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Concours de l’INJEP qui a autorisé l’utilisation du questionnaire national et a soutenu la démarche de labélisation de l’Enquête régionale sur les pratiques physiques et sportives; International audience; La Réunion est un territoire exposé depuis plusieurs décennies à une transition démographique, épidémiologique et nutritionnelle. D’après l’enquête santé européenne 2019 réalisée chez les personnes vivant à domicile (≥ 15 ans), 23-% de la population réunionnaise adulte présenterait un excès de sédentarité. Dans la perspective d’actions territorialisée basées sur la réduction des facteurs de risque, le comportement sédentaire apparaît comme un facteur modifiable de première importance. Notre objectif est de rechercher les déterminants individuels, sociaux et environnementaux de la sédentarité chez les Réunionnais.es de 15 ans et plus.La réponse à cet objectif s’appuie sur une approche méthodologique pluridisciplinaire combinant l’analyse statistique en santé et l’analyse spatiale. Les données utilisées sont celles de l’enquête régionale sur les pratiques physiques et sportives à La Réunion réalisée en septembre-décembre 2021 (ERPPS-2021), enrichies de bases environnementales (Filosofi, BD TOPO IGN, Base Permanente des Equipements, etc.).Cette enquête téléphonique transversale ponctuelle a fait l’objet d’un échantillonnage aléatoire à partir de la base de sondage Fidéli (Insee).Les analyses statistiques portent sur 2010 participants issus des 4 microrégions de l'île. L'exploitation des données déclaratives (comportements de santé, facteurs psychosociaux, conditions de vie et de travail, caractéristiques socio-économiques du lieu de résidence) et spatiales (facteurs environnementaux) est en cours.Il s’agit d’une approche originale, fondée sur des données probantes, à la frontière de l’épidémiologie sociale et de la géographie de la santé, qui laisse entrevoir des pistes en prévention primaire des maladies chroniques liées au mode de vie.

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International audience

Additional file 3. Map of land cover in Ifanadiana district, 2018, at a 10 m resolution following remote sensing analyses.

Additional file 5. Cumulative percentage of the population at each distance and time to seek treatment from the closest PHC and CHS.

Additional file 7. Comparison of travel time with other commonly used methods in geographic access modeling.

Additional file 9. Histogram of relative difference in travel time estimations for PHC and CHS routes between a statistical model with land cover and without land cover.

Additional file 2. Explanatory analyses of all variables, with 3 quantitative variables (slope, distance and rainfall) and 2 qualitative variables (land cover, individual type).

Additional file 4. Histogram of travel distance and time to PHC and CHS.

International audience; In the future, climate change will induce even more severe hurricanes. Not only should these be better understood, but there is also a necessity to improve the assessment of their impacts. Flooding is one of the most common powerful impacts of these storms. Analyzing the impacts of floods is essential in order to delineate damaged areas and study the economic cost of hurricane-related floods. This paper presents an automated processing chain for Sentinel-1 synthetic aperture radar (SAR) data. This processing chain is based on the S1-Tiling algorithm and the normalized difference ratio (NDR). It is able to download and clip S1 images on Sentinel-2 tiles footprints, perform multi-temporal filtering, and threshold NDR images to produce a mask of flooded areas. Applied to two different study zones, subject to hurricanes and cyclones, this chain is reliable and simple to implement. With the rapid mapping product of EMS Copernicus (Emergency Management Service) as reference, the method confers up to 95% accuracy and a Kappa value of 0.75.

Additional file 6. Non-linear smooth and 95% confidence intervals of the effect of slope change (%, absolute values) on travel speed in the multivariate GAM model presented in Table 3.

Additional file 8. Comparison of travel time for the population of Ifanadiana between a scenario with 19 PHCs and a scenario with 21 PHCs, after the construction of two new PHCs in 2016 and 2018.

