Navigating Sea Level Change: Harnessing GIS Techniques and Game Engines for Modeling and Analysis
2024-03-20 10:00 - 11:00 (Asia/Dubai) | Virtual
This webinar will offer insights on the power of GIS combined with game engines to foresee the impact of sea level rise on a city. A prototype developed with Unity will be presented to address this challenge.

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PROF. KHAULA ALKAABIAssociate ProfessorDr. Khaula Alkaabi is Associate Professor at Geography & Urban Sustainability Department, UAEU. She holds a BA degree from UAEU; a MA & a PhD in Geography from UNCG, USA; & Public Sector Innovation Diploma, University of Cambridge, UK. Her research interests: transportation, land use planning, spatial analysis, GIS, drone applications, economic geography, smart cities, entrepreneurship, & innovation. She served as Chair of Geography Department 2013- 2017, & Chief Innovation Officer 2015-2022.

DR. JUSTINE SARRAUJustine Sarrau holds a Bachelor’s degree in Geography, Urban Planning, and Environment from Université Toulouse Jean Jaurès, Toulouse, France, followed by a Master’s degree in Earth Observation and Geomatics from UNISTRA, Strasbourg, France. Currently pursuing a PhD in GIS (Geographic Information Systems) at UAEU.

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Remote Sensing to Understand Crop Health for Precision Agriculture
2024-05-22 10:00 - 11:00
Join us for a comprehensive webinar on leveraging remote sensing technologies to enhance crop health monitoring and management in precision agriculture. Precision agriculture is a farming management concept that utilizes technology to optimize crop yields and reduce waste. In this webinar, we will delve into the core concepts of precision agriculture and explore how remote sensing plays a crucial role in this field. Discover how to use the ENVI CropScience analysis tool for precise monitoring and analysis of crop health indicators, such as vegetation health. Learn about the significance of hyperspectral data in precision agriculture and how to analyze plot-level hyperspectral drone images for enhanced crop health assessment. Gain insights into calculating vegetation indices, such as NDVI (Normalized Difference Vegetation Index) and EVI (Enhanced Vegetation Index), using hyperspectral data for accurate crop health monitoring. This webinar is ideal for professionals and researchers in the fields of agriculture, remote sensing, and environmental science who are interested in advancing their knowledge of precision agriculture and remote sensing applications in crop health monitoring. Don’t miss this opportunity to deepen your understanding of precision agriculture and remote sensing technologies. Join us to unlock the potential of remote sensing in revolutionizing crop health management for a sustainable future.

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DR. SURYA DEB CHAKRABORTYSENIOR ANALYSTDr. Surya Deb Chakraborty is part of ESRI India and works as a senior analyst. Before joining ESRI India, he worked in many organizations like ICRISAT (International Crops Research Institute for the Semi-Arid Tropics) under the UN, the National Remote Sensing Center (NRSC, ISRO), MNCFC (Mahalanobis National Crop Forecast Centre), Regional Remote Sensing Center (ISRO) and IISC-ISRO space technology cell. He completed his PhD in geo-engineering from the National Remote Sensing Centre (NRSC, ISRO) at Andhra University and his M.Tech from the Indian Institute of Remote Sensing (IIRS, ISRO). He also completed his M.Sc. in geography from CSJM University Kanpur and a diploma in RS and GIS from Jadavpur University. In 2015, he received a Young Scientist fellowship award from KIT, Germany. His area of interest is urban anthropogenic heat flux estimation, watershed management, and agriculture applications using optical and microwave data. He primarily handles advanced remote sensing data processing, such as thermal, hyperspectral, LiDAR, and microwave.

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Coral Reef Early Warning System for Small Island Developing States (SIDS)
2024-06-12 10:00 - 11:00
Small Island Developing States (SIDS) face significant challenges from natural disasters, climate change, and limited resources, particularly the degradation of coral reefs due to rising sea temperatures. To combat this, 4EI has developed a Coral Reef Early Warning System for the Maldives, utilising remote sensing and community engagement to monitor water quality and coral cover. The system establishes a baseline assessment of coral reefs, tracks changes over time, and identifies early warning indicators of threats like coral bleaching. Outputs include monthly reports with updated reef maps and bleaching risk alerts. This system enhances climate resilience, supports marine ecosystems, boosts tourism, and protects coastlines, while fostering community involvement in conservation efforts.

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MR. JAVIER GARCIA LOPEZGeneral Manager at 4 Earth IntelligenceJavier is an experienced Project Manager with over a decade of experience in Remote Sensing. He adeptly handles both small and large-scale international projects, specialising in Remote Sensing, photogrammetry, and cartography. Javier has significantly contributed to the growth of remote sensing production and has developed new land products for emerging markets. His involvement in research and development focuses on improving methodologies, workflows, and software to enhance processes and workforce planning. Javier’s expertise spans various environmental and geospatial projects, and he is also skilled in capacity building and conducting workshops. His diverse skills and commitment to environmental stewardship make him a valuable asset in geospatial and environmental sciences.

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Building a Loss and Damage Atlas Driven by Satellite Data for Climate Resilience
2024-07-17 10:00 - 11:00
In efforts to bolster resilience against the impacts of climate change, the UAE Space Agency, in partnership with Planet Labs, has launched a project to construct an innovative loss and damage atlas driven by satellite data. The project aims to extend technology and expertise to developing countries, helping them tackle the loss and damage resulting from climate change and facilitate the establishment of early-warning systems.
Through this webinar, you will learn more about the UAE Space Agency’s vision to support transformative initiatives and projects aimed at combating climate change. Project participants will present their developed case studies on the Maldives. This will be followed by a presentation from Planet Labs, showcasing their platform and analytics. Finally, attendees will have the opportunity to participate in the project, leveraging Planet’s imagery and analytical models.

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REGISTER FOR LOSS AND DAMAGE ATLAS FOR CLIMATE RESILIENCE PROJECT

Mr. Adel YousefiDeveloper and Researcher at FarminDeveloper and researcher with expertise in advanced technologies, AI, and software development. Focused on creating innovative solutions and enhancing system efficiency.

Mrs. Soma MukherjeeGIS-Software Developer at BayanatSoma has experience in the geospatial domain for a span of 15 years, working with different reputed entities both within UAE as well as outside of UAE. During her work tenure ,she has been involved in the complete lifecycle of development of the GIS applications, project management and business acquisition activities. During the development phase of the Geospatial Analytics Platform (GIQ) , she was assigned as the Project Manager.

Luisa TeixeiraStrategic Programs Manager at Planet LabsLuisa Teixeira is a Program Manager, currently leading Planet’s contribution to several strategic Programs such as the UAE Space Agency Loss and Damage Atlas and the NICFI Satellite Data Program. Luisa has over 10 years of experience working with stakeholders from government, business and civil society to support them in making the best possible use of data and digital tools, with a focus on climate action and biodiversity conservation.

