Utilisation conjointe de données d'altimétrie satellitaire et de modélisation pour le calcul des débits distribués dans le bassin amazonien

This thesis proposes the development of a methodology that aims to obtain distributed discharges in the Amazon basin based on satellite altimetry data and modeled discharges. Given recent works and advances, this work focused particularly on the information that can be inferred from the resulting relationships. We used stage-discharge relationships based on Manning's equation that were optimized through a global optimization algorithm adequately configured. Altimetry data was taken from ENVISAT and Jason-2 missions and discharges were estimated for an overlapping period by the MGB-IPH model. A-priori intervals were defined into the SCEM-UA scheme for each optimization's parameter, and the algorithm allowed us to deal with input errors and output uncertainties. We produced a thousand gross database of rating curves and associated confidence intervals. Hydrological coherence was proved by validation with both modeled and in situ discharges. Successfully using an ENVISAT-based RC with Jason-2 data to estimate discharge at a cross-over, we proved that rating curves are not mission-dependent and can be used with any incoming water height data. Geomorphological characteristics of studied section given by our rating curves were validated through comparison with in situ data, inverse modeling of a braided river reach and synthetic rivers test cases.Cette thèse propose le développement d'une méthodologie permettant l'obtention des débits distribués dans le bassin amazonien à partir des hauteurs d'eau altimétriques. Au vu des derniers travaux et des avancées récentes dans ce domaine, ce travail a particulièrement porté sur les informations connexes pouvant être extraites des résultats. Nous avons utilisé des relations hauteur-débit basées sur l'équation de Manning et optimisées au travers d'un algorithme d'optimisation globale correctement paramétré. Les hauteurs d'eau ont été obtenues à partir des hauteurs altimétriques fournies par les missions ENVISAT et Jason-2, et les débits ont été estimés sur la même période par le modèle MGB-IPH sur l'ensemble du bassin. L'utilisation de l'algorithme d'optimisation SCEM-UA a permis de définir des intervalles a priori pour les paramètres ajustables ainsi que de gérer les notions d'erreur dans les données d'entrée, et d'incertitude dans les paramètres de sortie. Une des productions de ce travail est la construction d'une base de données d'un millier de courbes de tarage avec les intervalles de confiance associés. La validité spatiale de ces courbes de tarage a pu être vérifiée par comparaison avec les débits du modèle ainsi que les débits in situ disponibles. Leur stabilité dans le temps, quant à elle, a été confirmée par notre capacité à estimer des débits cohérents avec des informations de hauteurs d'eau provenant d'autres missions et d'autres périodes que celle à partir de laquelle les relations hauteur-débit avaient été estimées. Ce travail a également mis en évidence, par validation in situ, modélisation inverse et analyse de cas tests sur des rivières synthétiques, la capacité de la méthodologie proposée à identifier les caractéristiques géomorphologiques des sections étudiées

User-assisted intrinsic images

For many computational photography applications, the lighting and materials in the scene are critical pieces of information. We seek to obtain intrinsic images, which decompose a photo into the product of an illumination component that represents lighting effects and a reflectance component that is the color of the observed material. This is an under-constrained problem and automatic methods are challenged by complex natural images. We describe a new approach that enables users to guide an optimization with simple indications such as regions of constant reflectance or illumination. Based on a simple assumption on local reflectance distributions, we derive a new propagation energy that enables a closed form solution using linear least-squares. We achieve fast performance by introducing a novel downsampling that preserves local color distributions. We demonstrate intrinsic image decomposition on a variety of images and show applications.National Science Foundation (U.S.) (NSF CAREER award 0447561)Institut national de recherche en informatique et en automatique (France) (Associate Research Team “Flexible Rendering”)Microsoft Research (New Faculty Fellowship)Alfred P. Sloan Foundation (Research Fellowship)Quanta Computer, Inc. (MIT-Quanta T Party

Desertscape Simulation

International audienceWe present an interactive aeolian simulation to author hot desert scenery. Wind is an important erosion agent in deserts which, despite its importance, has been neglected in computer graphics. Our framework overcomes this and allows generating a variety of sand dunes, including barchans, longitudinal and anchored dunes, and simulates abrasion which erodes bedrock and sculpts complex landforms. Given an input time varying high altitude wind field, we compute the wind field at the surface of the terrain according to the relief, and simulate the transport of sand blown by the wind. The user can interactively model complex desert landscapes, and control their evolution throughout time either by using a varietyof interactive brushes or by prescribing events along a user-defined time-line

