Descrizione del progetto
Analizzare la geografia storica della popolazione e il suo effetto sull’uso del suolo
L’urbanizzazione ha determinato cambiamenti radicali nella distribuzione della popolazione ed è direttamente collegata a cambiamenti ambientali quali la deforestazione e l’abbandono dei terreni agricoli. Sebbene esista una mappatura contemporanea dell’uso e della copertura del suolo rispetto alla geografia dinamica della popolazione in Europa, simili correlazioni precedenti al 1970 risultano limitate. Finanziato dal Consiglio europeo della ricerca, il progetto GeoAI_LULC_Seg si propone di utilizzare l’intelligenza artificiale geospaziale per mappare accuratamente l’uso e la copertura del suolo dal 1940 in poi in una regione di confine tra Bulgaria e Turchia. Saranno messe in relazione le prime fotografie aeree, le immagini satellitari e i dati dei censimenti. Questo permetterà di ottenere una visione completa dell’uso e della copertura del suolo per aiutare i ricercatori a prevedere la futura geografia della popolazione e i cambiamenti nell’uso di tali terreni.
Obiettivo
Rural depopulation, agricultural land abandonment, and deforestation are massive concerns for Europe and elsewhere today and our planet's future. These interlinked phenomena can be analysed using land use and land cover (LULC) maps combined with dynamics of population geography, especially regarding urban sprawl. Modern LULC and spatially disaggregated population datasets go back to the 1980s and 1970s. Although we have earlier population data, these are not geomatched to locations in LULC maps. Earlier LULC maps are either not very reliable (extracted from historical maps) or limited in their geographical coverage (based on selected aerial photos or satellite imagery). These are severe limitations to developing longer and deeper perspectives and understanding the root causes of these detrimental changes in population geography and land use practices in large territories.
GeoAI_LULC_Seg will develop an advanced, modular, and customizable geospatial artificial intelligence-based land use land cover segmentation process to accurately map LULC conditions for around 30,000 km2 in a border region between Bulgaria and Turkey, including the cities Edirne, Istanbul, and Plovdiv, from historical aerial photographs and early reconnaissance satellite images (dating back to the 1950s and the 1970s respectively) by pairing them with geotagged historical population census data.
Our methodological novelties are not limited to GeoAI-based object segmentation and super-resolution applications for panchromatic imagery for our research area. Our project will create transferable knowledge and scalable methods for global applications for the 1970s, thanks to worldwide coverage of high-spatial-resolution satellite imagery we will process. Furthermore, we will build long-term LULC maps series commensurable with current satellite data (1950-2020), allowing us to improve predictions for future population geography and LULC changes.
Campo scientifico
- engineering and technologymechanical engineeringvehicle engineeringaerospace engineeringsatellite technology
- natural sciencesphysical sciencesopticsmicroscopysuper resolution microscopy
- natural sciencesphysical sciencesastronomyplanetary sciencesplanets
- natural sciencesearth and related environmental sciencessoil sciencesland-based treatment
- social sciencessociologydemographycensus
Programma(i)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Argomento(i)
Meccanismo di finanziamento
HORIZON-AG-LS - HORIZON Lump Sum GrantIstituzione ospitante
34450 Istanbul
Turchia