This ressource is part of the action 1 of the ESPOIRS Project. Multiple GNSS Stations have been installed or updated in the SWIO and the data are available here. "TO ADD : Different datasets, list of stations, etc ...."

This dataset encompasses model outputs generated by the Weather Research and Forecasting (WRF) regional climate model. A high-resolution (~1km) downscaling simulation was performed over two tropical islands, Reunion and Mauritius, situated in the South-West Indian Ocean (SWIO), with initial and boundary conditions provided by the ERA5 reanalysis with a global resolution of 0.25° × 0.25°. The simulation used three nested domains sequentially configured with spatial resolutions of 9, 3, and 1km, respectively, with a downscaling ratio of 3. The physical configurations of this simulation were determined through previous modeling studies and sensitivity tests. The published simulation data currently covers a period of 10 years, starting from 1991 (with the possibility to be extended to 30 years). Over 60 output variables were selected for publication with open access, including those related to the intermittent energy resources (e.g., surface solar radiation and its direct/diffuse components, wind speed/direction at multiple vertical levels, and precipitation, of interest for the run-off-river hydropower), as well as the widely used climatic/meteorological variables (e.g., temperature, pressure, humidity, etc.) at a temporal resolution varying from a day up to 30 minutes. All the data are available through an open-access data server, where an intelligent algorithm is applied to simplify the download process for data users. For the first time, a long-term, high-resolution climate/meteorological dataset covering Reunion and Mauritius has been simulated and published as open-access data, yielding substantial benefits to studies on climate modeling, weather forecasting, and even those related to climate change in the SWIO region. In particular, this dataset will enable a better understanding of the temporal and spatial characteristics of intermittent climate-related energy resources, consequently facilitating their implementation towards a green and low-carbon future.

The coastline or shoreline is the geographical boundary between sea and land. It corresponds according to the SHOM to "the leash of the highest seas in the context of an astronomical tide of coefficient 120 and under normal weather conditions (without overcost phenomenon). The coastline as defined above is not directly identifiable continuously on the ground or on a satellite or aerial image. From a perspective of studying the displacement of the shoreline, indicators allow us to approach this notion (the vegetation limit associated with the infrastructure limit, the beach limit, etc.). On the reef shoreline of Reunion Island the limit of vegetation and infrastructure as well as beach limit were retained. This limit results in the production of a line-type vector geographic information layer in a GIS resulting from the photo-interpolation on Pléiades satellite images. Pleiades satellite images from the Kalideos Réunion database (CNES) have been used since 2016 to study the position of the shoreline annually. Launched in 2011, Pléiades is a very high spatial resolution spatial image system (panchromatic optical instrument at 70 cm and 2.8 m multispectral) operating in the visible and near infrared with a swath of 20 km UMR Espace-Dev

The ressource describes the dataset obtained by deploying the GAMIC GMWR-25-DP RADAR in Toamasina (Tamatave) in Madagascar.

The ressource describes the dataset obtained by deploying the GAMIC GMWR-25-DP RADAR in the north of Mahé Island, in Seychelles.

The resource provides two land cover maps of Réunion Island for the years 1950 and 2022 derived from the analysis of ortho-photographs at the island scale (Source IGN). The produced typology uses five cover classes: forest, low vegetation, agriculture, urban, and shadow (related to topography). The method used is based on encoding the two aligned rasters, converted into a single band of grayscale for 2022, using a vision-transformer deep learning model. From the features calculated for each pixel, a random forest classification model is trained separately for each year using a set of ROIs (Regions Of Interest), target polygons delineated within each of the selected classes through photo-interpretation of the original images. Model validation is performed on independent sets of polygons also defined by photo-interpretation. The maps provided in the resource are derived from the prediction of cover classes for both years using the trained and validated models. These are raw predictions, meaning that no post-processing has been applied to reduce potential noise due to classification errors. The shared resource is part of the results from the FRAG'ILE research and development program (FRAGmentation en milieu InsuLairRE, UR / CBNM/ IRD, funded by OFB, https://fragile.frama.io).

WW3 model reanalysis on SWIO (south-western indian ocean) area at 0.5 degree of resolution

The beach profile is a sectional representation of its topography. The beach topography and its dynamics (by beach profile or transect approach) is illustrated by the acquisition of altimetry data along a fixed profile. 22 profiles are regularly monitored on the reef coast of Reunion Island: 2 profiles per year before the swell seasons of summer and austral winter; the impact of the events of strong swells (cyclones, southern swells) is systematically measured on the labeled Dynalit sites and more sporadically on the other sites. The methodology deployed locally since 2012 involves two Topcon Hiper II receivers (base and mobile) and one Topcon FC-250 controller (field notebook).

Le projet a pour objectif d'améliorer le signal de la pluie détectée par les géophones en comparant les données météorologiques d'un disdromètre, d'un pluviomètre et de 3 géophones afin d'extraire des données des sismographes pour mieux comprendre le transport sédimentaire issu du réseau sismologique installé dans la rivière des pluies et la rivière du Mat. Les objectifs sont : 1) déterminer les caractéristiques sismiques de la pluie sur le site de mesures 2) A terme, comprendre le déclenchement des éboulements et glissements liés aux pluies A court terme, ce projet devrait aussi permettre de : 1) comprendre pour un même type de pluie l'influence de sols de rugosités différentes sur les signaux enregistrés par les sismomètres 2) intégrer/contraindre pour un même type de sol l'influence de types de pluies différentes sur les enregistrements des sismomètres 3) déterminuer l'influence des tailles des gouttes et du nombre de gouttes (indications données par le disdromètre) sur le signal sismique