Computational methods to create and analyze a digital gene expression atlas of embryo development from microscopy images

Abstract The creation of atlases, or digital models where information from different subjects can be combined, is a field of increasing interest in biomedical imaging. When a single image does not contain enough information to appropriately describe the organism under study, it is then necessary to acquire images of several individuals, each of them containing complementary data with respect to the rest of the components in the cohort. This approach allows creating digital prototypes, ranging from anatomical atlases of human patients and organs, obtained for instance from Magnetic Resonance Imaging, to gene expression cartographies of embryo development, typically achieved from Light Microscopy. Within such context, in this PhD Thesis we propose, develop and validate new dedicated image processing methodologies that, based on image registration techniques, bring information from multiple individuals into alignment within a single digital atlas model. We also elaborate a dedicated software visualization platform to explore the resulting wealth of multi-dimensional data and novel analysis algo-rithms to automatically mine the generated resource in search of bio¬logical insights. In particular, this work focuses on gene expression data from developing zebrafish embryos imaged at the cellular resolution level with Two-Photon Laser Scanning Microscopy. Disposing of quantitative measurements relating multiple gene expressions to cell position and their evolution in time is a fundamental prerequisite to understand embryogenesis multi-scale processes. However, the number of gene expressions that can be simultaneously stained in one acquisition is limited due to optical and labeling constraints. These limitations motivate the implementation of atlasing strategies that can recreate a virtual gene expression multiplex. The developed computational tools have been tested in two different scenarios. The first one is the early zebrafish embryogenesis where the resulting atlas constitutes a link between the phenotype and the genotype at the cellular level. The second one is the late zebrafish brain where the resulting atlas allows studies relating gene expression to brain regionalization and neurogenesis. The proposed computational frameworks have been adapted to the requirements of both scenarios, such as the integration of partial views of the embryo into a whole embryo model with cellular resolution or the registration of anatom¬ical traits with deformable transformation models non-dependent on any specific labeling. The software implementation of the atlas generation tool (Match-IT) and the visualization platform (Atlas-IT) together with the gene expression atlas resources developed in this Thesis are to be made freely available to the scientific community. Lastly, a novel proof-of-concept experiment integrates for the first time 3D gene expression atlas resources with cell lineages extracted from live embryos, opening up the door to correlate genetic and cellular spatio-temporal dynamics. La creación de atlas, o modelos digitales, donde la información de distintos sujetos puede ser combinada, es un campo de creciente interés en imagen biomédica. Cuando una sola imagen no contiene suficientes datos como para describir apropiadamente el organismo objeto de estudio, se hace necesario adquirir imágenes de varios individuos, cada una de las cuales contiene información complementaria respecto al resto de componentes del grupo. De este modo, es posible crear prototipos digitales, que pueden ir desde atlas anatómicos de órganos y pacientes humanos, adquiridos por ejemplo mediante Resonancia Magnética, hasta cartografías de la expresión genética del desarrollo de embrionario, típicamente adquiridas mediante Microscopía Optica. Dentro de este contexto, en esta Tesis Doctoral se introducen, desarrollan y validan nuevos métodos de procesado de imagen que, basándose en técnicas de registro de imagen, son capaces de alinear imágenes y datos provenientes de múltiples individuos en un solo atlas digital. Además, se ha elaborado una plataforma de visualization específicamente diseñada para explorar la gran cantidad de datos, caracterizados por su multi-dimensionalidad, que resulta de estos métodos. Asimismo, se han propuesto novedosos algoritmos de análisis y minería de datos que permiten inspeccionar automáticamente los atlas generados en busca de conclusiones biológicas significativas. En particular, este trabajo se centra en datos de expresión genética del desarrollo embrionario del pez cebra, adquiridos mediante Microscopía dos fotones con resolución celular. Disponer de medidas cuantitativas que relacionen estas expresiones genéticas con las posiciones celulares y su evolución en el tiempo es un prerrequisito fundamental para comprender los procesos multi-escala característicos de la morfogénesis. Sin embargo, el número de expresiones genéticos que pueden ser simultáneamente etiquetados en una sola adquisición es reducido debido a limitaciones tanto ópticas como del etiquetado. Estas limitaciones requieren la implementación de estrategias de creación de atlas que puedan recrear un multiplexado virtual de expresiones genéticas. Las herramientas computacionales desarrolladas han sido validadas en dos escenarios distintos. El primer escenario es el desarrollo embrionario temprano del pez cebra, donde el atlas resultante permite constituir un vínculo, a nivel celular, entre el fenotipo y el genotipo de este organismo modelo. El segundo escenario corresponde a estadios tardíos del desarrollo del cerebro del pez cebra, donde el atlas resultante permite relacionar expresiones genéticas con la regionalización del cerebro y la formación de neuronas. La plataforma computacional desarrollada ha sido adaptada a los requisitos y retos planteados en ambos escenarios, como la integración, a resolución celular, de vistas parciales dentro de un modelo consistente en un embrión completo, o el alineamiento entre estructuras de referencia anatómica equivalentes, logrado mediante el uso de modelos de transformación deformables que no requieren ningún marcador específico. Está previsto poner a disposición de la comunidad científica tanto la herramienta de generación de atlas (Match-IT), como su plataforma de visualización (Atlas-IT), así como las bases de datos de expresión genética creadas a partir de estas herramientas. Por último, dentro de la presente Tesis Doctoral, se ha incluido una prueba conceptual innovadora que permite integrar los mencionados atlas de expresión genética tridimensionales dentro del linaje celular extraído de una adquisición in vivo de un embrión. Esta prueba conceptual abre la puerta a la posibilidad de correlar, por primera vez, las dinámicas espacio-temporales de genes y células.

