The webinar will provide an update on ESA’s P‑band SAR mission one year after launch, highlighting its key characteristics and in‑orbit performance. It will showcase the first scientific results, including early insights into biomass
The rapid expansion of Earth observation data from satellites, aerial platforms, and cloud-based archives has created unprecedented opportunities for large-scale environmental monitoring and analysis. At the same time, the volume, complexity, and velocity of these data demand new
Applications of various AI-based models for environmental management, including deforestation monitoring, urban tree cover change and canopy height prediction, forest health assessment, nature resources management
Join us for an introductory webinar highlighting the latest updates and capabilities of the GIQ platform and related UAE space ecosystem initiatives supporting academic, startup, and R&D entities. The session will showcase how researchers
AI/ML plays a crucial role in agriculture analytics, especially in geospatial crop monitoring and mapping. In your research-based talk, machine learning models will be covered for classifying crops using multi-sensor temporal datasets such as optical
This webinar explores the frontiers of Synthetic Aperture Radar (SAR) Earth observation, moving beyond conventional InSAR to advanced techniques that redefine measurement precision. We know that multi-stack PSInSAR reveals millimeter-scale urban subsidence and structural instability
Arid and semi-arid regions are among the most vulnerable environments to climate change, land degradation, water stress, heat extremes, and atmospheric dust. This webinar will explore how satellite Earth observations, remote sensing, GIS, climate modeling
The recent proposal to the European Space Agency for Hydroterra+, a geosynchronous SAR in C-band with small eccentricity, to study the evolution of the water vapour in the atmosphere, will be presented. Another possible solution, ARGOS, considering MIMO formations, will be recalled.
Since its introduction in 2017, Geospatial Artificial Intelligence (GeoAI) has grown rapidly in remote sensing and GIS research. This technology does not just introduce a new topic; it changes how we approach geospatial science by prioritizing predictive
