation entre entités d’un modèle et la sémantique décrivant son évolution. Les relations entre entités spatiales sont ici traduites en graphes d'interactions et ce sont ces graphes que l'on fait évoluer lors d'une simulation. Les concepts à la base d'Ocelet peuvent potentiellement manipuler les deux formes de représentation spatiale connues, celle aux contours définis (format vecteur) ou la discrétisation en grille régulière (format raster). Le format vecteur est déjà intégré dans la première version d'Ocelet. L'intégration du format raster et la combinaison des deux restaient à étudier et à réaliser. L'objectif de la thèse est d'abord étudier les problématiques liées à l'intégration des champs continus et leur représentation discrétisée en pavage régulier, à la fois dans le langage Ocelet et dans les concepts sur lesquels il repose. Il a fallu notamment prendre en compte les aspects dynamiques de cette intégration, et d'étudier les transitions entre données géographiques de différentes formes et graphe d'interactions à l'aide de concepts formalisés. Il s'est agi ensuite de réaliser l'implémentation de ces concepts dans la plateforme de modélisation Ocelet, en adaptant à la fois son compilateur et son moteur d'exécution. Enfin, ces nouveaux concepts et outils ont été mis à l'épreuve dans trois cas d'application très différents : deux modèles sur l’île de la Réunion, le premier simulant le ruissellement dans le bassin versant de la Ravine Saint Gilles s'écoulant vers la Côte Ouest de l'île, l’autre simulant la diffusion de plantes invasives dans les plaines des hauts à l'intérieur du Parc National de La Réunion. Le dernier cas décrit la spatialisation d'un modèle de culture et est appliqué ici pour simuler les rendements de cultures céréalières sur l’ensemble de l’Afrique de l’Ouest, dans le contexte d'un système d'alerte précoce de suivi des cultures à l'échelle régionale. / The modelling and simulation of spatial dynamics, particularly for studying landscape changes or environmental issues, raises the question of integrating different forms of spatial representation within the same model. Ocelet is an approach for modelling spatial dynamics based on the original concept of interaction graph. Such a graph holds both the structure of a relation between entities of a model and the semantics describing its evolution. The relationships between spatial entities are here translated into interaction graphs and these graphs are made to evolve during a simulation. The concepts on which Ocelet is based can potentially handle two known forms of spatial representation: shapes with contours (vector format) or regular grid cells (raster). The vector format is already integrated in the first version of Ocelet. The integration of raster and the combination of the two remained to be studied and carried out. The aim of the thesis is to first study the issues related to the integration of continuous fields and their representation by regular tiling, both in the Ocelet language and the concepts on which it is based. The dynamic aspects of this integration had to be taken into account and transitions between different forms of geographic data and interaction graphs had to be studied in the light of the concepts formalized. The concepts were then implemented in the Ocelet modelling platform, with the adaptation of both its compiler and runtime. Finally, these new concepts and tools were tested in three very different cases: two models on Reunion Island, the first simulating runoff in Ravine Saint Gilles watershed in the West Coast of the island, the other simulating the spread of invasive plants in the high plains inside the Reunion National Park. The last case describes the spatialisation of a crop model and is applied here to simulate the cereal crop yields in West Africa, in the context of an early warning system for regional crop monitoring.