Diminished UV-absorbing nets reduce the Spreads and population density of Macrosiphum euphorbiae in lettuce.

UV-absorbing covers reduce the incidence of injurious insect pests and viruses in protected crops. In the present study, the effect of a UV-absorbing net (Bionet) on the spatio-temporal dynamics of the potato aphid on lettuce plants was evaluated. A field experiment was conducted during three seasons in two identical tunnels divided in four plots. A set of lettuce plants were artificially infested with Macrosiphum euphorbiae adults and the population was estimated by counting aphids on every plant over 7 to 9 weeks. Insect population grew exponentially but a significantly lower aphid density was present on plants grown under the UV-absorbing cover compared to a standard 50 mesh net. Similarly, in laboratory conditions, life table parameters were significantly reduced under the Bionet. Moreover, SADIE analysis showed that the spatial distribution of aphids was effectively limited under the UV-absorbing nets. Our results indicate that UV-absorbing nets should be considered as an important component of lettuce indoor cropping systems preventing pesticide applications and reducing the risk of spread of aphid-borne virus diseases.

Reconstructing the Timing and Dispersion Routes of HIV-1 Subtype B Epidemics in The Caribbean and Central America: A Phylogenetic Story.

The Caribbean and Central America are among the regions with highest HIV-1B prevalence worldwide. Despite of this high virus burden, little is known about the timing and the migration patterns of HIV-1B in these regions. Migration is one of the major processes shaping the genetic structure of virus populations. Thus, reconstruction of epidemiological network may contribute to understand HIV-1B evolution and reduce virus prevalence. We have investigated the spatio-temporal dynamics of the HIV-1B epidemic in The Caribbean and Central America using 1,610 HIV-1B partial pol sequences from 13 Caribbean and 5 Central American countries. Timing of HIV-1B introduction and virus evolutionary rates, as well as the spatial genetic structure of the HIV-1B populations and the virus migration patterns were inferred. Results revealed that in The Caribbean and Central America most of the HIV-1B variability was generated since the 80 s. At odds with previous data suggesting that Haiti was the origin of the epidemic in The Caribbean, our reconstruction indicated that the virus could have been disseminated from Puerto Rico and Antigua. These two countries connected two distinguishable migration areas corresponding to the (mainly Spanish-colonized) Easter and (mainly British-colonized) Western islands, which indicates that virus migration patterns are determined by geographical barriers and by the movement of human populations among culturally related countries. Similar factors shaped the migration of HIV-1B in Central America. The HIV-1B population was significantly structured according to the country of origin, and the genetic diversity in each country was associated with the virus prevalence in both regions, which suggests that virus populations evolve mainly through genetic drift. Thus, our work contributes to the understanding of HIV-1B evolution and dispersion pattern in the Americas, and its relationship with the geography of the area and the movements of human populations.

Monthly Arctic sea ice lead fraction in 0.5° x 0.5° resolution from SARAL/Altika altimeter, link to datasets in NetCDF 4 format

Sea ice leads play an essential role in ocean-ice-atmosphere exchange, in ocean circulation, geochemistry, and in ice dynamics. Their precise detection is crucial for altimetric estimations of sea ice thickness and volume. This study evaluates the performance of the SARAL/AltiKa (Satellite with ARgos and ALtiKa) altimeter to detect leads and to monitor their spatio-temporal dynamics. We show that a pulse peakiness parameter (PP) used to detect leads by Envisat RA-2 and ERS-1,-2 altimeters is not suitable because of saturation of AltiKa return echoes over the leads. The signal saturation results in loss of 6-10% of PP data over sea ice. We propose a different parameter-maximal power of waveform-and define the threshold to discriminate the leads. Our algorithm can be applied from December until May. It detects well the leads of small and medium size from 200 m to 3-4 km. So the combination of the high-resolution altimetric estimates with low-resolution thermal infra-red or radiometric lead fraction products could enhance the capability of remote sensing to monitor sea ice fracturing.