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Soil Moisture Mapping Using L-band Microwave Radiometry and GNSS-R, and Disaggregation Algorithms for High Resolution Applications
2024-11-07 11:00 - 12:00
Soil moisture is a critical parameter influencing various environmental processes, agricultural productivity, and hydrological modeling. Traditional methods of soil moisture measurement often suffer from limitations in spatial resolution and temporal frequency. In this talk, these challenges will be addressed by leveraging the unique capabilities ofmicrowave radiometry and GNSS-R from space.
The talk begins with an overview of L-band microwave radiometry, which captures thermal emissions from the soil, and GNSS-R, a remote sensing technique that utilizes signals from global navigation satellites to infer soil moisture content based on reflected signals from the earth’s surface. Some of these instruments (ground-based to spaceborne) developed at the Universitat Politècnica de Catalunya-BarcelonaTech (Spain) are presented.
Then, the application of disaggregation algorithms is described. These algorithms play a pivotal role in enhancing the spatial resolution of soil moisture estimates derived from coarser resolution satellite data. By means of machine learning techniques and high-resolution auxiliary datasets, the algorithms effectively downscale the soil moisture information, enabling a more precise mapping of the soil conditions across diverse landscapes.
These findings show the potential for operational applications in agriculture, where timely and precise soil moisture information can inform irrigation practices and crop management strategies, and in climate and environmental monitoring where enhanced soil moisture data can support better predictions of drought conditions and flood risks. In a future, these high-resolution soil moisture maps could be routinely utilized in decision-making processes, ultimately contributing to better water management and improved resilience against climate change.

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Prof. Adriano CampsProfessor at CommSensLab-UPC, Dept. of Signal Theory and Communications, Universitat Politècnica de Catalunya, SpainProf. Adriano Camps joined the Dept. of Signal Theory and Communications, Universitat Politècnica de Catalunya (UPC), as an Assistant Professor in 1993, Associate Professor in 1997, and Full Professor since 2007. In 1999, he was on sabbatical leave at the Microwave Remote Sensing Lab., of the Univ. of Massachusetts, Amherst. Since September 2022 he has been an ASPIRE Visiting International Professor at the UAE University, Al Ain, Abu Dhabi. His research interests are focused on: 1) microwave remote sensing, with special emphasis on microwave radiometry by aperture synthesis (Ph.D. Thesis about the MIRAS instrument, which became the single payload of ESA’s SMOS mission), 2) remote sensing using signals of opportunity (GNSS-R), 3) radio frequency interference detection and mitigation, 4) ionospheric propagation, and 5) nanosatellites as a tool to test innovative remote sensors. His publication record includes over 284 papers in peer-reviewed journals, 12 book chapters, and the book Emery and Camps, “Introduction to Satellite Remote Sensing. Atmosphere, Ocean, Land and Cryosphere Applications,” Elsevier, 2017 (860 pages), and more than 558 conference presentations. According to Google Scholar/Scopus, his h-index is 64/52, and his publications have received more than 16.869/11.758 citations. According to the October 2023 Stanford ranking, he is among the top 2% of researchers.

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Rapid Flood Inundation Mapping and Flood Shelter Suitability Analysis in Bangladesh
2024-11-14 10:00 - 11:00
Floods are frequent natural hazards that produce an unusual water overflow that submerges a large area, affecting the frontline communities, their livelihood, environmental vulnerability, and increasing social and economic consequences. In the past few decades, average flood frequency, intensity, and duration have increased, seriously impacting low-lying countries. Knowing the areas inundated by floods is essential to mitigate the effects of the disaster. With timely flood information and early warnings, agencies and organisations involved in disaster management can speed up emergency response for relief and rescue measures. Rapid flood maps provide crucial inputs for assessing the extent of inundation areas and flood severity. In this masterclass, we will demonstrate a reproducible and automated method based on Google Earth Engine (GEE) to generate rapid flood magnitude data nationally. The seminar will enable the timely production of GIS and remote sensing data layers, along with the procedure of identifying suitable locations for flood shelters, enhancing disaster preparedness in Bangladesh.

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Mr. Kabir UddinGIS and Remote Sensing Specialist at International Centre for Integrated Mountain DevelopmentMr. Kabir Uddin has eighteen years of professional experience at the International Centre for Integrated Mountain Development (ICIMOD), Nepal, leading GIS and Remote Sensing environmental management. As a GIS and Remote Sensing Specialist at ICIMOD, he supervises and coordinates various aspects of GIS and remote sensing work. He is experienced in preparing a wide range of training manuals on mapping land cover, glaciers, flood hazards, and the suitability of flood shelters. He also conducts professional training in the Hindu Kush-Himalayan (HKH) countries. Mr. Kabir analyses optical and radar remote sensing data during flood disaster events for rapid flood inundation mapping and damage assessment systems. He works as a land cover thematic lead for SERVIR-HKH (a USAID-NASA Partnership), Land Cover and Ecosystem Services at ICIMOD to build the Regional Land Cover Monitoring System in close collaboration with various national and international organisations to generate consistent land cover maps on an annual basis. In addition, Mr. Kabir regularly publishes articles in peer-reviewed journals. Before joining ICIMOD, he worked as a GIS Expert at the Local Government Engineering Department (LGED), Bangladesh.

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The Role of GNSS Satellites in Natural Hazards Monitoring
2025-01-21 10:00 - 11:00
Global Navigation Satellite System has emerged as more beneficial in monitoring the Earth’s atmosphere for natural hazards and space weather events around the globe with high-resolution datasets from ground and space-based measurements. Besides PNT solutions, it is nowadays used for natural hazards monitoring namely, earthquakes, tsunamis, typhoons, volcanoes, Solar storms, etc. After the inclusion of more satellite constellations from different countries, accuracy and precision improved significantly. It is also used as in-situ observables for other remote sensing satellites at different altitudes over the Earth.

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Dr. Munawar ShahProfessor at Institute of Space TechnologyDr. Munawar Shah is a Professor at the Institute of Space Technology, Islamabad, Pakistan. He held postdocs from KMITL, Chumphon Thailand, and Tongji University, China. He got his PhD in Geodesy from Shanghai Astronomical Observatory in 2017. He has published more than 100 peer-reviewed papers with more than 1500 citations in reputed journals and participated in several conferences for paper presentations at national and international levels. He successfully did the convenership of the EGU and Vice Chair of IAG-GGOS-FWG-JSG1 with an excellent young researcher award from COSPAR for publishing a paper in Advances in Space Research. Besides this, he is a reviewer of Scientific Reports, JGR, GJI, AISR, Remote Sensing, etc. He has successfully supervised more than 30 Master’s students and 10 more students are currently working under his supervision. He is also the editor of Discover Geoscience and other special issues.