International audience; The southwestern Indian Ocean comprises numerous islands of less than 3000 sq km (Comoros, Seychelles, Mascarene Islands). These small island territories have very fragmented and diversified landscapes. Satellite imagery and landcover products at low and medium spatial resolution (usually from 4 kilometers to 250 meters) are not or poorly suited to the study of these areas. Therefore, we have developed a land use product, called Homisland-IO, based on the analysis of high spatial resolution images acquired by the SPOT 5 satellite between December 2012 and July 2014 and produced at the SEAS-OI Station. We used an object-based image analysis method to identify the 11 major classes of land cover / land use of these tropical islands. This methodology together with a good knowledge of the field has enabled us to achieve an overall accuracy of 86%, making it an operational product. These products have already been used in various projects, including epidemiology and health geography (Lept-OI, TROI, ISSE-Mayotte, etc) to describe the distribution and habitat of some vectors of diseases (mainly mosquitoes and rodents), a necessary condition for analyzing the risk of transmission of these diseases to humans.

International audience

The southwestern Indian Ocean comprises numerous islands of less than 3000 sq km (Comoros, Seychelles, Mascarene Islands). These small island territories have very fragmented and diversified landscapes. Satellite imagery and landcover products at low and medium spatial resolution (usually from 4 kilometers to 250 meters) are not or poorly suited to the study of these areas. Therefore, we have developed a land use product, called Homisland-IO, based on the analysis of high spatial resolution images acquired by the SPOT 5 satellite between December 2012 and July 2014 and produced at the SEAS-OI Station. We used an object-based image analysis method to identify the 11 major classes of land cover / land use of these tropical islands. This methodology together with a good knowledge of the field has enabled us to achieve an overall accuracy of 86%, making it an operational product. These products have already been used in various projects, including epidemiology and health geography (Lept-OI, TROI, ISSE-Mayotte, etc) to describe the distribution and habitat of some vectors of diseases (mainly mosquitoes and rodents), a necessary condition for analyzing the risk of transmission of these diseases to humans. Homisland-IO is freely accessible through a web portal and thus available for future uses.

International audience; By providing a wide view of territories, satellite images and aerial photographs allow to capture the environmental factors that can affect the health of populations. Since the development of satellite remote sensing in the 1970s, its use in the health field has had moderate success. Although its potential was widely mentioned in the literature until the 2000s, its operational contribution was not obvious. It is only recently that health applications have been enriched and multiplied by the development of interdisciplinary approaches. This article aims to question the uses of remote sensing applied to health issues according to technical, historical, and thematic aspects in order to identify the bottlenecks. First, it offers a didactic view of theoretical principles, available data and possible uses. Through a bibliographic study, it offers a retrospective look at the evolution of its implementation in the field of health, which allows synthesizing current contributions: for operational mapping, for surveillance and analysis of the dynamics of infectious diseases or, to a lesser extent, to apprehend the vulnerabilities of populations such as difficulties in accessing healthcare. Finally, the article concludes on the limits, recommendations and perspectives for optimizing these uses, which are often constrained by technical and structural issues and for which methodologies still need to be developed.; En prenant de la hauteur et en offrant une vue élargie des territoires, les images satellite et les photographies aériennes permettent d'appréhender les facteurs environnementaux qui peuvent conditionner la santé des populations. Depuis l'essor de la télédétection satellite à partir des années 1970, son usage dans le domaine de la santé a connu des succès modérés. Si son potentiel a été largement évoqué dans la littérature jusqu'aux années 2000, son apport opérationnel ne s'est pas imposé. Ce n'est que récemment que les applications en santé se sont enrichies et multipliées par le développement d'approches interdisciplinaires. Cet article vise à questionner les usages de la télédétection appliquée aux questions de santé selon les aspects techniques, historiques, et thématiques afin d'identifier les verrous. Il propose tout d'abord une vue didactique des principes théoriques, des données disponibles et des usages possibles. A travers une étude bibliographique, il offre un regard rétrospectif sur l'évolution de sa mise en ½uvre dans le domaine la santé, qui permet de synthétiser les contributions actuelles : pour la cartographie opérationnelle, pour la surveillance et l'analyse des dynamiques des maladies infectieuses ou, dans une moindre de mesure, pour appréhender les vulnérabilités des populations comme les difficultés d'accès aux soins. Enfin, l'article conclut sur les limites, les recommandations et les perspectives pour optimiser ces usages dont les verrous sont souvent techniques et structurels mais pour lesquels des méthodologies doivent encore être développées.; Ao fornecer uma visão ampla dos territórios, as imagens de sensoriamento remoto orbital e fotografias aéreas permitem analisar os fatores ambientais que podem condicionar a saúde das populações. Desde o surgimento do sensoriamento remoto orbital na década de 1970, seu uso no campo da saúde teve um sucesso moderado. Embora seu potencial tenha sido amplamente mencionado na literatura até a década de 2000, sua contribuição operacional era óbvia. Apenas recentemente as aplicações em saúde foram enriquecidas e multiplicadas pelo desenvolvimento de abordagens interdisciplinares. Este artigo tem como objetivo questionar os usos do sensoriamento remoto aplicados às questões de saúde, de acordo com os aspectos técnicos, históricos e temáticos, a fim de identificar os seus gargalos. Primeiramente propõe uma visão didática dos princípios teóricos, dados disponíveis e possíveis usos. Através de um estudo bibliográfico, oferece uma retrospectiva da evolução de sua implementação no campo da saúde, permitindo sintetizar as contribuições atuais: para o mapeamento operacional, para a vigilância e a análise da dinâmica de doenças infecciosas ou, em menor grau, para compreender as vulnerabilidades das populações, tais como as dificuldades de acesso aos serviços de saúde. Por fim, o artigo conclui sobre os limites, as recomendações e as perspectivas para otimizar esses usos, que muitas vezes são limitados por questões técnicas e estruturais e para as quais as metodologias ainda precisam ser desenvolvidas.