Marqueurs électrophysiologiques des dysfonctions attentionnelles et de leur récupération suite à un traumatisme craniocérébral léger

L’objectif principal de cette thèse était d’obtenir, via l’électrophysiologie cognitive, des indices de fonctionnement post-traumatisme craniocérébral léger (TCCL) pour différents niveaux de traitement de l’information, soit l’attention sélective, les processus décisionnels visuoattentionnels et les processus associés à l’exécution d’une réponse volontaire. L’hypothèse centrale était que les mécanismes de production des lésions de même que la pathophysiologie caractérisant le TCCL engendrent des dysfonctions visuoattentionnelles, du moins pendant la période aiguë suivant le TCCL (i.e. entre 1 et 3 mois post-accident), telles que mesurées à l’aide d’un nouveau paradigme électrophysiologique conçu à cet effet. Cette thèse présente deux articles qui décrivent le travail effectué afin de rencontrer ces objectifs et ainsi vérifier les hypothèses émises. Le premier article présente la démarche réalisée afin de créer une nouvelle tâche d’attention visuospatiale permettant d’obtenir les indices électrophysiologiques (amplitude, latence) et comportementaux (temps de réaction) liés aux processus de traitement visuel et attentionnel précoce (P1, N1, N2-nogo, P2, Ptc) à l’attention visuelle sélective (N2pc, SPCN) et aux processus décisionnels (P3b, P3a) chez un groupe de participants sains (i.e. sans atteinte neurologique). Le deuxième article présente l’étude des effets persistants d’un TCCL sur les fonctions visuoattentionelles via l’obtention des indices électrophysiologiques ciblés (amplitude, latence) et de données comportementales (temps de réaction à la tâche et résultats aux tests neuropsychologiques) chez deux cohortes d’individus TCCL symptomatiques, l’une en phase subaigüe (3 premiers mois post-accident), l’autre en phase chronique (6 mois à 1 an post-accident), en comparaison à un groupe de participants témoins sains. Les résultats des articles présentés dans cette thèse montrent qu’il a été possible de créer une tâche simple qui permet d’étudier de façon rapide et peu coûteuse les différents niveaux de traitement de l’information impliqués dans le déploiement de l’attention visuospatiale. Par la suite, l’utilisation de cette tâche auprès d’individus atteints d’un TCCL testés en phase sub-aiguë ou en phase chronique a permis d’objectiver des profils d’atteintes et de récupération différentiels pour chacune des composantes étudiées. En effet, alors que les composantes associées au traitement précoce de l’information visuelle (P1, N1, N2) étaient intactes, certaines composantes attentionnelles (P2) et cognitivo-attentionnelles (P3a, P3b) étaient altérées, suggérant une dysfonction au niveau des dynamiques spatio-temporelles de l’attention, de l’orientation de l’attention et de la mémoire de travail, à court et/ou à long terme après le TCCL, ceci en présence de déficits neuropsychologiques en phase subaiguë surtout et d’une symptomatologie post-TCCL persistante. Cette thèse souligne l’importance de développer des outils diagnostics sensibles et exhaustifs permettant d’objectiver les divers processus et sous-processus cognitifs susceptible d’être atteints après un TCCL.

Dynamique des ambiances lumineuses - approche basée sur la photométrie vidéo d’espaces de transition

Les variations de la lumière naturelle lors du passage d’un espace à un autre caractérisent de manière complexe, mais importante le design d’un bâtiment. Cette adaptation visuelle s’inscrit dans un processus spatiotemporel et influe sur le confort et le bien-être de ses occupants. La littérature fait état du peu de connaissances de la relation lumière espace-temps. Cette recherche propose donc d’étudier cette relation spatio-temporelle existant entre la lumière et l’espace, afin de qualifier un parcours architectural au moyen d’une expérimentation in situ et de segments filmiques. La recherche combine l’utilisation d’un luminance-mètre, d’une caméra vidéo et d’une méthode d’analyse d’images numériques afin de permettre l’évaluation des qualités spatio-temporelles de la lumière. Le parcours architectural est analysé selon la diversité et l’intensité des ambiances lumineuses en fonction du temps permettant de décrire les perceptions visuelles d’espaces transitions. Cette méthode dynamique offre un potentiel d’analyse et de création aux concepteurs désireux d’enrichir le design de séquences spatiales en favorisant la diversité lumineuse dans l’expérience architecturale. Mots clefs: adaptation visuelle, analyse d’images, ambiance lumineuse, contraste, éclairage naturel, espaces transitions, lumière perception visuelle, vidéo, spatio-temporel.

