Éditeur(s) : Université de Guyane
Extrait de : "Circulation des individus, des savoirs et des pratiques culturelles dans le plateau des Guyanes" : journée d'étude, le 16 juin 2016. Université de Guyane
Description : Présentation générale des journées d'études consacrées à la circulation des individus, des savoirs et des pratiques culturelles dans le plateau des Guyanes.
Siècle(s) traité(s) : 21
Droits : CC-BY-NC-ND - Attribution - Pas d'utilisation commerciale - Pas de modification
Permalien : http://www.manioc.org/fichiers/V16198
V16198

Éditeur(s) : Université de Guyane CCIG Fondation de l
Extrait de : Conférences de la Fondation de l'Université de Guyane
Description : Les données météorologiques peuvent être un élément décisif dans l'élaboration de la transition énergétique.
Siècle(s) traité(s) : 21
Droits : CC-BY-NC-ND - Attribution - Pas d'utilisation commerciale - Pas de modification
Permalien : http://www.manioc.org/fichiers/V21016
V21016

Éditeur(s) : HAL CCSD
Résumé : Dans un contexte de préférences non classiques (pouvant présenter des intransitivités et incomplétu­des, voire des circuits), les problèmes combinatoires de recherche d'une solution préférée sont semi-structurés. Leur résolution s'effectue généralement grâce à des interactions entre le Système Interactif d'Aide à la Décision (SIAD) et les décideurs selon un processus de décision. En proposant des algorithmes de résolution de problèmes connexes pertinents entièrement automatisables, le SIAD aide à obtenir des éléments de réponses aux questions que se pose un intervenant dans un processus de décision. Nous introduisons un tout nouveau type de SIAD, proposant des problèmes automatisables pertinents basés sur la déduction et le choix : les problèmes de consistance qualitative. Ainsi, nous présentons un algorithme glouton de consistance qualitative dans le cadre du problème d'arbre couvrant maximal basé sur une version ordinale de l'algorithme de Kruskal. Utilisés dans un processus itératif interactif, ce type de problèmes ne permet pas toujours d'aboutir à une solution maximale pour l'instance initiale. Le processus décisionnel est dit non pleinement rationnel. Pour y remédier, nous identifions algorithmiquement les arêtes critiques (présentes dans toute solution du sous-ensemble maximal courant). Enfin, nous fournissons des conditions nécessaires sur les préférences, en nous aidant des travaux en théorie du choix rationnel, pour que le processus conserve cette rationalité procédurale.
Troisièmes Journées Francophones de Programmationpar Contraintes (JFPC07)

Droits : info:eu-repo/semantics/OpenAccess
inria-00151158
https://hal.inria.fr/inria-00151158
https://hal.inria.fr/inria-00151158/document
https://hal.inria.fr/inria-00151158/file/31.pdf

Éditeur(s) : HAL CCSD
Résumé : 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.
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.
https://tel.archives-ouvertes.fr/tel-01527553

NNT : 2016YANE0006
tel-01527553
https://tel.archives-ouvertes.fr/tel-01527553
https://tel.archives-ouvertes.fr/tel-01527553/document
https://tel.archives-ouvertes.fr/tel-01527553/file/these-youven-goulamoussene2.pdf

Éditeur(s) : HAL CCSD MDPI
Résumé : International audience
Canopy height is a key variable in tropical forest functioning and for regional carbon inventories. We investigate the spatial structure of the canopy height of a tropical forest, its relationship with environmental physical covariates, and the implication for tropical forest height variation mapping. Making use of high-resolution maps of LiDAR-derived Digital Canopy Model (DCM) and environmental covariates from a Digital Elevation Model (DEM) acquired over 30,000 ha of tropical forest in French Guiana, we first show that forest canopy height is spatially correlated up to 2500 m. Forest canopy height is significantly associated with environmental variables, but the degree of correlation varies strongly with pixel resolution. On the whole, bottomland forests generally have lower canopy heights than hillslope or hilltop forests. However, this global picture is very noisy at local scale likely because of the endogenous gap-phase forest dynamic processes. Forest canopy height has been predictively mapped across a pixel resolution going from 6 m to 384 m mimicking a low resolution case of 3 points·km −2. Results of canopy height mapping indicated that the error for spatial model with environment effects decrease from 8.7 m to 0.91 m, depending of the pixel resolution. Results suggest that, outside the calibration plots, the contribution of environment in shaping the global canopy height distribution is quite limited. This prevents accurate canopy height mapping based only on environmental information, and suggests that precise canopy height maps, for local management purposes, can only be obtained with direct LiDAR monitoring.
ISSN: 2072-4292

hal-01590726
https://hal-univ-guyane.archives-ouvertes.fr/hal-01590726
https://hal-univ-guyane.archives-ouvertes.fr/hal-01590726/document
https://hal-univ-guyane.archives-ouvertes.fr/hal-01590726/file/remotesensing-08-00747.pdf
DOI : 10.3390/rs8090747