Les observations météorologiques depuis les satellites dans le domaine des micro-ondes sont actuellement limitées à 190 GHz. La prochaine génération de satellites météorologiques opérationnels européens (EUMETSAT Polar System-Second Generation-EPS-SG), em- portera un instrument, le Ice Cloud Imager (ICI), avec des fréquences sub-millimétriques jusqu’à 664 GHz, afin d’améliorer la caractérisation globale des nuages de glace. Pour préparer l’exploitation de ces nouvelles données, durant cette thèse, des travaux ont été effectués sur quatre axes complémentaires. Des simulations réalistes de transfert radiatif ont été réalisées de 19 à 700 GHz, pour des scènes météorologiques réelles, couvrant une grande variabilité des nuages en Europe. L’objectif était double : premièrement mieux comprendre la sensibilité des ondes millimétriques et sub-millimétriques à la phase glacée des nuages, deuxièmement créer une base de données robuste pour développer une méthode d’inversion statistique des caractéristiques des nuages de glace. Un code de transfert radiatif atmosphérique (Atmospheric Radiative Transfer Simulator ARTS) a été couplé avec des profils atmosphériques simulés par un modèle méso-échelle de nuage (Weather Research and Forecasting WRF), pour douze scènes européennes aux moyennes latitudes. Les propriétés de diffusion des hydrométéores (glace, neige, graupel, pluie et eau dans le nuage) ont été soigneusement sélectionnées, en particulier pour la phase glace, et la compatibilité avec la microphysique de WRF a été testée : le Discrete-Dipole approximation (DDA) est adopté pour calculer les propriétés diffusantes des particules de neige. Les simulations obtenues ont été systématiquement comparées avec des observations satellitaires coïncidentes d’imageurs et de sondeurs jusqu’à 200 GHz. L’accord entre les simulations et les observations montre la bonne qualité de la base de données, au moins jusqu’à 200 GHz... / The meteorological observations from satellites in the microwave domain are currently limited to 190 GHz. The next generation of European operational Meteorological Satellite (EUMETSAT Polar System-Second Generation-EPS-SG) will carry an instrument, the Ice Cloud Imager (ICI), with frequencies up to 664 GHz, to provide unprecedented measurements in the sub-millimeter spectral range, aiming to improve the characterization of ice clouds over the globe. To prepare this upcoming satellite-borne sub-millimeter imager, during this thesis, scientific efforts have been made on four complementary aspects. Realistic radiative transfer simulations have been performed from 19 to 700 GHz, for real meteorological scenes, covering a large variability of clouds in Europe. The goal was two fold, first to better understand the sensitivity of the microwave to sub-millimeter waves to the cloud frozen phases, and second, to create a robust training database for a statistical cloud parameter retrieval. The Atmospheric Radiative Transfer Simulator (ARTS) is coupled with atmospheric profiles from the Weather Research and Forecasting (WRF) model, for twelve diverse European mid-latitude scenes. The single scattering properties of the hydrometeors (cloud ice, snow, graupel, rain, and cloud water) are carefully selected, especially for the frozen phases, and compatibility with the micro- physics in WRF is tested: the Discrete-Dipole Approximation (DDA) is adopted for snow particles. The resulting simulations have been systematically compared with coincident satellite observations from imagers and sounders up to 200 GHz. The agreement between simulations and observations shows the good quality of the simulated training database, at least up to 200 GHz...

Airborne multi-sensor imaging is increasingly used to examine vegetation properties. The advantage of using multiple types of sensor is that each detects a different feature of the vegetation, so that collectively they provide a detailed understanding of the ecological pattern. Specifically, Light Detection And Ranging (LiDAR) devices produce detailed point clouds of where laser pulses have been backscattered from surfaces, giving information on vegetation structure; hyperspectral sensors measure reflectances within narrow wavebands, providing spectrally detailed information about the optical properties of targets; while aerial photographs provide high spatial-resolution imagery so that they can provide more feature details which cannot be identified from hyperspectral or LiDAR intensity images. Using a combination of these sensors, effective techniques can be developed for mapping species and inferring leaf physiological processes at ITC-level. Although multi-sensor approaches have revolutionised ecological research, their application in mapping individual tree crowns is limited by two major technical issues: (a) Multi-sensor imaging requires all images taken from different sensors to be co-aligned, but different sensor characteristics result in scale, rotation or translation mismatches between the images, making correction a pre-requisite of individual tree crown mapping; (b) reconstructing individual tree crowns from unstructured raw data space requires an accurate tree delineation algorithm. This thesis develops a schematic way to resolve these technical issues using the-state-of-the-art computer vision algorithms. A variational method, called NGF-Curv, was developed to co-align hyperspectral imagery, LiDAR and aerial photographs. NGF-Curv algorithm can deal with very complex topographic and lens distortions efficiently, thus improving the accuracy of co-alignment compared to established image registration methods for airborne data. A graph cut method, named MCNCP-RNC was developed to reconstruct individual tree crowns from fully integrated multi-sensor imagery. MCNCP-RNC is not influenced by interpolation artefacts because it detects trees in 3D, and it detects individual tree crowns using both hyperspectral imagery and LiDAR. Based on these algorithms, we developed a new workflow to detect species at pixel and ITC levels in a temperate deciduous forest in the UK. In addition, we modified the workflow to monitor physiological responses of two oak species with respect to environmental gradients in a Mediterranean woodland in Spain. The results show that our scheme can detect individual tree crowns, find species and monitor physiological responses of canopy leaves.

