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Understanding Our World Through Data Join hundreds of the world’s top data experts to exchange knowledge, transform your skills, and get inspired with FME. With over one hundred sessions on a range of topics, the FME International User Conference (FME UC) is three days of learning and networking geared for every user level from "newbie" to "ninja". Info and registration here.

Towards consistent inland water body mapping across space and time from optical Earth observation systems Inland water bodies, while covering less than 4% of the Earth surface, are essential to many global dynamic processes such as biogeochemical cycles, biodiversity, climate change and ecosystem services. Mapping the temporal distribution of terrestrial water is thus crucial for scientific research as well as for sustainable ecosystem management. The current deployment of an unprecedented Earth observation satellite constellation provides a unique opportunity to monitor quantitatively our changing environment. The tsunami of heterogeneous spatial datasets recently available required appropriate methods to extract relevant information. In this context, we aimed at mapping consistently inland water bodies with optical remote sensing by developing methods taking into account spatial and temporal resolutions independently of the environmental context and the observation sources. First, the thesis proposes a framework improving delineation of water bodies by handling sub-metric multi-source data acquired in heterogeneous observation conditions. Secondly, we assess the minimum size of water body mappable at sub-pixel level from 10-m sensors, with a specific interest for Sentinel-2 instrument potential. Thirdly, mapping water bodies using twice-daily 250-m MODIS observation was successfully demonstrated to produce maps and indicators describing the location, the intra-annual and the inter-annual behavior of all African inland water bodies. Finally, we address the challenge of water body map validation by proposing and applying an original validation strategy specific for land cover class underrepresented at a global scale.

Summary - Mapping annual cropland over large areas with high resolution satellite image time series With human population growth, biofuel development and climate change, the food supply system is subject to increasing pressures. In this context, timely and dependable information on crop production becomes crucial for market stability and food security. In spite of advances in satellite systems and data processing, there is a disconnect between operational cropland mapping and the state-of-the-art. This thesis seeks to bridge this gap by capitalizing on available land cover maps and by optimizing the satellite inputs. First, priority areas are identified for all countries to strategically allocate future efforts. Second, methods are proposed to enable regular cropland mapping over large areas in the absence of in situ calibration data. The combination of calibration data selected from land cover maps and spectral-temporal features derived from the satellite image time series yields spatially consistent results with an accuracy that varies depending on the landscape. The features are stable over time and reduce the intra-class variability which improves generalization. Finally, the spatial resolution requirements can be anticipated by quantifying the fragmentation of the agricultural landscapes. It allows to adjust the resolution to cope with the ever-increasing data volumes and to select appropriate imagery for reliable area estimation. These are essential building blocks towards an operational cropland mapping system and an improved global agriculture monitoring. http://www.uclouvain.be/fr/agenda/sst

Améliorez vos compétences en ArcGIS for Desktop grâce à ce cours qui vous apprendra à utiliser les outils ArcGIS pour la création de workflows dans le but d’analyses géospatiales. Vous apprendrez à organiser et à préparer les données pour effectuer des analyses. Vous créerez vos propres modèles de géoprocessing et vous participerez à un ambitieux projet d’analyse. A la fin de ce cours, vous serez capable de choisir les fonctions et les outils adéquats pour chaque cas de figure. Public cible Les analystes et les experts en SIG, ainsi que les personnes qui gèrent ou réalisent des projets d'analyse SIG. Connaissances préalables Il est conseillé d'avoir suivi le cours "ArcGIS 2 : Processus Essentiels" ou de posséder des connaissances équivalentes. Les objectifs A la fin de ce cours, vous serez en mesure de : importer des données de formats divers dans une géodatabase; créer les outils et utiliser les fonctionnalités existantes qui permettent de garder intègres vos données et qui permettent, de plus, de minimiser les erreurs lors de la création et l’édition de données; pallier aux problèmes d’alignement spatial; utiliser les outils de géoprocessing adéquats dans le cadre d’un processus décisionnel; créer un modèle complexe pour automatiser les tâches d’analyses. Question spécifique? training2017@esribelux.com

Devez-vous travailler avec un grand nombre de formats et de sources de données CAD/GIS différents ? Souhaitez-vous les visualiser et les traiter d’une manière simple ? Cette formation vous est alors destinée. Plus d'infos et inscription sur http://www.gim.be/fr/gis-training/fme-desktop.