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Advances in Remote Sensing and Artificial Intelligence in Marine and Coastal Studies
2025-01-29 10:00 - 11:00
This webinar will reveal the significance of applications for advances in remote sensing and artificial intelligence in marine and coastal studies. The webinar will demonstrate programming integration with the RS and AI disciplines, including cloud computing (GEE), generative ML models, open-source libraries, and more elements. The speaker will present high-level illustrations of real-world instances from their profession. The webinar will emphasize that AI has the potential to transform the methods by which we gather, analyze, and interpret data from vast and intricate oceans. AI oceanography has shown its efficacy in addressing many maritime challenges, including monitoring marine ecosystems and environmental conditions, as well as forecasting ocean currents and meteorological patterns. Simultaneously, driven by the ongoing advancement of remote sensing technologies in recent decades, ocean observation has transitioned into the big data age. Many ocean satellites outfitted with extensive sensors have been launched to observe oceans from both large and high-resolution perspectives.
Integrating AI with remote sensing has unleashed significant potential in addressing remote sensing retrieval, feature and pattern identification, and reconstruction challenges. Aggregated data may discern the fundamental principles of concealed connection, enhancing our understanding of the oceans and facilitating more efficient conservation and management initiatives. Combining these with other ocean data, like numerical models and reanalysis, might dramatically reduce current oceanography problems. This would create a new data-driven paradigm in ocean remote sensing.
This webinar’s primary objective is to provide a scientific forum to discuss the latest AI application developments in ocean remote sensing.

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Dr. Ismail MondalFaculty at Dept. of Marine Science, University of CalcuttaDr. Ismail Mondal is a Faculty in the Dept. of Marine Science, University of Calcutta, Kolkata-700019, India. He is a Remote Sensing and GIS specialist who has experience in environmental modeling in different applications, i.e., Climate Change in UN Sustainable Gol’s in Sea Level Rise in Marine Physical, Biological, and Chemical Modelling (Storm Surge and Coastal Vulnerability), SLAMM, Forest Ecology, Carbon Sequestration (Blue Carbon) of Biomass estimation, Aerosol Dynamic and Air Quality, Agriculture, Soil, Coastal and Estuarine modeling using Remote Sensing and GIS techniques. Moreover, He has an excellent working knowledge of tools like Remote Sensing, Digital Image Processing, Geographical Information Systems, Spatial data analysis, Programming Language, and statistical analysis (Google Earth Engine, Matlab, Python, etc.).

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Contemporary RS/GIS Skills Needed to Accommodate the Changing Geospatial Technologies
2025-02-12 11:00 - 12:00
This webinar focuses on the evolving geospatial landscape, aiming to equip GIS researchers and practitioners with essential skills to adapt effectively. By providing a guiding framework, that will help participants confidently navigate advancements, embrace innovation, and stay on course in the dynamic fields of geoinformatics.

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Dr. Anwarelsadat Eltayeb ElmahalSenior RS/GIS Lecturer at University of KhartoumHe is a Sudanese specialist and a senior lecturer in remote sensing, GIS, data science, and their applications in geoscience. With approximately +10 years of expertise in the academic field, teaching a variety of graduate and undergraduate courses. These courses covered subjects such as remote sensing and GIS applications in hydrology, hydrogeomorphology, web-GIS, satellite digital image processing, geostatistics, spatial databases, spatial cloud computing, and research methodologies. With +15 years’ experience in UN and international organizations, such as UNICEF, FAO, and the European Commission, as a specialist in information management and GIS and backed by a solid geoscience, data science, and visualization experience. Member of the British Society for Geomorphology and active participant in the society’s annual meetings in the UK. With strong knowledge and interest in spatial cloud computing, land use, land cover change, and environmental risk mapping using Google Earth Engine with native [JavaScript, Python] and non-native [RGEE] APIs. With many publications in the field that could be accessed through his Google Scholar profile.

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Turning Earth Observations to Natural Language Dialogues
2025-02-26 10:00 - 11:00
This talk covers the integration of recent GenAI technologies (Large Language Models) for earth observation and climate data. We will cover models developed by MBZUAI and its collaborators in recent years for improved analysis of GeoSpatial data using natural language conversations. These models can process multisensory inputs i.e., RGB, SAR, Mult-spectral and Temporal sequences and allow additional capabilities such as visual grounding and change detection. The talk will also cover applications of these models to specific use cases, e.g., damage assessment due to extreme weather events and tracking urban heat-island phenomena.

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Dr. Salman KhanAssociate Professor at Mohamed Bin Zayed University of Artificial IntelligenceDr. Salman Khan is an Associate Professor at Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI) and an honorary faculty member at the Australian National University (ANU). He works on multimodal learning algorithms for various applications, with a specific focus on earth observation and climate science. He has been a recipient of several prestigious scholarships, including Fulbright and IPRS, and served as a program committee member for several premier conferences where he has won multiple outstanding reviewer awards. He was the guest editor for IEEE TPAMI, MDPI Remote Sensing and acts as area chair for premier AI conferences such as NeurIPS, CVPR, ICML and ICCV. He, alongside his collaborators and students, won the best paper award in ICPRAM 2020, best paper honorable mention at ACCV 2024 and top ranks in CVPR-NTIRE 2019 and 2021 challenges on image enhancement. He has published over 100+ technical papers in top AI journals and conferences.

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Drones: Innovating Air Pollution and Climate Research
2025-03-05 10:00 - 11:00
Drones are transforming air pollution and climate research by providing real-time, high-resolution data from inaccessible areas and providing vertical information within the atmospheric boundary layer. Using remote sensing technology with sensors such as aerosol spectrometers, LiDAR, and gas analyzers, they measure pollutants, greenhouse gases, and atmospheric conditions. Their flexibility, cost-effectiveness, and ability to operate in hazardous environments make them invaluable for monitoring air quality, improving climate models, and informing policy.

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Dr. Ajit AhlawatAssistant Professor at Delft University of Technology - NetherlandsDr. Ajit is currently working as an Assistant Professor in the Department of Geoscience and Remote Sensing under the Faculty of Civil Engineering at Delft University of Technology (TU Delft), The Netherlands. He completed his Ph.D. from CSIR-National Physical Laboratory, India in the field of aerosol instrumentation in 2019. He then worked as a scientist at Leibniz Institute for Tropospheric Research (TROPOS), Germany for almost 6 years, where he contributed to the advancement of air pollution monitoring through ground-based and drone-based field campaigns. He has coordinated several projects on air pollution monitoring and atmospheric aerosol research. He has published 30 research papers in various prestigious international journals.

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Geographic Information Systems (GIS) and Remote Sensing for Renewable Energy Applications
2025-03-26 10:00 - 11:00
This webinar explores the application of Geographic Information Systems (GIS) and Remote Sensing in the field of renewable energy. The session will begin with an introduction to GIS and Remote Sensing, highlighting their importance in renewable energy planning, development, and management.
The presentation will cover key applications, including:
Solar Energy Applications – Resource assessment, site selection, and solar potential mapping.
Wind Energy Applications – Wind resource analysis, optimal site identification, and integration with GIS tools.
Hydropower and Marine Energy – Hydrological mapping, tidal and wave energy assessment, and remote sensing applications for water resource management.
Biomass and Bioenergy – Land-use analysis, biomass resource mapping, and sustainability evaluation.
Additionally, the webinar will discuss:
GIS and Remote Sensing for Climate Change and Environmental Monitoring – Tracking environmental changes, assessing renewable energy impacts, and supporting sustainability initiatives.
Smart Grids and Energy Planning – Enhancing grid optimization, demand forecasting, and strategic energy infrastructure development through GIS integration.
The session will also feature case studies and real-world applications, showcasing successful implementations of GIS and Remote Sensing in renewable energy projects.
Finally, the webinar will conclude with an exploration of future trends and challenges, highlighting emerging technologies, data integration advancements, and the evolving role of GIS and Remote Sensing in shaping a sustainable energy future.