Three-dimensional kinetic simulations of active suspensions: effect of chemotaxis and steric interaction

In this work, the effects of chemotaxis and steric interactions in active suspensions are analyzed by extending the kinetic model proposed by Saintillan and Shelley [1, 2]. In this model, a conservation equation for the active particle configuration is coupled to the Stokes equation for the flow arising from the force dipole exerted by the particles on the fluid. The fluid flow equations are solved spectrally and the conservation equation is solved by second-order finite differencing in space and second-order Adams-Bashforth time marching. First, the dynamics in suspensions of oxytactic run-and-tumble bacteria confined in thin liquid films surrounded by air is investigated. These bacteria modify their tumbling behavior by making temporal comparisons of the oxygen concentration, and, on average, swim towards high concentrations of oxygen. The kinetic model proposed by Saintillan and Shelley [1, 2] is modified to include run-and-tumble effects and oxygentaxis. The spatio-temporal dynamics of the oxygen and bacterial concentration are analyzed. For small film thicknesses, there is a weak migration of bacteria to the boundaries, and the oxygen concentration is high inside the film as a result of diffusion; both bacterial and oxygen concentrations quickly reach steady states. Above a critical film thickness (approximately 200 micron), a transition to chaotic dynamics is observed and is characterized by turbulent-like 3D motion, the formation of bacterial plumes, enhanced oxygen mixing and transport into the film, and hydrodynamic velocities of magnitudes up to 7 times the single bacterial swimming speed. The simulations demonstrate that the combined effects of hydrodynamic interactions and oxygentaxis create collective three-dimensional instabilities which enhances oxygen availability for the bacteria. Our simulation results are consistent with the experimental findings of Sokolov et al. [3], who also observed a similar transition with increasing film thickness. Next, the dynamics in concentrated suspensions of active self-propelled particles in a 3D periodic domain are analyzed. We modify the kinetic model of Saintillan and Shelley [1, 2] by including an additional nematic alignment torque proportional to the local concentration in the equation for the rotational velocity of the particles, causing them to align locally with their neighbors (Doi and Edwards [4]). Large-scale three- dimensional simulations show that, in the presence of such a torque both pusher and puller suspensions are unstable to random fluctuations and are characterized by highly nematic structures. Detailed measures are defined to quantify the degree and direction of alignment, and the effects of steric interactions on pattern formation will be presented. Our analysis shows that steric interactions have a destabilizing effect in active suspensions.

Integração de modelos espaciais e temporais para predições de níveis freáticos extremos

O objetivo deste trabalho foi avaliar cenários de níveis freáticos extremos, em bacia hidrográfica, por meio de métodos de análise espacial de dados geográficos. Avaliou-se a dinâmica espaço‑temporal dos recursos hídricos subterrâneos em área de afloramento do Sistema Aquífero Guarani. As alturas do lençol freático foram estimadas por meio do monitoramento de níveis em 23 piezômetros e da modelagem das séries temporais disponíveis de abril de 2004 a abril de 2011. Para a geração de cenários espaciais, foram utilizadas técnicas geoestatísticas que incorporaram informações auxiliares relativas a padrões geomorfológicos da bacia, por meio de modelo digital de terreno. Esse procedimento melhorou as estimativas, em razão da alta correlação entre altura do lençol e elevação, e agregou sentido físico às predições. Os cenários apresentaram diferenças quanto aos níveis considerados extremos - muito profundos ou muito superficiais - e podem subsidiar o planejamento, o uso eficiente da água e a gestão sustentável dos recursos hídricos na bacia.