Éditeur(s) : HAL CCSD
Résumé : International audience
ABSTRACT :A satellite retrieval of surface solar irradiance (SSI) based on GOES satellite data is presented and validated for the French Guiana with three years of in situ measurements from six ground stations. We propose a particle filter approach combining GOES satellite observations and in situ data. We propose an original observation function based on a joint probability distribution and taking advantages of the characteristics of both the involved type of data. The statistical results are compared with those of existing estimation methods and they are found to be in accordance with them. The daily bias ranges from -12 W/m² (-6% of the mean of measurements) to 12 W/m² (6%), depending on the stations. The daily root mean square difference ranges between 23 W/m² (10%) and 27 W/m² (15%). The correlation coefficient is close to 0.92. There is no seasonal climatic effect on the method, the bias and RMSD remain similar for both the rainy and the dry season, but better correlation is observed in the rainy season than in the dry season. Uncertainties are mainly due to the presence of specific tropical atmospheric conditions during the dry season. The method has been tested through various tests: cross-validation scheme has highlighted the potential generalization of the model in a temporal dimension; the ability of the method to effectively duplicate anomalies in surface solar irradiance time series has also been tested. The robustness of the results shows the interest of the method compared to other existing estimation methods. Because of its simplicity of implementation this method opens new prospects in estimating surface solar irradiance. It is concluded that using a particle filter and original observation function method allow a high-quality surface solar irradiance estimation in French Guiana.RESUMEUne méthode d'estimation de l'irradiance solaire de surface (SSI) à partir de données satellites GOES est présentée et validée par comparaison avec trois années de mesures in situ provenant de six stations météorologiques de Guyane Française. Dans cet article, nous proposons une approche par filtre particulaire combinant observations du satellite GOES et données in situ. Nous proposons une fonction d'observation originale basée sur une distribution de probabilité conjointe des deux types de données. Les résultats statistiques sont conformes à ceux des méthodes existantes. Le biais journalier varie de -16 W / m² (-7% de la moyenne des mesures) à 12 W / m² (6%). L'erreur quadratique moyenne (RMSD) est comprise entre 23 W / m² (10%) et 27 W / m² (15%). Le coefficient de corrélation est de 0,92. La méthode est peu sensible aux variations climatiques saisonnières, le biais et RMSD restent similaires en saison des pluies comme en saison sèche, mais une meilleure corrélation est observée pendant la saison des pluies. Les incertitudes sont principalement dues à la présence de conditions atmosphériques tropicales spécifiques en saison sèche. La méthode a été soumise à différents tests : un processus de validation croisée a mis en évidence la possible généralisation du modèle dans une dimension temporelle, la capacité du modèle à reproduire efficacement des anomalies dans les séries temporelles d'irradiance solaire de surface a aussi été testée. La robustesse des résultats obtenus montrent l'intérêt du modèle par rapport aux autres méthodes d'estimation existantes. A cause de sa simplicité de mise en oeuvre cette méthode ouvre de nouvelles perspectives en matière d'estimation de l'irradiance solaire au sol. Nous concluons que l'utilisation d'un filtre particulaire combinée à une fonction d'observation originale permet une estimation de haute qualité de l'irradiance solaire au sol en Guyane Française.
Canadian Journal of Remote Sensing

meteo-01304574
https://hal-meteofrance.archives-ouvertes.fr/meteo-01304574
DOI : 10.1080/07038992.2015.1040150