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Prof. Abdul Ghani OlabiDirector of Sustainable Energy & Power Systems Research Centre at University of SharjahProf. Abdul Ghani Olabi serves as the Director of the Sustainable Energy and Power Systems Research Centre at the University of Sharjah, UAE. He holds both an M.Eng. and a Ph.D. from Dublin City University, Ireland, and has held academic and research positions at prestigious institutions, including the National Research Council of Italy, the FIAT Research Centre in Italy, Dublin City University, and the Institute of Engineering and Energy Technologies at the University of the West of Scotland (UWS). Prof. Olabi is the founder of two renowned international conferences: the International Conference on Sustainable Energy and Environmental Protection (SEEP) and the International Conference on Materials Science and Smart Materials (MSSM). In addition to his contributions to academia, he plays a pivotal role in academic publishing, serving as Editor-in-Chief of the Encyclopedia of the Renewable Energy (Elsevier), the Encyclopedia of Green Materials (Elsevier), and the Encyclopedia of Smart Materials (Elsevier). He is also the Editor of the Reference Module in Materials Science and Engineering (Elsevier). Prof. Olabi and his team have made significant contributions to renewable energy and energy storage systems through innovative research projects. They have been granted numerous patents in areas such as hydrogen production, advanced PEM fuel cells, and the development of innovative supercapacitors and batteries.

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Research at the intersection of satellite-based InSAR – geotechnical engineering and ML
2025-04-23 10:00 - 11:00
The webinar will focus on Dr. Maral’s research at the intersection of Earth Observation (satellite InSAR), machine learning, and geotechnical engineering for monitoring critical infrastructure like tailings dams. Additionally, it will explore cutting-edge EO and ML research in other applications such as agriculture and sustainable finance.
Dr. Maral is a researcher at the Department of Engineering Science, University of Oxford. Her research is on using EO/ML for infrastructure monitoring, and have received an award in the category for Data Science and AI at COP28 from the Prototypes for humanity, an Industrial Fellowship from the UK’s 1851 Royal Commission and a Keeley Senior Scholar of Wadham College, University of Oxford. She is also a senior EO consultant the Satellite Applications Catapult for the last 8 years, previously Remote Sensing Analyst at Airbus Defense and Space. Maral is alos the co-chair for the Technology Exploration Interest Group of Committee on Earth Observation Satellites, which is the main international coordination body for civic space.

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Dr. Maral BayaraaResearcher at University of OxfordCurrently DPhil researcher at the Department of Engineering Science, University of Oxford. My research is on using EO/ML for infrastructure monitoring, and have received an award in the category for Data Science and AI at COP28 from the Prototypes for humanity, an Industrial Fellowship from the UK’s 1851 Royal Commission and a Keeley Senior Scholar of Wadham College, University of Oxford. I am also a senior EO consultant the Satellite Applications Catapult for the last 7 years, previously Remote Sensing Analyst at Airbus Defence and Space. I am also the co-chair for the Technology Exploration Interest Group of Committee on Earth Observation Satellites, which is the main international coordination body for civic space.

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Leveraging AI and Remote Sensing (Optical, Radar, LiDAR, and UAV) to Address Environmental and Ecosystem Challenges
2025-04-30 09:00 - 10:00
This webinar will present a decade of pioneering research from Salehi-Geolab, culminating in over 70 journal publications and nearly 100 presentations at esteemed international conferences. The focus of the webinar is to explore the integration of machine learning and computer vision techniques with remote sensing data, aiming to enhance our understanding of ecosystem dynamics influenced by human activity and climate change across urban, state, and national scales.
We will showcase our advancements in monitoring key ecosystems such as wetlands, forests, inland waters, and urban forestry, utilizing cutting-edge machine learning methodologies and big data analytics. Key highlights will include our national wetland classification initiative in Canada, utilizing SAR and multispectral imagery, alongside forest height and aboveground biomass estimation for the northeastern United States through space-borne LiDAR, SAR, and optical data, integrated with deep learning models. Additionally, we will present our innovative work in water quality monitoring, leveraging data from UAVs, field sensors, and satellites. The webinar will also feature our deep learning framework for the automatic 3D modeling of individual trees in urban and forest environments, which includes the detection and parameter estimation (e.g., volume, crown area, height, and biomass) using UAV LiDAR and photogrammetry.
Through this session, we aim to provide insights into the transformative potential of advanced remote sensing technologies and machine learning in environmental monitoring and management.

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Dr. Bahram SalehiAssociate Professor of Remote Sensing Engineering and Graduate Students Coordinator at State University of New York College of Environmental Science and ForestryDr. Bahram Salehi is Associate Professor of Remote Sensing Engineering and graduate student’s coordinator at the State University of New York College of Environmental Science and Forestry (ESF). He holds a PhD in Geomatics Engineering – Remote Sensing from the University of New Brunswick, Canada (2012). With over 20 years of academic and industrial experience, Dr. Salehi is a globally recognized expert in remote sensing, specializing in artificial intelligence (AI) and machine learning for processing multispectral, radar, lidar, and UAV data to monitor environmental changes at regional and national levels. He is internationally recognized for his pioneering work in remote sensing of wetlands, including the development of high-resolution nationwide wetland inventory of Canada (2022). His current research focuses on ecosystem and environmental changes, particularly in forests biomass, urban trees, and water quality, leveraging AI and multisensor remote sensing technologies. Dr. Salehi has co-authored more than 70 peer-reviewed journal publications, with over 6,400 citations and an h-index of 37 as of March 2025. He has mentored, as the principal advisor, 15 graduate students, including 10 PhD and 4 MS students and a postdoctoral fellow, and has extensive teaching experience in Geomatics Engineering and Remote Sensing across universities in Canada and the U.S.

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International Collaboration of Satellite Application in Disaster Management: Sentinel Asia and International Disaster Charter
2025-05-07 10:00 - 11:00
There has been more than 20 years of history in international collaboration, applying satellite imagery to disaster management. Sentinel Asia is a community consisting of satellite data providers, data analyzers and disaster management organizations in Asian Pacific region. Similarly, International Disaster Charter provides satellite data from various countries in the world. The webinar first introduces Sentinel Asia and International Disaster Charter and how they work. Then there will be examples of analyzed products for various disasters such as floods, earthquakes, volcano eruptions, etc. Later, there will be a presentation of other activities such as user meetings, capacity building, and promoting activities to maintain sustainable and active engagement with disaster management community.