Optimization of a non-activating medium for short-term chilled storage of barramundi (Lates calcarifer) testicular spermatozoa

Reliable short-term chilled sperm storage is a critical prerequisite to using advanced reproductive techniques for captive breeding of barramundi (Asian sea bass; Lates calcarifer). Marine Ringer's solution (MRS) is a common non-activating medium (NAM) and has previously been used to store sperm from wild-caught barramundi. However, MRS-stored spermatozoa from captive-bred barramundi were observed to lyse within 30 min incubation. Therefore, this study aimed to optimize the composition of NAM for short-term chilled storage by characterizing and mimicking the biochemical profile of seminal and blood plasma of captive-bred barramundi. To further understand the effect of each component, osmolality was first examined to determine its effect on sperm viability. Thereafter, the effects of NaHCO3, pH, and Na+ and K+ concentrations on sperm motility were investigated. Optimization of the NAM formula was achieved through iterative adaptions. The increase in NAM osmolality from 260 to 400 mOsm/kg led to a significant improvement in sperm viability. Moreover, using HEPES instead of NaHCO3 as buffering agent significantly enhanced sperm motility and velocity. As a result, sperm samples diluted with optimized NAM (185 mM NaCl, 5.1 mM KCl, 1.6 mM CaCl2·2H2O, 1.1 mM MgSO4·7H2O, 10.0 mM HEPES, 5.6 mM D+ glucose, 400 mOsm/kg, pH 7.4) and stored at 4 °C showed no significant loss in total motility for up to 48 h and retained progressive motility for up to 72 h. The optimized NAM developed in this study significantly extended the functional lifespan of spermatozoa during chilled storage, permitting the ongoing development of advanced reproductive technologies for barramundi

Coherent Intrinsic Images from Photo Collections

International audienceAn intrinsic image is a decomposition of a photo into an illumination layer and a reflectance layer, which enables powerful editing such as the alteration of an object's material independently of its illumination. However, decomposing a single photo is highly under-constrained and existing methods require user assistance or handle only simple scenes. In this paper, we compute intrinsic decompositions using several images of the same scene under different viewpoints and lighting conditions. We use multi-view stereo to automatically reconstruct 3D points and normals from which we derive relationships between reflectance values at different locations, across multiple views and consequently different lighting conditions. We use robust estimation to reliably identify reflectance ratios between pairs of points. From these, we infer constraints for our optimization and enforce a coherent solution across multiple views and illuminations. Our results demonstrate that this constrained optimization yields high-quality and coherent intrinsic decompositions of complex scenes. We illustrate how these decompositions can be used for image-based illumination transfer and transitions between views with consistent lighting

UTILIZAÇÃO DE DADOS DE SENSORES REMOTOS COMO INSTRUMENTO DE GESTÃO DE RECURSOS HÍDRICOS NA BACIA DO RIO MADEIRA

O presente estudo teve como objetivo principal, a validação de informações geomorfológicas na bacia do rio Madeira utilizando dados de sensores remotos. Com base nas informações geradas pelo estudo espera-se contribuir para o monitoramento hidrológico da região da bacia do rio Madeira, uma vez que em toda a extensão da bacia Amazônica existem problemas relacionados ao monitoramento hidrológico, o que acaba gerando impactos negativos na gestão de recursos hídricos da região. A validação das informações geomorfológicas, mais especificamente a variável profundidade, foi feita com base na elaboração de uma curva chave produzida com dados de vazão simulada pelo Modelo de Grandes Bacias – MGB e pelas cotas altimétricas oriundas de dados do satélite Sentinel 3A durante o período de 2016 a 2019. Esses dados relacionados as informações geomorfológicas de profundidade foram validados, usando como referência as medidas de profundidade provenientes da batimetria da área de estudo analisada. Esta batimetria foi realizada pelo Serviço de Sinalização Náutica – SSN-9 que é responsável pela segurança da navegação dentro da bacia Amazônica. A validação das informações geomorfológicas relacionadas a variável profundidade pode indicar um caminho para novas alternativas no monitoramento hidrológico da bacia Amazônica, onde é possível, utilizar dados de modelagem hidrológica e cotas altimétricas provenientes de satélites para fazer um monitoramento seguro e com alta resolução temporal e espacial

