BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//ESGRS - ECPv6.18.2//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:ESGRS
X-ORIGINAL-URL:https://esgrs.ae
X-WR-CALDESC:Events for ESGRS
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:Asia/Dubai
BEGIN:STANDARD
TZOFFSETFROM:+0400
TZOFFSETTO:+0400
TZNAME:+04
DTSTART:20250101T000000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Asia/Dubai:20261028T110000
DTEND;TZID=Asia/Dubai:20261028T120000
DTSTAMP:20261013T070239Z
CREATED:20261013T070239Z
LAST-MODIFIED:20261013T070239Z
UID:6700-1793185200-1793188800@esgrs.ae
SUMMARY:AI-Driven Time-Series InSAR for Ground Deformation and Geohazard Monitoring
DESCRIPTION:This webinar presents an AI-driven approach to time-series Interferometric Synthetic Aperture Radar (InSAR) for monitoring and understanding Earth surface deformation and supporting geohazard assessment. It will provide an overview of the principles of InSAR and multi-temporal analysis\, including the extraction and interpretation of deformation patterns from satellite radar observations over time. \nThe webinar will explore how Artificial Intelligence and Machine Learning can be integrated with InSAR time-series techniques to improve the detection\, characterization\, classification\, and prioritization of deformation signals and anomalous areas. Particular attention will be given to AI-based approaches for identifying persistent and emerging deformation hotspots\, distinguishing significant deformation patterns from noise and measurement uncertainties\, and transforming large-scale satellite observations into actionable information. \nPractical examples will be presented to demonstrate the potential of combining Sentinel-1 SAR data\, time-series InSAR processing\, and AI techniques for monitoring phenomena such as land subsidence\, ground instability\, landslides\, and other geohazard-related deformation processes. The webinar will also discuss challenges related to temporal variability\, atmospheric effects\, spatial and temporal resolution\, data quality\, and the generalization of AI models across different geographic and environmental conditions. \nFinally\, the webinar will highlight the potential of AI-driven InSAR as a scalable Earth Observation framework for continuous deformation monitoring\, early detection of abnormal surface movements\, geohazard assessment\, and the development of intelligent early-warning and decision-support systems. \n\nRegister Now\n\n\n    \n    \n    \n\n                \n        \n            \n\n                \n                                \n                    \n                        \n                            \n                                \n                                Dr. Hind Zeyada Abdel Hamid EbrahimAI & Satellite Remote Sensing Research Scientist at National Authority for Remote Sensing and Space Sciences (NARSS)Dr. Hind Zeyada Abdel Hamid Ebrahim is an AI and Satellite Remote Sensing Research Scientist at the National Authority for Remote Sensing and Space Sciences (NARSS)\, Egypt. She holds a PhD in Computer and Systems Engineering\, with a specialization in Artificial Intelligence and SAR Remote Sensing. Her research focuses on AI-driven Earth Observation\, Synthetic Aperture Radar (SAR)\, time-series InSAR\, Earth surface deformation monitoring\, and geohazard assessment. She has extensive experience in developing deep learning and AI approaches for satellite imagery analysis\, including SAR-based oil spill detection and monitoring\, as well as Sentinel-2-based water body mapping and monitoring. Her research also covers environmental monitoring\, land cover analysis\, and the development of intelligent Earth Observation solutions. She is actively involved in academic teaching\, scientific research\, and the supervision of AI and remote sensing projects. \n\n                            \n                        \n                    \n\n                    \n                        \n            \n\n        \n                \n        \n            No Results Found
URL:https://esgrs.ae/wevent/ai-driven-time-series-insar-for-ground-deformation-and-geohazard-monitoring/
LOCATION:Virtual
CATEGORIES:2026,Webinars
ATTACH;FMTTYPE=image/jpeg:https://esgrs.ae/wp-content/uploads/2026/10/dwk-earth.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Dubai:20261109T090000
DTEND;TZID=Asia/Dubai:20261109T153000
DTSTAMP:20260928T052651Z
CREATED:20260928T051822Z
LAST-MODIFIED:20260928T052651Z
UID:6679-1794214800-1794238200@esgrs.ae
SUMMARY:Exploring the World Through ArcGIS: Imagery\, GeoAI\, and Reality Mapping
DESCRIPTION:Discover how imagery can become a powerful source of insight with ArcGIS. \nIn this workshop\, you’ll explore how to access\, manage\, visualize\, and analyze a wide range of imagery\, including satellite\, aerial\, drone\, elevation\, and raster data. You’ll see how ArcGIS brings these different imagery sources together and turns them into useful information for mapping\, monitoring\, analysis\, and decision making. You’ll also explore advanced imagery analysis\, GeoAI\, and Reality Mapping\, and learn how imagery can be transformed into accurate 2D and 3D products. Through hands on exercises\, you’ll put these capabilities into practice by managing imagery in ArcGIS Pro and applying an imagery analysis workflow to identify change and extract meaningful information from real world data.
URL:https://esgrs.ae/wevent/exploring-the-world-through-arcgis-imagery-geoai-and-reality-mapping/
LOCATION:Mohammed Bin Rashid Space Centre
CATEGORIES:Workshops
ATTACH;FMTTYPE=image/jpeg:https://esgrs.ae/wp-content/uploads/2026/09/sat-img-area-green.jpg
END:VEVENT
END:VCALENDAR