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Mr. Goro TakeiAssociate Senior Engineer, Deputy Executive Secretariat of Sentinel Asia, Board Member of International Disaster Charter - Japan Aerospace Exploration Agency (JAXA)Goro Takei joined the National Aerospace Development Agency: NASDA (Former organization of Japan Aerospace Exploration Agency: JAXA) in 2001. He has more than 20 years of experience in design, development, integration, test, operation and application of earth observation satellites with optical sensors and synthetic aperture radar sensors (SAR). His current duty is to provide satellite data of area affected by natural hazards to Disaster Management Organizations, when emergency observation is requested by member organizations of Sentinel Asia and International Disaster Charter. He is the deputy executive secretariat and technical lead of Sentinel Asia and the board member of the International Disaster Charter, promoting utilization of space related assets in the international disaster management community.

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The Role of Geospatial Databases in Enterprise GIS Systems
2025-05-21 09:00 - 10:00
This session explores the foundational role of geospatial databases in the architecture of modern Enterprise GIS systems. It highlights how spatial data storage, management, and integration drive efficiency, scalability, and cross-system interoperability. The session will cover key concepts such as database schema design, spatial indexing, and multi-user access models, along with real-world implementation examples using MSSQL, Oracle, and PostgreSQL/PostGIS.

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Mr. Mostafa EssamGeospatial Solutions Expert at SETS International For Engineering ConsultancyHe is GIS and Remote Sensing professional with over 17 years of experience delivering geospatial solutions across government and enterprise sectors in the Middle East and North Africa. His expertise spans spatial data infrastructure (SDI), remote sensing analytics, and enterprise GIS implementation using platforms like ESRI, Hexagon, and open-source technologies. He has led and contributed to strategic projects in Saudi Arabia, Egypt, and the UAE, including traffic monitoring systems, violation detection through AI-integrated satellite imagery, and national GIS transformations. Mostafa is highly experienced in satellite data processing, change detection, feature extraction, and AI-based image classification.

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Understanding the Role of Anthropogenic Heat in Shaping Urban Heat Islands and Groundwater Response Through Remote Sensing
2025-06-25 10:00 - 11:00
This lecture focuses on the growing impact of anthropogenic heat in urban areas and its role in intensifying urban heat islands and altering groundwater temperature patterns. Through the use of remote sensing—particularly thermal and optical satellite imagery—we will explore how land use changes and increased impervious surfaces contribute to rising surface and subsurface temperatures. The session emphasizes the relevance of geospatial analysis for understanding urban climate dynamics and supports sustainable urban planning and water resource management.

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Dr. Surya Deb ChakrabortyMBRSC LabDr. Surya Deb Chakraborty is an accomplished Analyst at the MBRSC Lab, University of Dubai. With an impressive 14 years of experience in the field of remote sensing and GIS, Dr. Chakraborty has contributed significantly to various prestigious organizations, including ESRI, ICRISAT (under the UN), NRSC (ISRO), MNCFC, Regional Remote Sensing Centre (ISRO), and IISc-ISRO Space Technology Cell. Dr. Chakraborty has a proven track record in geospatial training, having conducted 400 specialized sessions on ArcGIS Desktop, ArcGIS Pro, ENVI, SARscape, and SNAP for government agencies, private enterprises, and academic institutions. His training expertise extends to diverse groups, from small teams of three to large batches of up to 80 participants. Academic Credentials: Ph.D. in Geo-Engineering – NRSC (ISRO), Andhra University M.Tech in Remote Sensing & GIS – Indian Institute of Remote Sensing (IIRS, ISRO) M.Sc. in Geography – CSJM University, Kanpur Diploma in Remote Sensing & GIS – Jadavpur University Achievements & Research Focus: Recipient of the Young Scientist Fellowship Award – KIT, Germany (2015) Specializes in urban anthropogenic heat flux estimation, watershed management, and agricultural applications using optical and microwave data Expert in advanced remote sensing data processing, including Thermal, Hyperspectral, LiDAR, and Microwave data analysis Dr. Chakraborty is deeply passionate about leveraging geospatial technology to solve real-world challenges and is dedicated to ongoing research and collaboration in the field. His expertise and contributions continue to make a significant impact in remote sensing and GIS applications.

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How AI Enriches Remote Sensing Data Analysis in Urban Areas Insights on: Datasets, Strategies and Application
2025-07-30 11:00 - 12:00
Urban areas are under increasing pressure due to the economic, social, and environmental domains since the extraordinary rise in global urbanization, which is predicted to reach roughly 70% by 2050. The rapid pace of urbanization calls for intensive studies on mapping urban growth, assessing infrastructure, managing water resources, and monitoring natural land cover. The Urban environment, however, presents one of the most challenging research fields for remote sensing data analysis tasks due to the complexity of urban landscapes, the wide range of land cover materials, and the variety of land use classes. To address the challenges related metropolitan settings, recent Earth observation satellites provide a wide range of valuable spatial and quantitative information, large geographic coverage, and real-time monitoring. About one thousand Earth Observation (EO) satellites are in orbits, according to Union of Concerned Scientists (UCS), offering various multimodal remote sensing data including Multi/ Hyper-Spectral (MS/HS) images, Digital Surface Models (DSMs), and LiDAR point clouds. It is more challenging to accurately classify urban land cover and pinpoint particular features when multimodal data is interpreted using traditional methods. The integration of remote sensing techniques and Artificial Intelligence (AI) approaches provide affordable tools for gathering and analyzing large amounts of data in comparison to resource-intensive traditional scenarios like human based surveying and field observation. AI enhances data processing accuracy and efficiency, providing valuable information for urban development, infrastructure management, and environmental surveillance. AI tools interpret remote sensing data employing cutting-edge Neural Networks (NNs) to identify relevant land use and land cover characteristics and over-come human development challenges. The webinar explores the effectiveness of AI strategies especially neural networks (e.g., CNN, DNN, SNN, KAN) for remote sensing dataset analysis in urban areas and exploring their applications.

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Mohamed FawzyPh.D. Researcher/Teaching Assistant at Budapest University of Technology and EconomicsA Ph.D. researcher investigating AI, photogrammetry, remote sensing, and Earth observation. Recently, I am focusing on developing innovative solutions for Earth tracking activities leveraging recent AI strategies. I highly believe that the power of photogrammetry, remote sensing, image processing, and geospatial information systems are expected to be the next issue in of interest for the world. Their applications have received much interest in human development since their function is extremely related to the analysis of built-up areas, infrastructural networks, water resource monitoring, climate change effects, and disaster management.

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Remote Sensing & GIS for Smart Cities: Insights, Innovation, and Impact
2025-09-03 10:00 - 11:00
This webinar explores the critical role of geospatial technologies in building and managing smart cities. Participants will gain insights into how GIS, photogrammetry, remote sensing, and AI are leveraged to capture, assess, and analyze urban data in real-time. Through practical examples and use cases, the session will demonstrate how these technologies support data-driven urban planning, infrastructure monitoring, environmental assessment, and decision-making. Join us to discover how geospatial intelligence transforms raw data into actionable solutions for smarter, more sustainable cities.