Éditeur(s) : HAL CCSD European Geosciences Union
Résumé : International audience
Natural disturbances are the dominant form of forest regeneration and dynamics in unmanaged tropical forests. Monitoring the size distribution of treefall gaps is important to better understand and predict the carbon budget in response to land use and other global changes. In this study, we model the size frequency distribution of natural canopy gaps with a discrete power law distribution. We use a Bayesian framework to introduce and test, using Monte Carlo Markov chain and Kuo–Mallick algorithms, the effect of local physical environment on gap size distribution. We apply our methodological framework to an original light detecting and ranging dataset in which natural forest gaps were delineated over 30 000 ha of unmanaged forest. We highlight strong links between gap size distribution and environment, primarily hydrological conditions and topography, with large gaps being more frequent on floodplains and in wind-exposed areas. In the future, we plan to apply our methodological framework on a larger scale using satellite data. Additionally , although gap size distribution variation is clearly under environmental control, variation in gap size distribution in time should be tested against climate variability.
ISSN: 1726-4170

hal-01590729
https://hal-univ-guyane.archives-ouvertes.fr/hal-01590729
https://hal-univ-guyane.archives-ouvertes.fr/hal-01590729/document
https://hal-univ-guyane.archives-ouvertes.fr/hal-01590729/file/bg-14-353-2017.pdf
DOI : 10.5194/bg-14-353-2017

Éditeur(s) : HAL CCSD MDPI
Résumé : International audience
Satellite precipitation products are a means of estimating rainfall, particularly in areas that are sparsely equipped with rain gauges. The Guiana Shield is a region vulnerable to high water episodes. Flood risk is enhanced by the concentration of population living along the main rivers. A good understanding of the regional hydro-climatic regime, as well as an accurate estimation of precipitation is therefore of great importance. Unfortunately, there are very few rain gauges available in the region. The objective of the study is then to compare satellite rainfall estimation products in order to complement the information available in situ and to perform a regional analysis of four operational precipitation estimates, by partitioning the whole area under study into a homogeneous hydro-climatic region. In this study, four satellite products have been tested, TRMM TMPA (Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis) V7 (Version 7) and RT (real time), CMORPH (Climate Prediction Center (CPC) MORPHing technique) and PERSIANN (Precipitation Estimation from Remotely-Sensed Information using Artificial Neural Network), for daily rain gauge data. Product performance is evaluated at daily and monthly scales based on various intensities and hydro-climatic regimes from 1 January 2001 to 30 December 2012 and using quantitative statistical criteria (coefficient correlation, bias, relative bias and root mean square error) and quantitative error metrics (probability of detection for rainy days and for no-rain days and the false alarm ratio). Over the entire study period, all products underestimate precipitation. The results obtained in terms of the hydro-climate show that for areas with intense convective precipitation, TMPA V7 shows a better performance than other products, especially in the estimation of extreme precipitation events. In regions along the Amazon, the use of PERSIANN is better. Finally, in the driest areas, TMPA V7 and PERSIANN show the same performance.
ISSN: 2072-4292

Droits : http://hal.archives-ouvertes.fr/licences/copyright/
hal-01257912
https://hal.archives-ouvertes.fr/hal-01257912
https://hal.archives-ouvertes.fr/hal-01257912/document
https://hal.archives-ouvertes.fr/hal-01257912/file/remotesensing-07-15831.pdf
DOI : 10.3390/rs71215831

Éditeur(s) : HAL CCSD
Résumé : International audience
The Heliosat-II method was developed to process Meteosat satellite images in order to assess the solar irradiation at surface. It is modified for its use with GOES satellite images in order to estimate the solar irradiation over French Guiana.Modifications include a change in the calibration formula, in the calculation of the cloud albedo, and in the values of the Linke turbidity factor. These modifications allow the improvement of the performances of the Heliosat-II model in Intertropical zones in French Guiana. The outcomes were compared to coincident measurements of hourly irradiation performed by ground stations.The results show that the use of the maximum apparent albedo as the cloud albedo (ρcmax), along with a fixed value of the Linke turbidity factor produces the best results; the bias was less than 23.61 Wh/m2 (5% of the mean value of the measurements) overall, and the RMSE was less than 109.39 W/m2 (24%) overall when using hourly values. In the case of daily means, the RMSE drops to less than 10.08 W/m2 (10%) overall, whereas the overall bias remains unchanged, as expected. The model performs better in clear skies than in cloudy skies. The results suggest that the Linke turbidity factor used in the Heliosat-II method does not reproduce well the attenuation of the solar radiation in French Guiana. The results were compared to those obtained from Heliosat II method and Meteosat images (HelioClim-3 database) and we found a better accuracy for GOES satellite data, which exhibits smaller viewing angle. The use of the Heliosat II method with GOES images allows assessment of the SSI with a good accuracy and high temporal and spatial resolutions.
Canadian Journal of Remote Sensing

meteo-01304576
https://hal-meteofrance.archives-ouvertes.fr/meteo-01304576
DOI : 10.1080/07038992.2015.1040876

Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
The purpose of this article is to improve modeling of solar irradiance through the analysis of measurement data on the ground in the intertropical zone. For this, we identify, using information criteria, the probabilistic distributions introduced in two models of synthetic solar irradiance generation. We then validate the results by using the KL divergence and KSI parameter as comparison criteria between distributions arising from real and synthesized data. Our study confirms, for example, that the Gaussian classical distribution is not suitable for modeling solar irradiance, and we propose other more suitable statistical laws instead. The value of the identification procedure of the distribution laws presented in this article is that it ensures the production of solar irradiance data comparable in their statistical content to the measured data. Another advantage is that this procedure contributes to highlighting the time invariance of distribution laws representing the random terms. We conclude that this new information-criteria-based method permits the identification of the probability laws that best describe the statistical distributions introduced in models of synthetic solar irradiance generation.
ISSN: 0038-092X

meteo-01304572
https://hal-meteofrance.archives-ouvertes.fr/meteo-01304572
https://hal-meteofrance.archives-ouvertes.fr/meteo-01304572/document
https://hal-meteofrance.archives-ouvertes.fr/meteo-01304572/file/Manuscript_Hal.pdf
DOI : 10.1016/j.solener.2016.02.038

Éditeur(s) : HAL CCSD MDPI
Résumé : International audience
Satellite precipitation products are a means of estimating rainfall, particularly in areas that are sparsely equipped with rain gauges. The Guiana Shield is a region vulnerable to high water episodes. Flood risk is enhanced by the concentration of population living along the main rivers. A good understanding of the regional hydro-climatic regime, as well as an accurate estimation of precipitation is therefore of great importance. Unfortunately, there are very few rain gauges available in the region. The objective of the study is then to compare satellite rainfall estimation products in order to complement the information available in situ and to perform a regional analysis of four operational precipitation estimates, by partitioning the whole area under study into a homogeneous hydro-climatic region. In this study, four satellite products have been tested, TRMM TMPA (Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis) V7 (Version 7) and RT (real time), CMORPH (Climate Prediction Center (CPC) MORPHing technique) and PERSIANN (Precipitation Estimation from Remotely-Sensed Information using Artificial Neural Network), for daily rain gauge data. Product performance is evaluated at daily and monthly scales based on various intensities and hydro-climatic regimes from 1 January 2001 to 30 December 2012 and using quantitative statistical criteria (coefficient correlation, bias, relative bias and root mean square error) and quantitative error metrics (probability of detection for rainy days and for no-rain days and the false alarm ratio). Over the entire study period, all products underestimate precipitation. The results obtained in terms of the hydro-climate show that for areas with intense convective precipitation, TMPA V7 shows a better performance than other products, especially in the estimation of extreme precipitation events. In regions along the Amazon, the use of PERSIANN is better. Finally, in the driest areas, TMPA V7 and PERSIANN show the same performance.
ISSN: 2072-4292

meteo-01304579
https://hal-meteofrance.archives-ouvertes.fr/meteo-01304579
https://hal-meteofrance.archives-ouvertes.fr/meteo-01304579/document
https://hal-meteofrance.archives-ouvertes.fr/meteo-01304579/file/remotesensing-07-15831.pdf
DOI : 10.3390/rs71215831

Éditeur(s) : HAL CCSD Taylor & Francis: STM, Behavioural Science and Public Health Titles
Résumé : International audience
Measurements of daily means of surface solar irradiance made at four ground stations in French Guiana are compared to estimates from the HelioClim-3 database produced by the Heliosat-2 method applied to Meteosat satellite images. The bias ranges from 12 W m−2 (6% of the mean of measurements) to 23 W m−2 (12%), depending on the stations. The root mean square difference ranges between 23 W m−2 (11%) and 35 W m−2 (18%). The correlation coefficient (r) is close to 0.9. Better results are observed during the rainy season than during the dry season. Uncertainties are mainly due to the presence of clouds, large viewing angles of the Meteosat satellite, and limitations of the atmospheric transmittance model under the tropical atmospheric conditions. It is concluded that the Heliosat-2 method provides new knowledge about solar radiation in French Guiana.
International Journal of Remote Sensing

hal-00779675
https://hal-mines-paristech.archives-ouvertes.fr/hal-00779675
https://hal-mines-paristech.archives-ouvertes.fr/hal-00779675/document
DOI : 10.1080/01431161.2012.756598