Marqueurs électrophysiologiques des dysfonctions attentionnelles et de leur récupération suite à un traumatisme craniocérébral léger

L’objectif principal de cette thèse était d’obtenir, via l’électrophysiologie cognitive, des indices de fonctionnement post-traumatisme craniocérébral léger (TCCL) pour différents niveaux de traitement de l’information, soit l’attention sélective, les processus décisionnels visuoattentionnels et les processus associés à l’exécution d’une réponse volontaire. L’hypothèse centrale était que les mécanismes de production des lésions de même que la pathophysiologie caractérisant le TCCL engendrent des dysfonctions visuoattentionnelles, du moins pendant la période aiguë suivant le TCCL (i.e. entre 1 et 3 mois post-accident), telles que mesurées à l’aide d’un nouveau paradigme électrophysiologique conçu à cet effet. Cette thèse présente deux articles qui décrivent le travail effectué afin de rencontrer ces objectifs et ainsi vérifier les hypothèses émises. Le premier article présente la démarche réalisée afin de créer une nouvelle tâche d’attention visuospatiale permettant d’obtenir les indices électrophysiologiques (amplitude, latence) et comportementaux (temps de réaction) liés aux processus de traitement visuel et attentionnel précoce (P1, N1, N2-nogo, P2, Ptc) à l’attention visuelle sélective (N2pc, SPCN) et aux processus décisionnels (P3b, P3a) chez un groupe de participants sains (i.e. sans atteinte neurologique). Le deuxième article présente l’étude des effets persistants d’un TCCL sur les fonctions visuoattentionelles via l’obtention des indices électrophysiologiques ciblés (amplitude, latence) et de données comportementales (temps de réaction à la tâche et résultats aux tests neuropsychologiques) chez deux cohortes d’individus TCCL symptomatiques, l’une en phase subaigüe (3 premiers mois post-accident), l’autre en phase chronique (6 mois à 1 an post-accident), en comparaison à un groupe de participants témoins sains. Les résultats des articles présentés dans cette thèse montrent qu’il a été possible de créer une tâche simple qui permet d’étudier de façon rapide et peu coûteuse les différents niveaux de traitement de l’information impliqués dans le déploiement de l’attention visuospatiale. Par la suite, l’utilisation de cette tâche auprès d’individus atteints d’un TCCL testés en phase sub-aiguë ou en phase chronique a permis d’objectiver des profils d’atteintes et de récupération différentiels pour chacune des composantes étudiées. En effet, alors que les composantes associées au traitement précoce de l’information visuelle (P1, N1, N2) étaient intactes, certaines composantes attentionnelles (P2) et cognitivo-attentionnelles (P3a, P3b) étaient altérées, suggérant une dysfonction au niveau des dynamiques spatio-temporelles de l’attention, de l’orientation de l’attention et de la mémoire de travail, à court et/ou à long terme après le TCCL, ceci en présence de déficits neuropsychologiques en phase subaiguë surtout et d’une symptomatologie post-TCCL persistante. Cette thèse souligne l’importance de développer des outils diagnostics sensibles et exhaustifs permettant d’objectiver les divers processus et sous-processus cognitifs susceptible d’être atteints après un TCCL.

Analyse du compartiment mésozooplanctonique et écologie alimentaire printanière de la sardine, Sardina pilchardus (Walbaum, 1782), et de l’anchois, Engraulis encrasicolus (Linné, 1758) adultes dans le Golfe de Gascogne

Dietary studies of marine species constitute an important key to improve the understanding of its biology and of its role in the ecosystem. Thus, prey-predator relationships structure and determine population dynamics and the trophic network at the ecosystem scale. Among the major study sites, the marine ecosystem is submitted to natural and anthropogenic constraints. In the North-Eastern part of the Atlantic Ocean, the Bay of Biscay is a large open area surrounded South by Spain and East by France. This bay is an historic place of intense fishery activities for which the main small pelagic species targeted are the pilchard, Sardina pilchardus and the anchovy, Engraulis encrasicolus. The aim of this work is to analyze the trophic ecology of these two small pelagic fish in spring in the Bay of Biscay. To do this, a first section is devoted to their prey composed by the mesozooplanktonic compartment, through a two-fold approach: the characterization of their spatio-temporal dynamics during the decade 2003-2013 and the measurement of their energetic content in spring. For this season, it appears that all prey types are not worth energetically and that the Bay of Biscay represents a mosaic of dietary habitat. Moreover, the spring mesozooplankton community presents a strong spatial structuration, a temporal evolution marked by a major change in abundance and a control by the microphytoplankton biomass. The second section of this work is relative to a methodological approach of the trophic ecology of S. pilchardus and E. encrasicolus. Three different trophic tracers have been used: isotopic ratios of carbon and nitrogen, parasitological fauna and mercury contamination levels. To improve the use of the first of these trophic tracers, an experimental approach has been conducted with S. pilchardus to determine a trophic discrimination factor. Finally, it appears that the use of these three trophic tracers has always been permitted to highlight a temporal variability of the relative trophic ecology of these fish. However, no spatial dynamics could be identified through these three trophic tracers.