Dados de altura da superfície do mar medidos a partir de satélites altimétricos e saídas de dois modelos de circulação geral dos oceanos (OGCM for the Earth Simulator - OFES e Community Earth System Model - CESM) foram utilizados com o objetivo de verificar se modelos numéricos climáticos reproduzem ondas de Rossby de forma similar à observada em dados altimétricos no Atlântico Sul. Os modelos diferem quanto à forçante, o modelo OFES é forçado com dados do NECP-NCAR enquanto que o modelo CESM é acoplado com modelo atmosférico, de gelo e terrestre. Uma vez que essas ondas dependem da estrutura interna de densidade e da forçante do vento, podemos fazer inferências sobre a adequação desses dois fatores nos modelos à realidade observada pelo altímetro. Uma série de filtros de resposta impulsiva finita 2D (FIR-2D) foi aplicada aos dados de anomalia da altura da superfície do mar com o propósito de detectar as ondas de Rossby e as componentes de onda encontradas nos dados dos modelos foram comparadas com as do altímetro. Os dois modelos são capazes de reproduzir ondas de Rossby e apresentam melhores resultados em baixas latitudes. Porém o modelo OFES apresentou mais dificuldades para reproduzir os parâmetros de onda encontrados no altímetro apresentando diferenças médias de até 68% para a amplitude, 34% para o comprimento de onda e 38% para a velocidade de fase. Em contrapartida as maiores diferenças médias entre os parâmetros de onda calculados a partir dos dados altimétricos e do modelo CESM foram de 32% para a amplitude, 20% para o comprimento de onda e 20% para a velocidade de fase. Além disso, o modelo CESM foi capaz de reproduzir o sinal sazonal com uma correlação média de aproximadamente 0,7 com o sinal sazonal encontrado pelo altímetro em toda a bacia do oceano Atlântico Sul enquanto que o sinal sazonal do modelo OFES apresentou uma correlação média de 0,4 com o sinal encontrado pelo satélite. Estes resultados mostram que os dois modelos reproduzem o fenômeno satisfatoriamente, sendo o CESM melhor que o OFES. A diferença dos resultados deve estar ligada aos aspectos supracitados, especificamente à forçante atmosférica e estrutura de densidade na coluna d\'água nas latitudes ao sul de 20ºS. / Sea surface height data measured from altimetry satellites and outputs of two ocean general circulation models (OGCM for the Earth Simulator - OFES and Community Earth System Model - CESM) were used to determine whether climate numerical models reproduce the Rossby waves in a manner similar to those observed in altimetry record in the South Atlantic. The models differs in the forcing, OFES is forced with NCEP-NCAR data while CESM is coupled with atmospheric model, ice and land model. Because these waves depend on the internal density structure and wind forcing, we can make inferences about the suitability of these two factors in the models in comparison with the altimetry data used as a reference. A series of finite impulse response band-pass filters (FIR-2D) was applied to isolate the westward propagating signals corresponding to Rossby waves in the altimeter. Both models are able to reproduce Rossby waves and show better results in low latitudes. However, the OFES model presented more difficulty to reproduce the wave parameters found in altimeter with differences of up to 68% for amplitude, 34% for the wavelength and 38% for phase velocity. By contrast the greatest differences between the wave parameters computed from the altimeter data and the CESM model were 32% for amplitude, 20% for the wavelength and 20% for phase velocity. Furthermore, the CESM model was capable of reproducing the seasonal signal correlation with an average of approximately 0.7 with altimeter\'s seasonal signal found throughout the South Atlantic basin, while the OFES\'s seasonal signal showed an average correlation 0.4 with the signal found by the satellite. These results indicate that both models can reproduce the phenomenon satisfactorily, the CESM better than OFES. The difference between the results should be related with the aspects cited above, specifically with the atmospheric forcing and the density structure in the water column in latitudes southern then 20ºS.

