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La densité de bâti est calculée par maille de 150 mètres de côté et sur la base d'une extraction du bâti à partir d'imagerie très haute résolution spatiale (1.5m) SPOT 6/7, pour les années 2015 à 2019.
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L'atlas cartographique offre un aperçu des données produites et traitées dans le cadre du projet Artisols. Ce dernier, soutenu par la Région Occitanie et le Fonds Européen de Développement Régional (FEDER), s’inscrit dans une démarche d’évaluation et de qualification du processus d’artificialisation des sols en région Occitanie.Neuf grandes thématiques y sont développées : - Les bâtiments résidentiels et d’activité- L’occupation du sol - La densité de bâti par maille de 150 m de côté - L'évolution de la densité de bâti entre 2017 et 2019- Les taches urbaines - La densité de bâti au sein des taches urbaines- Le coefficient de dispersion- L'indice de fragmentation des espaces non artificialisés- L'indice de compacité des taches urbaines
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Cette donnée raster résulte d'une classification par méthode d'apprentissage profond à partir d'imagerie très haute résolution spatiale (1.5m) SPOT 6/7. Des post-traitements ont été effectués afin de mieux caractériser les classes relatives à l'artificialisation.
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Meteorological observations from weather stations interpolated on a 25x25 km grid, on a daily basis from 1979 to the last calendar year completed, for France. Meteorological observations are freely accessible via OGC SensorThings Standard service : https://frost.geosas.fr/agri4cast/v1.0/ Observed properties : - maximum air temperature (°C), - minimum air temperature (°C), - mean air temperature (°C), - mean daily wind speed at 10m (m/s), - vapour pressure (hPa), - sum of precipitation (mm/day), - potential evapotranspiration from a crop canopy (mm/day), - total global radiation (KJ/m2/day), More informations on Agri4cast Resources Portal : https://agri4cast.jrc.ec.europa.eu/DataPortal/Index.aspx
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ObjectivesThe hyperspectral images (HI) is at the moment still too poorly considered; nevertheless its specificities make a weighty auxiliary for the monitoring of the elements of the urban area. The HYEP project has for objective to propose a panel of methods and processes designed for hyperspectral imaging. We take into account other existing sensors in order to compare the performances. If the IH is complementary to the sensors HRS and VHRS due to its better radiometric richness, it allows to identify and to characterize the natural or anthropogenic elements in a complementary perspective. To this end methods for the extraction of information had to be adapted, created even. The methodological part of the project articulated at the same time in the solidification of the current approaches and the design of new methods. Results have been presented along the project duration to scientific community and local authorities. One of the milestones of the works was the comparison of the results to various spatial resolutions to specify the contribution of such a hyperspectral sensor with regard to those existing or to come. Data and data processing Methods: existing or adapted The methods were chosen among all the existing methods by adapting them to the signal, among spectral ranges and to the characteristics of urban areas. Since data arose from airborne platforms, the first developments were realized to counter the effects of the atmosphere on the IH (atmospheric correction - 3 tested methods) and a database of spectral signature for diverse elements of land use in town (roofs, roads, the vegetation etc.) was established. It allowed encircling better the spectral values of materials. It was set up based simultaneously on the literature, in situ and laboratory measurements. Its contributions in various classification processing were tested. Methods for information, extraction, pansharpening or classification purposes were used for various spatial and spectral resolutions to highlight its interest towards other sensors and also its benefits for a spatial mission. Classification and unmixing methods have been adapted and spatial pattern indicators for urban areas defined.Outcomes- 3 atmospheric correction methods have been tested; it leads to a specific code development by ONERA.- Methods adaptation : pansharpening and unmixing- Transfer: a complete design of the study has been transfered to Kaunas (Lituania) teams- Algorithms: Depository on http://openremotesensing.net/- One of the major results is the extraction and the identification of photovoltaic panel- CNRS Summer school 2017Scientific productionThe team has presented at ISPRS Geospatial Week 2015, GeoHyper (2015), Jurse 2017, IGARSS 2016-2017, SFPT or workshops TEMU, AFIGEO and to GdR Session (MaDics and ISIS) or within the framework of the Hypxim mission. The team organized special conference sessions at the national level, SFPT hyperspectral (2016) and international level IGARSS 2018 and WHISPERS 2018. A thematic CNRS summer school (2017 August 28 - September 1st - 25 participants) has been set up.The project gave rise to 10 publications Rang A and 38 communications, 4 chapters and a special issue for the RemoteSensing journal.
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Les cartographies des espaces bâtis sur la région Occitanie résultent d'une extraction automatique par méthode d'apprentissage profond (deep learning) à partir d'imagerie très haute résolution spatiale (1.5m) SPOT 6/7, pour les années 2015 à 2019. Fichiers fournis sous forme vectorielle. (2021-09-09)
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The re-establishment of the river continuum on the Sélune after the dams have been levelled will enable colonization of the upper reaches of the basin, which were previously inaccessible to eels. Before the dams were levelled, two main tributaries were used by amphihaline fish for reproduction, in addition to the main river: the Beuvron and the Oir. The eel population of the Sélune was monitored in the pre-flushing phase by abundance index campaigns carried out in 2013, 2015, 2019 on a network of stations covering the entire Sélune hydrographic network. Since 2021, this network of stations has evolved to monitor changes in the part of the watershed accessible following the dismantling of the 2 dams. These data enable us to estimate changes in eel abundance along the Sélune and its tributaries, as well as their size structure before and after the removal of the dams. The inventory is carried out in early September, every other year between 2013 and 2019, then every year since, using an electric fishing device and dip nets. Thirty thirty-second fishing stations are set up. A fishing station comprises approximately 100 meters of river. All eels caught are anaesthetized and biometric measurements are taken (weight, length, horizontal and vertical eye diameter, determination of yellow or silver stage). All eels are released directly at the fishing site. This layer provides station abundances by fishing session.
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Geodetic markers were installed along the main course of the Sélune. Physically marked out in the field, these markers have been located with a high-precision GPS (planimetric and z-precisions are given in the table). Please note that these markers may move slightly with the wetting/drying cycles of mainly clay soils, and their coordinates may be updated if necessary. Geodetic markers can be used as reference points to define a device or a new study area.
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Cette carte est issue de travaux de recherche menés dans le cadre du projet GABIR (Gestion Agricole des Biomasses à l’échelle de l’Ile de la Réunion). Elle a été produite en utilisant une mosaïque d'images Spot6/7 pour calculer la segmentation (extraction d'objets homogènes à partir de l'image). Nous utilisons une base de données terrain ayant une nomenclature emboitée avec 3 niveaux de précision nous permettant de produire une classification par niveau. Le niveau 3, le plus détaillé distinguant les types de cultures présente une précision globale de 86% et un indice de Kappa est de 0,85. Le niveau 2, distinguant les groupes de cultures présente une précision globale de 91% et un indice de Kappa est de 0,90. Le niveau 1, distinguant les grands groupes d'occupation du sol présente une précision globale de 97% et un indice de Kappa est de 0,95. (2019-06-12) La précision globale de la carte est de 88,71 % et l'indice de Kappa est de 86,47%. La chaine Moringa est mise au point au sein du CES Occupation des Sols du pôle THEIA pour cartographier l’occupation du sol dans les contextes variés des pays du Sud. Afin d’être plus facilement reproductible, elle est automatisée et son implémentation est réalisée avec des outils libres (Orfeo Toolbox, R, Python). (2019-03-26)