Comparison of multitemporal MODIS-EVI smoothing algorithms and its contribution to crop monitoring.

Crop monitoring and more generally land use change detection are of primary importance in order to analyze spatio-temporal dynamics and its impacts on environment. This aspect is especially true in such a region as the State of Mato Grosso (south of the Brazilian Amazon Basin) which hosts an intensive pioneer front. Deforestation in this region as often been explained by soybean expansion in the last three decades. Remote sensing techniques may now represent an efficient and objective manner to quantify how crops expansion really represents a factor of deforestation through crop mapping studies. Due to the special characteristics of the soybean productions' farms in Mato Grosso (area varying between 1000 hectares and 40000 hectares and individual fields often bigger than 100 hectares), the Moderate Resolution Imaging Spectroradiometer (MODIS) data with a near daily temporal resolution and 250 m spatial resolution can be considered as adequate resources to crop mapping. Especially, multitemporal vegetation indices (VI) studies have been currently used to realize this task [1] [2]. In this study, 16-days compositions of EVI (MODQ13 product) data are used. However, although these data are already processed, multitemporal VI profiles still remain noisy due to cloudiness (which is extremely frequent in a tropical region such as south Amazon Basin), sensor problems, errors in atmospheric corrections or BRDF effect. Thus, many works tried to develop algorithms that could smooth the multitemporal VI profiles in order to improve further classification. The goal of this study is to compare and test different smoothing algorithms in order to select the one which satisfies better to the demand which is classifying crop classes. Those classes correspond to 6 different agricultural managements observed in Mato Grosso through an intensive field work which resulted in mapping more than 1000 individual fields. The agricultural managements above mentioned are based on combination of soy, cotton, corn, millet and sorghum crops sowed in single or double crop systems. Due to the difficulty in separating certain classes because of too similar agricultural calendars, the classification will be reduced to 3 classes : Cotton (single crop), Soy and cotton (double crop), soy (single or double crop with corn, millet or sorghum). The classification will use training data obtained in the 2005-2006 harvest and then be tested on the 2006-2007 harvest. In a first step, four smoothing techniques are presented and criticized. Those techniques are Best Index Slope Extraction (BISE) [3], Mean Value Iteration (MVI) [4], Weighted Least Squares (WLS) [5] and Savitzky-Golay Filter (SG) [6] [7]. These techniques are then implemented and visually compared on a few individual pixels so that it allows doing a first selection between the five studied techniques. The WLS and SG techniques are selected according to criteria proposed by [8]. Those criteria are: ability in eliminating frequent noises, conserving the upper values of the VI profiles and keeping the temporality of the profiles. Those selected algorithms are then programmed and applied to the MODIS/TERRA EVI data (16-days composition periods). Tests of separability are realized based on the Jeffries-Matusita distance in order to see if the algorithms managed in improving the potential of differentiation between the classes. Those tests are realized on the overall profile (comprising 23 MODIS images) as well as on each MODIS sub-period of the profile [1]. This last test is a double interest process because it allows comparing the smoothing techniques and also enables to select a set of images which carries more information on the separability between the classes. Those selected dates can then be used to realize a supervised classification. Here three different classifiers are tested to evaluate if the smoothing techniques as a particular effect on the classification depending on the classifiers used. Those classifiers are Maximum Likelihood classifier, Spectral Angle Mapper (SAM) classifier and CHAID Improved Decision tree. It appears through the separability tests on the overall process that the smoothed profiles don't improve efficiently the potential of discrimination between classes when compared with the original data. However, the same tests realized on the MODIS sub-periods show better results obtained with the smoothed algorithms. The results of the classification confirm this first analyze. The Kappa coefficients are always better with the smoothing techniques and the results obtained with the WLS and SG smoothed profiles are nearly equal. However, the results are different depending on the classifier used. The impact of the smoothing algorithms is much better while using the decision tree model. Indeed, it allows a gain of 0.1 in the Kappa coefficient. While using the Maximum Likelihood end SAM models, the gain remains positive but is much lower (Kappa improved of 0.02 only). Thus, this work's aim is to prove the utility in smoothing the VI profiles in order to improve the final results. However, the choice of the smoothing algorithm has to be made considering the original data used and the classifier models used. In that case the Savitzky-Golay filter gave the better results.