A Amazônia é a maior floresta tropical do mundo e desempenha papel fundamental na regulação climática do continente sul-americano. A expansão de atividades antrópicas ocorridas na Amazônia nos últimos 70 anos provocou mudanças nos padrões de cobertura do solo na região que levaram ao surgimento de diversas políticas de conservação em nível nacional e internacional. Uma das principais técnicas para o monitoramento e acompanhamento do desenvolvimento dessas políticas são as técnicas fornecidas pelo sensoriamento remoto. Esse trabalho tem por objetivo avaliar o desempenho de três classificadores de imagens digitais (Mínima Distância Euclidiana, Máxima Verrosimilhança e Extration and Classification of Homogeneous Objects) na região central da Amazônia brasileira. Foram utilizadas duas abordagens para realizar as classificações, na primeira os classificadores foram aplicados sobre uma imagem do satélite Landsat - 8 que teve seus números digitais convertidos para valores de refletância e na segunda abordagem os classificadores foram aplicados sobre imagens fração resultantes da aplicação do modelo linear de mistura espectral na imagem do Landsat - 8. Para avaliar os desempenho dos classificadores e das abordagens propostas aplicou-se uma matriz de confusão e foi calculado o índice Kappa para cada um dos resultados obtidos. Os resultados mostraram que o Máxima verossimilhança apresentou o melhor desempenho nas duas abordagem seguido pelo ECHO com resultados próximos. O Mínima Distância teve o pior desempenho nas duas abordagem. Os resultados também indicaram que a redução da dimensionalidade dos dados provocadas pelo modelo linear de mistura espectral foi capaz de melhorar o desempenho apenas do ECHO. / The Amazon is the largest tropical forest in the world and plays a key role in the climate regulation in South America.In the last 70 years, the expansion of anthropogenic activities in this biome has led to changes in land´s cover patterns in that region which have led to the emergence of several conservation policies in national and international levels. One of the main techniques of monitoring the development of these policies is the technique provided by remote sensing. This theses aims to evaluate the performance of three digital image classifiers (Minimum Distance, Maximum Verification and Extraction and Classification of Homogeneous Objects) in the Brazilian’s Amazon central region. Two approaches were used to perform the classifications. To the first one the classifiers were applied on the satellite Landsat – 8’s image that had its digital numbers converted to values of reflectance. To the second approach the classifiers were applied on fraction images resulting from the application of the linear model of spectral mixing in the Landsat-8 image. To evaluate the performance of the proposed classifiers and approaches a confusion matrix the Kappa index was adopted to calculate each of the obtained results. The results showed that the maximum probability has presented the best performance in the two approaches followed by ECHO with close results. The Minimum Distance had the worst performance in both approaches. The results also indicated that the reduction of data dimensionality caused by the linear spectral mixing model was able to improve the performance of only ECHO.

A Área de Proteção Ambiental do Banhado Grande na Bacia Hidrográfica do rio Gravataí, inserida na região metropolitana de Porto Alegre, abriga uma extensa Área Úmida em sua porção central. A partir de técnicas de Sensoriamento Remoto e Geoprocessamento para a análise das variáveis físicas como, geologia, cota altimétrica, pedologia e índices de vegetação como o NDVI e o NDWI, foi possível classificar compartimentos de Unidades de Paisagem associados às Áreas Úmidas em: Unidade de Paisagem Turfeira e Unidade de Paisagem / Planície de Inundação. A delimitação destas áreas, visa o planejamento do uso racional destes ambientes para a sua manutenção e preservação. No início da década de 1970, um trecho do rio Gravataí foi canalizado, com objetivo de drenar as Áreas Úmidas e viabilizar a expansão das áreas de cultivo do arroz, esta intervenção ocasionou um processo erosivo em forma de voçoroca no Banhado Grande, no município de Glorinha. A partir de uma série temporal de imagens satelitais foi possível mapear e quantificar a evolução do processo erosivo da voçoroca entre os anos de 2003 a 2015. Os resultados do mapeamento mostraram um aumento de quatro vezes na área da voçoroca de 2909,62 m² em 2003 para 12097,70 m² em 2015. No mapeamento da voçoroca e no monitoramento dos processos erosivos no banhado foram o uso das técnicas como: a) monitoramento por estaqueamento; b) mapeamento por imagens de satélite; b) mapeamento por varredura de Laser Scanner Terrestre. O Laser Scanner Terrestre mostrou-se uma ferramenta potencial para o mapeamento da voçoroca em virtude de sua alta precisão e rapidez na coleta de dados no campo, gerando modelos digitais de elevação com alta precisão. O uso do modelo permitiu identificar áreas de erosão deposição e de sedimentos, a partir do perfil topográfico. É necessário o monitoramento contínuo do processo erosivo na área do Banhado Grande, combinando métodos para modelar a sua dinâmica. Essas ferramentas de apoio são fundamentais para a elaboração do Plano de Manejo e estudos que visam a restauração das Áreas Úmidas do rio Gravataí. / The Banhado Grande Environmental Protected Area in the Gravataí river basin, located in the metropolitan area of Porto Alegre, has an extensive wetland area in its central portion. From remote sensing and geoprocessing techniques for the analysis of physical variables such as geology, topography, pedology and vegetation indices such as NDVI and NDWI, it was possible to classify compartments of Landscape Units associated to Wetlands in: Peat Landscape Unit and Landscape Unit / Flood Plain. The delimitation of these areas, aims at planning the rational use of these environments for their maintenance and preservation. In the beginning of the 1970s, a section of the Gravataí river was channeled, with the objective of draining the wetlands and making possible the expansion of rice cultivation areas, this intervention caused an erosive process in the form of gully in Banhado Grande, in the municipality of Glorinha. From a time series of satellite images, it was possible to map and quantify the evolution of the erosion process of the voçoroca between the years 2003 to 2015. The results of the mapping showed a significant increase in the gully of 2909.62 m² in 2003 to 12097.70 m² in 2015. In the mapping of gully and in the monitoring of the erosive processes in the swamp, were used techniques such as: a) stacking monitoring; b) mapping by satellite images; b) scanning mapping of terrestrial Laser Scanner. The terrestrial Laser Scanner has proved to be a potential tool for the mapping of the gully because of its high precision and rapid data collection in the field, generating digital elevation models with high precision. The use of the model allowed identifying areas of erosion deposition and sediment from the topographic profile. It is necessary, however, to choose suitable techniques for the continuous monitoring of the erosive process in the area of the Grande Banhado, combining methods to model the dynamics. These support tools are fundamental for the elaboration of the Management Plan and studies that aim at the restoration of the wetlands of the Gravataí river flood plain.

