Work Packages
From Research Challenges to Innovative Solutions
The project is divided into thematically connected work packages that systematically address the key research challenges and objectives of the GeoAI project. Each work package is divided into tasks that address areas of acquisition and processing of diverse spatial data, advanced spatial analytics with artificial intelligence, and selected use cases.
Work Packages
MANAGEMENT AND COORDINATION
Leader: Prof. Dr. Anka Lisec (UL FGG)
The work package is dedicated to project coordination and management, including data management and risk management; additionally, this WP is dedicated to activities for dissemination of project results and communication. The work package consists of:
- Task 1.1: Project administration and coordination,
- Task 1.2: Data management,
- Task 1.3: Quality assessment and risk management,
- Task 1.4: Communication and dissemination.
DATA
ACQUISITION
Leader: Prof. Dr. Krištof Oštir (UL FGG)
The work package is dedicated to geospatial technologies for acquisition and modeling of spatial data. It addresses scientific and technological challenges related to diverse geospatial data sources with varying temporal and spatial resolution; the goal is to evaluate existing data sources and develop innovative process models for acquisition and processing of spatial data obtained through mass acquisition technologies. The work package consists of:
- Task 2.1: Assessment of usability and validation of existing remote sensing datasets for spatiotemporal modeling,
- Task 2.2: Acquisition and processing of UAV-photogrammetric and multispectral data for large-scale spatiotemporal modeling,
- Task 2.3: Acquisition and processing of UAV-hyperspectral data for large-scale spatiotemporal modeling,
- Task 2.4: Acquisition and processing of terrestrial data for 3D modeling.
SPATIAL
ANALYTICS
Leader: Prof. Dr. Sašo Džeroski (IJS)
The work package is dedicated to the development and validation of machine learning (ML) methods for (semi)automated geospatial mapping and modeling based on various georeferenced data acquired through diverse platforms and sensors. The work package consists of:
- Task 3.1: Foundation models for remote sensing data,
- Task 3.2: Machine learning for point cloud processing,
- Task 3.3: Integration of geospatial data from different sources,
- Task 3.4: Advanced machine learning methods for geospatial data,
- Task 3.5: Semantic technologies for sharing and reuse of geospatial data and models.
GEOSPATIAL
MODELING
Leader: Assoc. Prof. Dr. Žiga Kokalj (ZRC SAZU)
The work package is dedicated to the development of artificial intelligence-based solutions for processing and analysis of spatial data and advanced 3D and 4D modeling of spatial phenomena. The work package consists of:
- Task 4.1: Time series modeling for change detection,
- Task 4.2: 3D modeling of topography and spatial phenomena for risk management,
- Task 4.3: Processing and visualization of large point clouds,
- Task 4.4: Object-oriented 3D modeling of cities and landscapes,
- Task 4.5: Extended reality technologies for using 3D city models in analytics and urban planning.
PILOT PROJECTS
Leader: Dr. Mateja Jemec Auflič (GeoZS)
The work package is dedicated to use cases where advanced geospatial data models and algorithms developed in WP2, WP3, and WP4 will be applied to selected examples, with particular emphasis on geospatial modeling in support of sustainable spatial planning and sustainable and resilient management of the built and natural environment. The work package consists of:
- Task 5.1: Geospatial technologies for land cover change analysis,
- Task 5.2: Geospatial information for landslide management,
- Task 5.3: 3D geospatial modeling for studying underground structures and aquifers,
- Task 5.4: Multi-hazard risk assessment modeling in cultural heritage areas,
- Task 5.5: 3D models of cities and landscapes for urban planning/monitoring and flood modeling.