International audience; The southwest of the Indian Ocean comprises numerous islands of less than 3000 sq km (Comoros, Seychelles, Mascarene Islands). These small island territories have very fragmented and diversified environments. Satellite imagery and products at low and medium spatial resolution (usually from 4 kilometers to 250 meters) are not or poorly suited to the study of these areas. This is particularly the case for ecological studies such as the study of vector-borne diseases where the evaluation of interactions at a fine scale is critical to understand their spatial dynamics. To overcome this need, we realized a homogeneous land cover mapping of these small islands, by analysing SPOT 5 satellite images acquired between July 2013 and July 2014 by SEAS-OI Station. We used an object-based image analysis method to identify the 12 major classes of land cover / land use of these tropical islands. To improve the results of this classification, we used some data from the free and participative OpenStreetMap (OSM) database as training data. These data were first checked and even completed to ensure their quality. This information helped us in particular to improve our results on agricultural areas (sugar cane, market gardening) and to define more precisely the main roads. This methodology together with a good knowledge of the field has enabled us to achieve an overall accuracy of 85%, making it an operational product. In return, we fed the OSM database by integrating the classes for which we had the best accuracy (mangrove, surface water and forest). Indeed, OSM is a particularly interesting platform for releasing and disseminating land use data.

International audience; The southwest of the Indian Ocean comprises numerous islands of less than 3000 sq km (Comoros, Seychelles, Mascarene Islands). These small island territories have very fragmented and diversified environments. Satellite imagery and products at low and medium spatial resolution (usually from 4 kilometers to 250 meters) are not or poorly suited to the study of these areas. This is particularly the case for ecological studies such as the study of vector-borne diseases where the evaluation of interactions at a fine scale is critical to understand their spatial dynamics. To overcome this need, we realized a homogeneous land cover mapping of these small islands, by analysing SPOT 5 satellite images acquired between July 2013 and July 2014 by SEAS-OI Station. We used an object-based image analysis method to identify the 12 major classes of land cover / land use of these tropical islands. This methodology together with a good knowledge of the field has enabled us to achieve an overall accuracy of 85%, making it an operational product. In order to illustrate the importance of this dataset, we present its use in health research to describe thelocation of health observations: whether the place of residence of patients or the points of capture of disease vectors through several examples in Reunion, Mayotte, the Union of the Comoros and the Republic of Seychelles. In these studies, high resolution allows to provide very fine information on the surrounding environment, while little data is usually available at this scale. In the statistical analyzes, these data were mainly used to differentiate between infected and non-infected individuals. This high resolution landcover is available on a web portal to allow a wider distribution to researchers and thematicians using land cover information in their field.