Spatial and temporal analysis of Barmah Forest virus disease in Queensland, Australia

Barmah Forest virus (BFV) disease is one of the most widespread mosquito-borne diseases in Australia. The number of outbreaks and the incidence rate of BFV in Australia have attracted growing concerns about the spatio-temporal complexity and underlying risk factors of BFV disease. A large number of notifications has been recorded continuously in Queensland since 1992. Yet, little is known about the spatial and temporal characteristics of the disease. I aim to use notification data to better understand the effects of climatic, demographic, socio-economic and ecological risk factors on the spatial epidemiology of BFV disease transmission, develop predictive risk models and forecast future disease risks under climate change scenarios. Computerised data files of daily notifications of BFV disease and climatic variables in Queensland during 1992-2008 were obtained from Queensland Health and Australian Bureau of Meteorology, respectively. Projections on climate data for years 2025, 2050 and 2100 were obtained from Council of Scientific Industrial Research Organisation. Data on socio-economic, demographic and ecological factors were also obtained from relevant government departments as follows: 1) socio-economic and demographic data from Australian Bureau of Statistics; 2) wetlands data from Department of Environment and Resource Management and 3) tidal readings from Queensland Department of Transport and Main roads. Disease notifications were geocoded and spatial and temporal patterns of disease were investigated using geostatistics. Visualisation of BFV disease incidence rates through mapping reveals the presence of substantial spatio-temporal variation at statistical local areas (SLA) over time. Results reveal high incidence rates of BFV disease along coastal areas compared to the whole area of Queensland. A Mantel-Haenszel Chi-square analysis for trend reveals a statistically significant relationship between BFV disease incidence rates and age groups (ƒÓ2 = 7587, p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. A cluster analysis was used to detect the hot spots/clusters of BFV disease at a SLA level. Most likely spatial and space-time clusters are detected at the same locations across coastal Queensland (p<0.05). The study demonstrates heterogeneity of disease risk at a SLA level and reveals the spatial and temporal clustering of BFV disease in Queensland. Discriminant analysis was employed to establish a link between wetland classes, climate zones and BFV disease. This is because the importance of wetlands in the transmission of BFV disease remains unclear. The multivariable discriminant modelling analyses demonstrate that wetland types of saline 1, riverine and saline tidal influence were the most significant risk factors for BFV disease in all climate and buffer zones, while lacustrine, palustrine, estuarine and saline 2 and saline 3 wetlands were less important. The model accuracies were 76%, 98% and 100% for BFV risk in subtropical, tropical and temperate climate zones, respectively. This study demonstrates that BFV disease risk varied with wetland class and climate zone. The study suggests that wetlands may act as potential breeding habitats for BFV vectors. Multivariable spatial regression models were applied to assess the impact of spatial climatic, socio-economic and tidal factors on the BFV disease in Queensland. Spatial regression models were developed to account for spatial effects. Spatial regression models generated superior estimates over a traditional regression model. In the spatial regression models, BFV disease incidence shows an inverse relationship with minimum temperature, low tide and distance to coast, and positive relationship with rainfall in coastal areas whereas in whole Queensland the disease shows an inverse relationship with minimum temperature and high tide and positive relationship with rainfall. This study determines the most significant spatial risk factors for BFV disease across Queensland. Empirical models were developed to forecast the future risk of BFV disease outbreaks in coastal Queensland using existing climatic, socio-economic and tidal conditions under climate change scenarios. Logistic regression models were developed using BFV disease outbreak data for the existing period (2000-2008). The most parsimonious model had high sensitivity, specificity and accuracy and this model was used to estimate and forecast BFV disease outbreaks for years 2025, 2050 and 2100 under climate change scenarios for Australia. Important contributions arising from this research are that: (i) it is innovative to identify high-risk coastal areas by creating buffers based on grid-centroid and the use of fine-grained spatial units, i.e., mesh blocks; (ii) a spatial regression method was used to account for spatial dependence and heterogeneity of data in the study area; (iii) it determined a range of potential spatial risk factors for BFV disease; and (iv) it predicted the future risk of BFV disease outbreaks under climate change scenarios in Queensland, Australia. In conclusion, the thesis demonstrates that the distribution of BFV disease exhibits a distinct spatial and temporal variation. Such variation is influenced by a range of spatial risk factors including climatic, demographic, socio-economic, ecological and tidal variables. The thesis demonstrates that spatial regression method can be applied to better understand the transmission dynamics of BFV disease and its risk factors. The research findings show that disease notification data can be integrated with multi-factorial risk factor data to develop build-up models and forecast future potential disease risks under climate change scenarios. This thesis may have implications in BFV disease control and prevention programs in Queensland.