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Eng. Hussein M. AbdulmuttalibGIS Principal Specialist at GIS Center Department of Dubai MunicipalityHussein M. Abdulmuttalib is an MSc Civil Engineer, graduated from the Technical University of Budapest, with over 20 years of experience in geospatial analytics, remote sensing, photogrammetry, and smart city planning. He currently serves as a GIS Specialist at Dubai Municipality, where he also contributes to the management of GeoHub—the Municipality’s GIS innovation incubator.

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Climate Change impact on the formation of the Cyclogenesis process over the Arid and semi-arid regions of South Asia
2025-09-10 10:00 - 11:00
Climate change is altering atmospheric and oceanic patterns, significantly impacting cyclogenesis—the formation and development of tropical and extratropical cyclones. In arid and semi-arid regions of South Asia, such as parts of Pakistan, northwest India, and Afghanistan, traditionally not known for frequent cyclonic activity, shifts in temperature, and sea surface warming in adjacent oceans (e.g., Arabian Sea and Bay of Bengal). Changes in wind shear are making conditions more conducive to cyclone formation.
Rising sea surface temperatures due to global warming enhance evaporation and provide more energy for storm systems. Increased moisture availability and weakened vertical wind shear can allow cyclones to intensify more rapidly, and in some cases, form in regions that were previously considered unlikely. These changes pose new threats to dryland communities that are poorly equipped to handle such extreme events, raising concerns about infrastructure, water security, and disaster preparedness.
In summary, climate change is expanding the geographic range and intensity of cyclogenesis, increasing the vulnerability of arid and semi-arid regions in South Asia to extreme weather events.

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Dr. Ajoy DasCartographer at Gujarat UniversityDr. Ajoy Das has a keen interest in maps since he was an undergraduate student. He has a Bachelors in Geography with specialization in Pedology from The University of Burdwan, a Masters in Geography with specialization in Agricultural Geography from CSJM University, PGD in Geoinformatics with specialization in Water Resources Management from West Bengal University of Technology, MTech in GIS with specialization in Natural resources conservation and management through participatory approach from NIIT University, and a Ph.D. in Geography with specialization in Wetland biodiversity conservation and management from Gujarat University, India. He is currently working as a Cartographer at the Department of Earth Sciences, Gujarat University, and sharing best practices for mapping and analysis with modern GIS, Remote Sensing, and GNSS technologies. He publishes and presents worldwide on many aspects of mapping and GIS. His working areas are natural resources management, biodiversity conservation, Hydro-Geomorphology, terrain analysis, and spatio-temporal modeling, addressing critical and contemporary issues on climate change impact, Disaster risk resilience on Earth and its environment.

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Uncertainty-aware Urban Digital Twin based on Mobile Laser Scanning
2025-09-16 10:00 - 11:00
Mobile Laser Scanning (MLS) systems have become an indispensable solution that has reached a high level of popularization in various fields, for instance, digital twinning, smart cities, engineering geodesy, 3D modeling, autonomous driving, etc. Compared with the remarkable achievements of the MLS systems in efficient data acquisition and various scenario applications, the uncertainty evaluation and reduction has not followed the same trend, significantly lagging behind the development pace of current MLS systems. On the other hand, uncertainty-aware digital twinning remains an underexplored topic. This talk will present our latest work on modeling uncertainty in MLS point clouds and its application to building quality-assured urban digital twin.

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Mr. Ziyang XuResearch Associate and PhD Candidate - Chair of Engineering Geodesy, TUMMr. Ziyang Xu is currently a doctoral student at TUM Chair of Engineering Geodesy. Before, he graduated from Wuhan University in China, majored in Geodesy and Geomatics, and also worked in industry for 3 years, including IBM, Xiong’an New Area, and Zhejiang Academy of Surveying and Mapping. His main research interests are MLS quality control and improvement, uncertainty evaluation, and its application in digital twinning.

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Dust Storm Mapping and Monitoring in the Middle East using Remote Sensing Data and Google Earth Engine Platform
2025-09-23 10:00 - 11:00
This webinar will explore advanced techniques and tools for monitoring dust storms and aerosol distributions using remote sensing technologies. This session will cover a range of key topics aimed at enhancing your understanding of environmental monitoring through satellite data and machine learning.
Key topics include:

Remote Sensing products for dust storm monitoring
Aerosol mapping using Aerosol Optical Depth (AOD) products
Aerosol thickness mapping with PM2.5 concentration data
Dust storm occurrence mapping and monitoring
Analyzing dust storm trends using machine learning methods

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Dr. Amirhossein AhrariResearcher at University of OuluI have received bachelor’s and master’s degrees in Remote Sensing from the University of Tehran (Iran) between 2011 and 2018. As a remote sensing researcher, I worked at the Remote Sensing Research Center (RSRC) at Sharif University of Technology and FAO (Iran) between 2018 and 2020. Since then, I moved to Finland and started a PhD in Environmental Engineering, and received a PhD degree in 2025. My PhD thesis is entitled “Environmental Monitoring using Remote Sensing Data and Machine Learning”. I am skilled in remote sensing, artificial intelligence, and environmental engineering, and share my skills through my YouTube channel “Google Earth Engine with Amirhossein Ahrari”. Recently, I have received the Google Developer Expert title from the Google Earth Engine team at Google, which officially approved my skills. Currently working as a Researcher at the University of Oulu and collaborating on peer-reviewed papers that are already highlighted on my Google Scholar account.

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Geospatial Innovation in Action: Mobile Mapping, AI, and Digital Twins for Adaptive Decision Support
2025-10-08 10:00 - 11:00
Recent advances in mobile mapping systems have been driven by rapid improvements in sensor technology and platform integration, enabling the efficient capture of high-resolution, multi-modal geospatial data at unprecedented spatial and temporal scales. Coupled with developments in artificial intelligence and data analytics tools, these systems now facilitate automated feature extraction, pattern recognition, and predictive modeling from vast and complex geospatial datasets. As a result, there has been an explosion of potential applications across sectors seeking to leverage location-based intelligence, from natural resource management to infrastructure monitoring.
These technological trajectories converge in the creation of multi-resolution digital twins—virtual replicas of the physical environment that integrate heterogeneous geospatial data streams into coherent, scalable models. Digital twins provide a dynamic, data-rich foundation for decision support, enabling stakeholders to simulate scenarios, evaluate trade-offs, and optimize interventions. In digital forestry, they can enhance forest inventory precision, wildfire risk modeling, and ecosystem monitoring. For transportation asset management, digital twins offer continuous assessment of roadway and bridge conditions, improving maintenance planning and safety outcomes. In urban development, they guide sustainable planning, optimize land use, and evaluate the impacts of growth in real time. Along shorelines, digital twins enable fine-grained monitoring of erosion, flooding risks, and ecosystem health, supporting climate resilience strategies.
Together, the integration of mobile mapping innovations, AI-driven analytics, and digital twin frameworks heralds a new era of data-driven decision-making, where spatial intelligence informs more adaptive, efficient, and sustainable management of natural and built environments.