The southwest of the Indian Ocean comprises numerous islands of less than 3000 sq km (Comoros, Seychelles, Mascarene Islands). These small island territories have very fragmented and diversified environments. Satellite imagery and products at low and medium spatial resolution (usually from 4 kilometers to 250 meters) are not or poorly suited to the study of these areas. This is particularly the case for ecological studies such as the study of vector-borne diseases where the evaluation of interactions at a fine scale is critical to understand their spatial dynamics. To overcome this need, we realized a homogeneous land cover mapping of these small islands, by analysing SPOT 5 satellite images acquired between July 2013 and July 2014 by SEAS-OI Station. We used an object-based image analysis method to identify the 12 major classes of land cover / land use of these tropical islands. This methodology together with a good knowledge of the field has enabled us to achieve an overall accuracy of 85%, making it an operational product. In order to illustrate the importance of this dataset, we present its use in health research to describe thelocation of health observations: whether the place of residence of patients or the points of capture of disease vectors through several examples in Reunion, Mayotte, the Union of the Comoros and the Republic of Seychelles. In these studies, high resolution allows to provide very fine information on the surrounding environment, while little data is usually available at this scale. In the statistical analyzes, these data were mainly used to differentiate between infected and non-infected individuals. This high resolution landcover is available on a web portal to allow a wider distribution to researchers and thematicians using land cover information in their field.

International audience; The South-western Indian Ocean is characterized by various heterogeneous insular territories. Many of these islands are biodiversity hotspots and in order to preserve this heritage, some of them are protected. In La Reunion, the Parc National (created in 2007 and on the UNESCO world heritage list since 2010), covers 40 % of the territory while since 2006, Europa island (Shattered Islands) is a national natural reserve where some areas are integrally protected. Forest fires are a major threat to these areas of preserved biodiversity. Last main fires in La Reunion occurred in 2010, 2011 and 2013, and in june 2013 on Europa island.In 2013, the monitoring and mapping of the fires of Etang-Saint-Paul (July, La Reunion) and Europa (June) were carried out by the SEAS-OI (Survey of Environment Assisted by Satellites in the Indian Ocean), in collaboration with the ONF (Office National des Forêts) of La Reunion and the SDIS (Service Départemental d’Incendie et de Secours), using high resolution SPOT 5 imagery. These maps allowed the estimation of the fire extent, to about 4 and 70 hectares for Europa and Etang-Saint-Paul respectively, and to support field intervention during the crisis.In both cases, the monitoring of post-fire recovery of the affected areas was realized using PLEIADES images acquired by the SEAS-OI station in the frame of the CNES RTU. This part of the study is still ongoing and aim at taking advantage of the very high spatial resolution offered by PLEIADES products in order to quantify precisely the extent of the burned surface during both fires, and provide first insights on the post-fire evolution in terms of plant recolonization. This is an important issue in these protected areas where the ecosystems are threatened by the post-fire settlement of invasive species.This study was part of the operational mission of the SEAS-OI station, gathering local actors in the management of forest fire crisis in the south-western Indian Ocean. In particular, we demonstrate here the interest of the satellite approach in the management of natural disasters on remote territories like Europa island, and in protected areas where a rapid response is needed. Thanks to the combination of optical SPOT 5 and PLEAIDES high resolution products, SEAS-OI was able to provide operational products for the management of these fires. These applications led to a partnership between SEAS-OI, the ONF and the SDIS, whose objective is to use satellite images to monitor the protected territories of the Iles Eparses.