Characterisation of Landscape with Forest Fragmentation Dynamics

Land cover (LC) and land use (LU) dynamics induced by human and natural processes play a major role in global as well as regional patterns of landscapes influencing biodiversity, hydrology, ecology and climate. Changes in LC features resulting in forest fragmentations have posed direct threats to biodiversity, endangering the sustainability of ecological goods and services. Habitat fragmentation is of added concern as the residual spatial patterns mitigate or exacerbate edge effects. LU dynamics are obtained by classifying temporal remotely sensed satellite imagery of different spatial and spectral resolutions. This paper reviews five different image classification algorithms using spatio-temporal data of a temperate watershed in Himachal Pradesh, India. Gaussian Maximum Likelihood classifier was found to be apt for analysing spatial pattern at regional scale based on accuracy assessment through error matrix and ROC (receiver operating characteristic) curves. The LU information thus derived was then used to assess spatial changes from temporal data using principal component analysis and correspondence analysis based image differencing. The forest area dynamics was further studied by analysing the different types of fragmentation through forest fragmentation models. The computed forest fragmentation and landscape metrics show a decline of interior intact forests with a substantial increase in patch forest during 1972-2007.

Insights to urban dynamics through landscape spatial pattern analysis

Urbanisation is a dynamic complex phenomenon involving large scale changes in the land uses at local levels. Analyses of changes in land uses in urban environments provide a historical perspective of land use and give an opportunity to assess the spatial patterns, correlation, trends, rate and impacts of the change, which would help in better regional planning and good governance of the region. Main objective of this research is to quantify the urban dynamics using temporal remote sensing data with the help of well-established landscape metrics. Bangalore being one of the rapidly urbanising landscapes in India has been chosen for this investigation. Complex process of urban sprawl was modelled using spatio temporal analysis. Land use analyses show 584% growth in built-up area during the last four decades with the decline of vegetation by 66% and water bodies by 74%. Analyses of the temporal data reveals an increase in urban built up area of 342.83% (during 1973-1992), 129.56% (during 1992-1999), 106.7% (1999-2002), 114.51% (2002-2006) and 126.19% from 2006 to 2010. The Study area was divided into four zones and each zone is further divided into 17 concentric circles of 1 km incrementing radius to understand the patterns and extent of the urbanisation at local levels. The urban density gradient illustrates radial pattern of urbanisation for the period 1973-2010. Bangalore grew radially from 1973 to 2010 indicating that the urbanisation is intensifying from the central core and has reached the periphery of the Greater Bangalore. Shannon's entropy, alpha and beta population densities were computed to understand the level of urbanisation at local levels. Shannon's entropy values of recent time confirms dispersed haphazard urban growth in the city, particularly in the outskirts of the city. This also illustrates the extent of influence of drivers of urbanisation in various directions. Landscape metrics provided in depth knowledge about the sprawl. Principal component analysis helped in prioritizing the metrics for detailed analyses. The results clearly indicates that whole landscape is aggregating to a large patch in 2010 as compared to earlier years which was dominated by several small patches. The large scale conversion of small patches to large single patch can be seen from 2006 to 2010. In the year 2010 patches are maximally aggregated indicating that the city is becoming more compact and more urbanised in recent years. Bangalore was the most sought after destination for its climatic condition and the availability of various facilities (land availability, economy, political factors) compared to other cities. The growth into a single urban patch can be attributed to rapid urbanisation coupled with the industrialisation. Monitoring of growth through landscape metrics helps to maintain and manage the natural resources. (C) 2012 Elsevier B.V. All rights reserved.

Seasonal plankton dynamics along a cross-shelf gradient off northern Spain

The development of population models able to reproduce the dynamics of zooplankton is a central issue when trying to understand how a changing environment would affect zooplankton in the future. Using 10 years of monthly data on phytoplankton and zooplankton abundance in the Bay of Biscay from the IEO's RADIALES time-series programme, we built non-parametric Generalized Additive Models (GAMs) able to reproduce the dynamics of plankton on the basis of environmental factors (nutrients, temperature, upwelling and photoperiod). We found that the interaction between these two plankton components is approximately linear, whereas the effects of environmental factors are non-linear. With the inclusion of the environmental variability, the main seasonal and inter-annual dynamic patterns observed within the studied plankton assemblage indicate the prevalence of bottom-up regulatory control. The statistically deduced models were used to simulate the dynamics of the phytoplankton and zooplankton. A good agreement between observations and simulations was obtained, especially for zooplankton. We are presently developing spatio-temporal GAM models for the North Sea based on the Continuous Plankton Recorder database.