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Prof. Ayman F. HabibProfessor of Civil Engineering at Purdue UniversityAyman Habib is the Thomas A. Page Professor at the Lyles School of Civil Engineering at Purdue University. He is the Co-Director of the Civil Engineering Center for Applications of UAS for a Sustainable Environment (CE-CAUSE). He is also the Associate Director of Purdue University’s Joint Transportation Research Program (JTRP) and Institute of Digital Forestry (iDiF). He received the M.Sc. and Ph.D. degrees in photogrammetry from The Ohio State University, Columbus, OH, USA, in 1993 and 1994, respectively. His research interests include the fields of terrestrial and aerial mobile mapping systems using photogrammetric and LiDAR remote sensing modalities, UAV-based 3D mapping, and integration of multi-modal, multi-platform, and multi-temporal remote sensing data for applications in transportation, infrastructure monitoring, environmental protection, precision agriculture, digital forestry, resource management, and archeology.

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Hydro-geodesy of the Arabian Peninsula
2025-10-28 10:00 - 11:00
Hydro-geodesy is an interdisciplinary scientific discipline that employs geodetic methodologies, primarily satellite-based techniques, to investigate the dynamics of water movement and the resultant land surface oscillations. The Arabian Peninsula is classified as a water-scarce region, characterized by limited precipitation, elevated evaporation rates, and excessive groundwater extraction. Additionally, it is surrounded by oceanic bodies that exhibit both seasonal fluctuations and long-term secular trends. These hydrological motions induce variations in stress on the Earth’s crust, potentially leading to both short-term seasonal movements and long-term subsidence. Our recent research findings indicate that winter atmospheric loading also contributes significantly to the seasonal crustal movements. Such crustal deformations can pose significant challenges to the sustainability of human settlements and infrastructure. In the context of climate change, increasing water demand, and sea level rise scenarios, a comprehensive understanding of hydro-geodesy within the Arabian Peninsula becomes crucial. Such knowledge is instrumental in addressing regional hydrological and infra-structural issues and in fostering sustainable development trajectories. In my talk, I will present our research results based on Gravity Recovery and Climate Experiment (GRACE) and its Follow-On, Global Navigation Satellite System (GNSS), Non-Tidal Atmospheric Loading (NTAL), and satellite altimetry datasets, and discuss the groundwater decline rates, sea level variability, and the associated crustal movement in the Arabian Peninsula Region.

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Dr. Muhammad UsmanAssistant Professor at Zayed UniversityDr. Muhammad Usman completed his MS and PhD at Hokkaido University (Japan) with the Japanese Government’s MEXT Scholarship. He also has two years of postdoc research experience at the King Abdullah University of Science and Technology (KAUST), Saudi Arabia. He won the Outstanding Student Presentation Award (OSPA) at the Japan Geoscience Union-American Geophysical Union (JpGU-AUG) joint meeting of 2017 in Makuhari Messe, Chiba, Japan. He won first prize in the “Student Paper Contest” at the Annual Technical Conference (ATC) 2011, which was organized by the Pakistan Association of Petroleum Geoscientists (PAPG). He studies the water cycle, ocean dynamics, geodetic hazards, geomorphology, climate change, and different physical parameters of the environment using remote sensing data and field surveys. He mainly uses Synthetic Aperture Radar (SAR), Global Navigation Satellite System (GNSS), Gravity Recovery and Climate Experiment (GRACE) Satellite, Satellite Altimetry, and various climatic data; Python, MATLAB, and Generic Mapping Tool (GMT) products.

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Crop Yield Prediction as an Early Warning Tool for Drought and Food Security Disasters
2026-01-13 10:00 - 11:00
Timely and reliable crop yield prediction is a critical component of early warning systems for drought and food security disasters, particularly in climate-vulnerable regions such as Afghanistan. The country is highly exposed to extreme weather events, and winter wheat plays a central role in national food security. Accurately capturing the influence of irrigation on crop productivity is therefore essential for anticipatory food security planning.
In this study, we evaluate Earth Observation (EO) based yield prediction models for winter wheat in Afghanistan by distinguishing between irrigation-sensitive and irrigation-insensitive predictors. EO datasets were grouped accordingly, and an irrigated area mask was applied to isolate signals from irrigated croplands. To enhance model robustness and reduce noise from inter annual variability, a first-difference approach was applied to both yield and predictor time series. The irrigation-sensitive model incorporates vegetation indices and biophysical parameters (NDVI, LAI, and FAPAR) along with surface and root-zone soil moisture from GLEAM (Global Land Evaporation Amsterdam Model), while the irrigation-insensitive model relies on precipitation, reference evapotranspiration, aridity index, and soil moisture from FLDAS ( FEWS NET Land Data Assimilation System).
Winter wheat yields were predicted from January through May, revealing that forecasts generated in February and March, approximately four months before harvest, were the most accurate. The combined vegetation-and-precipitation model achieved the lowest prediction error (RMSE ≈ 0.30 mt/ha), outperforming models that relied solely on irrigation-sensitive or irrigation-insensitive predictors. Results demonstrate the potential of EO-driven yield forecasting as an effective early warning tool for drought and food security monitoring. By providing reliable seasonal yield estimates well ahead of harvest, such models can support proactive decision-making and targeted interventions in regions where irrigation plays a critical role in buffering climatic shocks.

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Dr. Barnali DasAssistant Professor at Kansas State UniversityBarnali Das is Assistant Professor of Geography and Director of Natural Resources and Environmental Sciences Secondary Major at Kansas State University. She received her bachelor’s degree in Geography from University of Calcutta in 2009. She earned her master’s degree in 2011 and doctorate in 2022, both in geography, from University of Pune. She has also Diploma in Remote Sensing and GIS from Indian Institute of Remote Sensing (IIRS), Indian Space Research Organisation (ISRO). Her PhD work won the Best Scientific Story Award in 2022, a national award across all scientific and technical fields organized by the Augmenting Writing Skills for Articulating Research (AWSAR) program of the Department of Science and Technology (DST). Dr. Das worked as Postdoctoral research scholar at Smithsonian Tropical Research Institute (STRI) in Panama and at University of California Santa Barbara (UCSB) before joining K-State in 2025. Her work focused on how climate change and shoreline dynamics affect mangroves in Central America as a postdoctoral researcher at the STRI. At UCSB her work utilizes earth observation products, remote sensing, satellite-derived biophysical parameters, and machine learning methods to understand how climate extremes affect crops in food insecure countries. Earlier in her career, she worked with the India Meteorological Department on the Forecasting Agricultural Output using Space, Agro-meteorology, and Land-based Observations (FASAL) project, where she applied geospatial and agro-meteorological approaches to operational crop yield forecasting.