International audience; Background: Malaria remains endemic in Comoros. In 2006, malaria was the leading cause of mortality, morbidity and consultation in hospitals. The Government of the Union of the Comoros is committed in the fight against malaria through the establishment of a National Strategic Plan in 2007 that was later updated for the period 2012-2016. The results of these efforts show that the disease is in a pre-elimination phase. Despite a clear decline of malaria several aspects of its epidemiology should be clarified including the identification of endemic areas.Methods: Monthly cases, as reported by the “Programme National de lutte Contre le paludisme” (PNLP) from 2010 to 2014, were geo-referenced in each island at the sanitary district level. The incidence of malaria by district was calculated using population data from the National Census. We completed the spatial database with data on environmental and social factors including meteorology, physical geography, land use (analyzed by remote sensing of SPOT 5 satellite images), population characteristics, and health care facilities. We performed statistical analyzes to show the relationships between the variables and the prevalence of malaria.Results: The mapping of malaria incidence between 2010 and 2014 shows its heterogeneity among the 17 sanitary districts. Five districts (Hambou, Centre, Fomboni, Mutsamudu and Pomoni) reveal a high endemicity. Also we have highlighted the spatial relationships between malaria incidences and environmental and socio-demographic variables.Conclusion: This work is the first spatial analysis of the epidemiology of malaria in Comoros. It contributes to a better understanding of the spatial dynamics of malaria to help the Ministry of Health to eradicate malaria by 2016.

International audience; This paper describes the Spatial Data Infrastructure of the SEAS-OI satellite ground station. The objective of this SDI is to promote the use and to enhance the distribution of satellite data among the scientific community and the public institutions in the Southwest of the Indian Ocean.

International audience

Although there are statistics and general cartography on irrigation systems in Latin America, this information does not permit to identify the irrigated family farming zones located in the highland areas. In this article we locate and quantify those zones through the use of cartographic methods that helped to identify the zones that meet three requirements: 1) they are irrigated areas; 2) they are located in zones above 1000 m; 3) Their rural population density is higher than 50 inhabitants per km2. The results confirm a wide presence of this type of systems in all Latin-American sub-regions. Nevertheless, due to the restrictions of quality and updating of the information from the available sources, the results given in the present document must be taken as a guideline. Si bien existen estadísticas y cartografía general sobre los sistemas de riego en Latinoamérica, esta información no permite identificar las zonas de agricultura familiar irrigada localizada en zonas altas. En este artículo ubicamos y contabilizamos dichas zonas mediante la utilización de metodologías cartográficas que permitieron aislar las zonas que cumplen tres requisitos: 1) son áreas irrigadas, 2) están ubicadas por encima de los 1000 m. y 3) su densidad poblacional rural es superior a 50 hab/km². Los resultados confirman la amplia presencia de este tipo de sistemas en todas las subregiones de América Latina. Sin embargo, debido a las restricciones de calidad y actualización de la información de base, los resultados presentados deben tomarse a nivel orientativo. Bien qu'il existe des statistiques et cartographie générale sur les systèmes d'irrigation de l'Amérique latine, il n'est pas possible de distinguer les zones d'agriculture familiale irriguée situées en altitude. Dans cet article nous localisons et quantifions ces zones en utilisant des méthodologies de cartographie qui permettent d'isoler ce type de zones. Les critères retenus pour la sélection de ces zones sont : 1) la présence d'irrigation; 2) une densité de population rurale dépassant 50 habitants/km2; 3) une altitude supérieure à 1000m. Les résultats obtenus confirment une présence remarquable de ce type de production à travers du continent. Toutefois, en raison du manque de précision de certaines sources données, les résultats présentés sont à titre informatif.

This study aims to compare urban land cover classifications based on the use of two decision trees - Best First Tree (BFT) and Logistic Model Tree (LMT) - for two different legend levels. The legend level 1 presents 11 urban land cover classes and the legend level 2 presents 42 classes. A WorldView-3 image was used, with 16 multispectral bands and a spatial resolution of 0,31 m. The study area corresponds to a transect within the campus of Campinas State University, São Paulo, in the Southeastern Region of Brazil. At the legend level 1, the classifications achieved very similar accuracies, showing global accuracy indices around 76% and 82%. At the legend level 2, on its turn, the accuracies were very different. The results obtained by the BFT algorithm presented a global accuracy index of 64%, while this index reached 78% for the result produced by the LMT algorithm. The comparisons between classifications accomplished at the same legend level were performed by means of hypothesis tests. The comparisons revealed that at the legend level 1 the performance of the algorithm was significantly the same in both scenes. However, at the legend level 2, the LMT algorithm performed better than the BFT algorithm. Thus, one can conclude that the greater spatial and spectral refinement of the WV-3 sensor contributed to the improvement of the classification accuracy in the more detailed legend level.