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The three-year project aims to develop innovative methods of Earth observation, geospatial modelling and spatial analytics for data-driven and knowledge-driven spatial decision-making. The project is an ambitious initiative designed to go beyond the state-of-the-art in geospatial science by integrating novel geospatial technologies, advances in artificial intelligence (AI) with its subdomain of machine learning (ML), and advances in big geospatial data processing and analytics. In addition, the project aims to increase research capacity in geospatial science in Slovenia and beyond, with a particular focus on using geospatial artificial intelligence and machine learning for the advanced 3D/4D spatial modelling and analytics within geospatial information systems (GIS) to support spatial decisions.
Given the overall project objectives and to accelerate the transition towards a sustainable and resilient society, the project has five (5) specific objectives that will be achieved through interlinked tasks defined in the project work packages (WPs):
(i) To develop pipelines for using cutting-edge technologies for mass geospatial data acquisition and EO, focusing on open data and low-cost technologies at various spatial and temporal scales;
(ii) To develop and validate novel ML methods for (semi)automated geospatial mapping and modelling based on various geospatial data, with a particular emphasis on the scientific challenges related to geospatial data fusion and advanced ML;
(iii) To conceptualise and develop innovative 3D and spatial-temporal models, analytics and visualisation of the built and natural environment at various scales from neighbourhood level to regional and cross-border levels, focusing on models relevant for supporting spatial decisions;
(iv) to enhance the research and innovation (R&I) excellence and technological capacities of partner institutions in geospatial science and beyond through interdisciplinary collaborative research activities; and
(v) to increase the overall R&I potential of the geospatial domain by applying and disseminating the acquired knowledge and, with this, to generate an impact on society.
Work Packages:
The project is organised into five work packages:
WP1: Project coordination, dissemination and communication, dedicated to project coordination and management, including data management and risk management, as well as to communication and dissemination activities;
WP2: Geospatial technologies for spatial data acquisition and modelling, dedicated to the scientific and technological challenges related to various geospatial data sources at different spatial and temporal scales; the aim is to evaluate the existing datasets and develop innovative pipelines for selected mass geospatial data acquisition and processing technologies;
WP3: Machine learning for geospatial modelling, dedicated to developing and validating machine learning (ML) methods for (semi)automated geospatial mapping and modelling based on various georeferenced data acquired by various platforms and sensors;
WP4: Geospatial modelling and analytics to use geospatial data and ML models for spatial data processing for advanced 3D and 4D modelling of spatial phenomena;
WP5: Geospatial modelling for decision support – use cases, where advanced geospatial models and ML algorithms developed in WP2, WP3, and WP4 will be used for selected applications, with a particular focus on its application for geospatial modelling to support sustainable spatial planning and sustainable and resilient management of built and natural environments.
Project partnership
University of Ljubljana, Faculty of Civil and Geodetic Engineering (UL FGG) (lead partner)
University of Ljubljana, Faculty of Computer and Information Science (UL FRI)
Jožef Stefan Institute (IJS)
Scientific Research Centre of the Slovenian Academy of Sciences and Arts (ZRC SAZU)