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The Contribution of Satellite EO to Better Understanding Hazards and Disasters
2026-01-20 11:00 - 12:00
Satellite Earth Observation (EO) can be used to detect, identify and measure parameters relevant to disaster risk management. This can help in different phases including disaster response and recovery and in other phases such as risk prevention and mitigation. Modern EO missions providing high resolution and wide area mapping with systematic and global revisit, new information technologies have been applied to increase access to EO data and information. Regarding the immediate disaster response phase the International Charter Space & Major Disasters is providing rapid access at no cost to imagery from 240+ satellites and is reserved to a pre-defined list of users, the Authorized Users. Regarding risk assessment and prevention different initiatives have taken place to provide geoscience users and risk management experts with advanced systems and tools able to retrieve geoinformation concerning hazard and exposure including historical and up-to-date data from dedicated EO missions. The proposed lecture will explain and illustrate how these data and tools allow to better understand hazards and disasters.

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Eng. Philippe BallyEarth Observation Science & Application Engineer at European Space AgencyPhilippe Bally is a remote sensing expert working with the European Space Agency (ESA) in the Climate Action, Sustainability and Science Department of the Earth Observation Directorate. Graduated from an aerospace engineering Grande Ecole, Philippe worked with the French Space Agency (CNES) and joined Spot Image (France) in 1996 working on Earth Observation projects in Latin America and Asia in the fields of cartography and disaster risk management. He joined the ESRIN centre of ESA in 2000 and participates to the satellite Earth Observation (EO) programmes with focus on disaster risk management, humanitarian aid and international development. Philippe implemented large scale projects on advanced remote sensing such as the Geohazard Exploitation Platform for geoscience and a rapid mapping platform for disaster response using satellite imagery. He collaborates with the United Nations and Multilateral Development Banks. In 2022, he was appointed Board member of the International Charter ‘Space and Major Disasters’, an international collaboration for EO based disaster response.

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Advanced Oil Spill Trajectory Modelling for Environmental Protection
2026-02-04 10:00 - 11:00
Current oil spill emergency response protocols employ standardized, universal strategies that fail to account for critical environmental variations, particularly water temperature effects on oil weathering behaviour. This research addresses this operational gap through comparative analysis of two contrasting marine environments using integrated satellite remote sensing and GNOME (General NOAA Operational Modelling Environment) trajectory modelling.
The study examines the 1989 Exxon Valdez spill in Alaska’s cold waters (8°C, 257,000 barrels) and the 2017 Al-Khafji spill in the Arabian Gulf’s warm waters (40°C, 35,000 barrels). Satellite data from Landsat 5 TM and Sentinel-2 achieved 84-86% detection accuracy, validated through NOAA aerial surveys and multi-stage verification protocols.
Key findings reveal counterintuitive results: despite 32°C higher temperatures, the Arabian Gulf exhibited 24% lower evaporation (26.3%) compared to Alaska (34.8%) due to rapid emulsification processes that trapped volatile components. Alaska showed 7% shoreline beaching versus 0.5% in the Gulf, with dramatically different surface persistence patterns (57.9% vs 72.8%).

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Mr. Osman HamedFaculty of Engineering and Sciences at University of WolverhamptonOsman Hamed is a final-year PhD candidate in Environmental and Analytical Sciences at the University of Wolverhampton, UK, supervised by Professor Craig Williams, Dr. Catherine Duke, and Professor Abdallah Shanbleh. His research focuses on integrating satellite remote sensing (Landsat, Sentinel-2) with NOAA’s GNOME trajectory model for advanced oil spill monitoring and prediction. Osman’s doctoral work provides a comparative analysis of oil spill behaviour across contrasting marine environments—the 1989 Exxon Valdez spill in Alaska’s cold waters versus the 2017 Al-Khafji spill in the Arabian Gulf’s warm waters. His research demonstrates how environmental parameters, particularly water temperature, critically influence oil weathering processes and emergency response effectiveness.

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The Contribution of Satellite Data and Artificial Intelligence for Earthquake Response with damage mapping at building level
2026-02-17 10:00 - 11:00
The presentation will touch down on how earth observation data is currently used to detect building damages following an earthquake event. It will focus on the use of damage detection deep learning algorithms with very high resolution optical data, through the lens community challenge recently held by ESA phi-lab with the support of the International Charter: Space And Major Disasters.

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Eng. Mounia El BazEO Digital Innovation Engineer at ESAMounia El Baz received the Engineering degree in Applied Mathematics from École Centrale Paris (now CentraleSupélec) and the Master of Science in Mathematics, Computer Vision and Machine Learning from ENS Paris-Saclay, both part of Université Paris-Saclay. She was formerly a Senior Data Scientist at Descartes Underwriting, specializing in wildfire modeling, and is currently an EO Digital Innovation Innovation Engineer at the Φ-lab, ESA/ESRIN.

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Operational Satellite Radar Interferometry (InSAR) Applications for Earthquake and Ground Deformation Monitoring
2026-03-12 10:00 - 11:00
Earthquake-induced ground deformation and slow-moving geohazards such as subsidence and landslides pose significant risks across tectonically active and rapidly urbanizing regions. Through real case studies, the session will demonstrate how multi-temporal SAR datasets can be transformed into actionable deformation maps supporting disaster response, risk assessment, and resilient urban planning. The webinar highlights practical workflows, time-series deformation analysis for disaster management authorities. Participants will gain insight into InSAR processing strategies, time-series analysis approaches, and GIS-based integration workflows for disaster risk mapping and decision-support applications at local and provincial levels.

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Dr. Fatma Canaslan ÇomutDivision Manager – Earthquake and Disaster Risk Reduction at Governorship of Denizli Provincial Directorate of Disaster and Emergency (AFAD)Dr. Fatma Canaslan Çomut is a Cartography/Geomatics Engineer specializing in disaster risk reduction studies based on geodesy, remote sensing, radar interferometry, and Geographic Information Systems (GIS). She completed her graduate studies at the Department of Geodesy, Institute of Natural Sciences, Selçuk University in 2016. She has been working at the Denizli Provincial Disaster and Emergency Management Directorate since 2012. Since 2014, she has served as the Head of the Earthquake and Risk Reduction Branch, where she coordinates provincial disaster response and risk reduction planning processes. Her work integrates multi-temporal SAR interferometry and GIS-based spatial analysis for monitoring earthquakes, land subsidence, landslides, groundwater depletion, and infrastructure-related ground instability. Dr. Çomut actively participates in international collaborations and scientific events, contributing to the advancement of satellite-based disaster response methodologies.

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The Contribution of Satellite SAR Observations for Geohazards and Disaster Assessment Mapping
2026-03-31 12:00 - 13:00
Overview on how SAR data contributes to Geohazards mapping and Damage Assessment Mapping, indicating some initiatives, software and platforms that help its exploitation by final users and decision makers

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Dr. José Manuel Delgado BlascoGeosaptial System Engineer at European Space AgencyJosé Manuel Delgado Blasco, holds a double Ph.D. diploma in Geoscience and Remote Sensing from Delft University of Technology (The Netherlands) and Dr of Science in Geography from KU Leuven (Belgium). He has extensive experience working in the Earth Observation domain, specialized in algorithm development/parallelisation, processing platforms, AI, advanced InSAR applications, data fusion and algorithm optimization. Currently works as Geospatial System Engineer in the ESA Φ-lab Invest Office within the EO Commercialisation programme helping companies developing sustainable EO solutions.

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