Descripción del proyecto
Analizar la geografía histórica de la población y su efecto en el uso del suelo
La urbanización ha dado lugar a cambios bruscos en la distribución de la población y está relacionada de forma directa con cambios ambientales como, por ejemplo, la deforestación y el abandonos de tierras agrícolas. Si bien existe una cartografía contemporánea del uso y la ocupación del suelo (LULC, por sus siglas en inglés) comparada con la geografía dinámica de la población en Europa, las correlaciones similares previas a 1970 son escasa. El objetivo del proyecto GeoAI_LULC_Seg, financiado por el Consejo Europeo de Investigación, es emplear inteligencia artificial geoespacial para cartografiar con precisión el LULC a partir de 1940 en una región fronteriza entre Bulgaria y Turquía. En este sentido, se correlacionarán fotografías aéreas antiguas, imágenes satelitales y datos de censos. De este modo se creará una visión integral del LULC para ayudar a los investigadores a predecir la geografía de la población y los cambios en el uso del suelo en el futuro.
Objetivo
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.
Ámbito científico
- 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
Programa(s)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Régimen de financiación
HORIZON-AG-LS - HORIZON Lump Sum GrantInstitución de acogida
34450 Istanbul
Turquía