UTILIZAÇÃO DE DADOS DE SENSORES REMOTOS COMO INSTRUMENTO DE GESTÃO DE RECURSOS HÍDRICOS NA BACIA DO RIO MADEIRA

O presente estudo teve como objetivo principal, a validação de informações geomorfológicas na bacia do rio Madeira utilizando dados de sensores remotos. Com base nas informações geradas pelo estudo espera-se contribuir para o monitoramento hidrológico da região da bacia do rio Madeira, uma vez que em toda a extensão da bacia Amazônica existem problemas relacionados ao monitoramento hidrológico, o que acaba gerando impactos negativos na gestão de recursos hídricos da região. A validação das informações geomorfológicas, mais especificamente a variável profundidade, foi feita com base na elaboração de uma curva chave produzida com dados de vazão simulada pelo Modelo de Grandes Bacias – MGB e pelas cotas altimétricas oriundas de dados do satélite Sentinel 3A durante o período de 2016 a 2019. Esses dados relacionados as informações geomorfológicas de profundidade foram validados, usando como referência as medidas de profundidade provenientes da batimetria da área de estudo analisada. Esta batimetria foi realizada pelo Serviço de Sinalização Náutica – SSN-9 que é responsável pela segurança da navegação dentro da bacia Amazônica. A validação das informações geomorfológicas relacionadas a variável profundidade pode indicar um caminho para novas alternativas no monitoramento hidrológico da bacia Amazônica, onde é possível, utilizar dados de modelagem hidrológica e cotas altimétricas provenientes de satélites para fazer um monitoramento seguro e com alta resolução temporal e espacial

Associação do impacto da variabilidade da temperatura nos oceanos atlântico e pacífico com os níveis dos rios da Amazônia a partir de dados altimétricos

The influence of SST (Sea Surface Temperature) of adjacent oceans on the variability of water levels in the Amazon basin was investigated by using radar altimetry from the ENVISAT and Jason-2 missions. Data from the in situ network was used to compare the correlations of water level and SST anomalies in the sub-basins of the Amazonas-Peru, Solimões, Negro and Madeira Rivers. The analysis was made on the monthly and annual scales between 2003 and 2015. The correlations with anomalies of levels from altimetry presented higher accuracy indices than those from the conventional network. In general, ATN and PAC are better correlated with the entire basin. During the flood months, most of the sub-basins presented negative associations with ATN. In the months of ebb, the response to the indexes varies according to the region. The satellite altimetry data permitted to reach regions non-monitored by the conventional network. We also analyzed the impacts of hydrological extremes in all these sub-regions in the last 13 years. In Western Amazon, the drought of 2010 stands out, associated with the warming of the Tropical Atlantic and the El Niño. In the Negro River, the water level anomalies were the lowest in the basin during the 2005 drought. In the Purus River, the effects of the 2010 drought that affected the entire Amazon, were higher in 2011 due to its strong relationship with the Atlântic and Pacific oceans. In general, hydrological extremes are stronger or highlighted when SST increases simultaneously in both oceans. © 2018, Brazilian Journal of Water Resources. All rights reserved

Human Movement and Ergonomics: an Industry-Oriented Dataset for Collaborative Robotics

International audienceImproving work conditions in industry is a major challenge that can be addressed with new emerging technologies such as collaborative robots. Machine learning techniques can improve the performance of those robots, by endowing them with a degree of awareness of the human state and ergonomics condition. The availability of appropriate datasets to learn models and test prediction and control algorithms however remains an issue. This paper presents a dataset of human motions in industry-like activities, fully labeled according to the ergonomics assessment worksheet EAWS, widely used in industries such as car manufacturing. Thirteen participants performed several series of activities, such as screwing and manipulating loads in different conditions, resulting in more than 5 hours of data. The dataset contains the participants' whole-body kinematics recorded both with wearable inertial sensors and marker-based optical motion capture, finger pressure force, video recordings, and annotations by 3 independent annotators of the performed action and the adopted posture following the EAWS postural grid. Sensor data are available in different formats to facilitate their reuse. The dataset is intended for use by researchers developing algorithms for classifying, predicting or evaluating human motion in industrial settings, as well as researchers developing collaborative robotics solutions that aim at improving the workers' ergonomics. The annotation of the whole dataset following an ergonomics standard makes it valuable for ergonomics-related applications, but we expect its use to be broader in the robotics, machine learning and human movement communities