Objective By 2050, around three quarters of the world’s population will live in cities. The new dimension of ongoing global migration into the cities poses fundamental challenges to our societies across the globe. Despite of increasing efforts, global urban mapping still drags behind the geometric, thematic and temporal resolutions of geo-information needed to address these challenges.Nowadays diverse sets of incomplete data exist. For example, Earth observation (EO) satellites reliably provide geodetically accurate large scale geo-information of the cities on a routine basis from space. But the data availability is limited by resolutions and acquisition geometries of the sensors. Complementarily, massive imagery, text messages and GIS data from open sources and social media are temporally quasi-seamless, spatially multi-perspective, but with diversely unknown qualities. With So2Sat I will jointly exploit big data from social media and satellite observations for global urban mapping, and aim at breakthroughs in 3D/4D urban modelling, infrastructure occupancy classification, and very high resolution population density mapping on a global scale for revolutionizing urban geographic research. The following methodological and application objectives will be addressed: improving urban-related information retrieval from EO satellite data (MO1), mining urban imagery and text messages from social media data (MO2), information fusion from heterogeneous data sources (MO3), big data processing (MO4), as well as pilot applications in informal settlements classification (AO1) and global population density estimation (AO2).The outcome of So2Sat will be the first and unique global and consistent spatial data set on urban morphology (3D/4D) of settlements, and a multidisciplinary application derivate assessing population density. This is seen as a giant leap for urban geography research as well as for formation of opinions for stakeholders based on resilient data. Fields of science natural sciencesearth and related environmental sciencesatmospheric sciencesclimatologyclimatic zonesengineering and technologymechanical engineeringvehicle engineeringaerospace engineeringsatellite technologynatural sciencescomputer and information sciencesdata sciencebig datanatural sciencescomputer and information sciencesartificial intelligencemachine learningdeep learningnatural sciencescomputer and information sciencesdata sciencedata processing Programme(s) H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC) Main Programme Topic(s) ERC-2016-STG - ERC Starting Grant Call for proposal ERC-2016-STG See other projects for this call Funding Scheme ERC-STG - Starting Grant Coordinator TECHNISCHE UNIVERSITAET MUENCHEN Net EU contribution € 1 440 250,00 Address Arcisstrasse 21 80333 Muenchen Germany See on map Region Bayern Oberbayern München, Kreisfreie Stadt Activity type Higher or Secondary Education Establishments Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Other funding € 0,00 Beneficiaries (2) Sort alphabetically Sort by Net EU contribution Expand all Collapse all TECHNISCHE UNIVERSITAET MUENCHEN Germany Net EU contribution € 1 440 250,00 Address Arcisstrasse 21 80333 Muenchen See on map Region Bayern Oberbayern München, Kreisfreie Stadt Activity type Higher or Secondary Education Establishments Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Other funding € 0,00 DEUTSCHES ZENTRUM FUR LUFT - UND RAUMFAHRT EV Germany Net EU contribution € 56 250,00 Address Linder hohe 51147 Koln See on map Region Nordrhein-Westfalen Köln Köln, Kreisfreie Stadt Activity type Research Organisations Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Other funding € 0,00