D’une part, les instruments permettant de mesurer les précipitations (pluviomètres, radars, etc.) effectuent des mesures de natures différentes et à différentes échelles. Leurs données sont difficilement comparables. D’autre part, les modèles décrivant l’évolution des précipitations sont eux complexes et difficiles à paramétrer et à valider. Dans cette thèse, nous utilisons l’assimilation de données afin de coupler des observations hétérogènes des précipitations et des modèles, pour étudier les précipitations et leur variabilité spatiotemporelle à différentes échelles (macrophysique, qui s’intéresse aux cellules de pluie, et microphysique, qui s’intéresse à la distribution en taille des gouttes – DSD – qui les composent). Tout d’abord, nous développons un algorithme permettant de restituer des cartes de précipitations à partir de mesures de l’atténuation causée par la pluie à des ondes provenant de satellites de télévision. Nos restitutions sont validées par rapport à des données radar et pluviomètres sur un cas d’étude dans le sud de la France. Ensuite, nous restituons, toujours par assimilation de données, des profils verticaux de DSD et de vents verticaux à partir de mesures de flux de gouttes au sol (par disdromètres) et de spectres Doppler en altitude (par radar). Nous utilisons ces restitutions sur 3 cas d’étude pour étudier les phénomènes physiques agissant sur les gouttes de pluie durant leur chute et pour évaluer la paramétrisation de ces phénomènes dans les modèles. / On the one hand, the instruments designed to measure rainfall (rain gages, radars, etc.) perform measurements at different scales and of different natures. Their data are hard to compare. On the other hand, models simulating the evolution of rainfall are complex. It is not an easy task to parameterize and to validate them. In this thesis, we use data assimilation in order to couple heterogeneous observations of rainfall and models for studying rain and its spatiotemporal variability at different scales (macrophysical scale, which is interested in rain cells, as well as microphysical scale, which is interested in the drop size distribution – DSD). First, we develop an algorithm able to retrieve rain maps from measurements of attenuation of waves coming from TV satellites due to rainfall. Our retrievals are validated by comparison with radar and rain gages data for a case study in south of France. Second, we retrieve – again with data assimilation – vertical profiles of DSD and vertical winds from measurements of rain drop fluxes on the ground (using a disdrometer) and of Doppler spectra aloft (using a radar). We use these retrievals for 3 case studies to study the physical phenomena acting on rain drops during their fall and to evaluate the parameterization of these phenomena in models.

Thesis. 1976. Ph.D.--Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. / Microfiche copy available in Archives and Engineering. / Vita. / Includes bibliographical references. / Ph.D.

Thesis. 1976. Ph.D.--Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. / Microfiche copy available in Archives and Engineering. / Vita. / Includes bibliographical references. / Ph.D.

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1981. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING. / Vita. / Includes bibliographical references. / by Martin Glen Bello. / Ph.D.