{"id":19202,"date":"2026-04-29T12:49:12","date_gmt":"2026-04-29T10:49:12","guid":{"rendered":"https:\/\/it-u.at\/?post_type=event&#038;p=19202"},"modified":"2026-04-30T11:38:48","modified_gmt":"2026-04-30T09:38:48","slug":"earth-observation-and-geoai-for-climate-resilient-urban-systems-grss-school","status":"publish","type":"event","link":"https:\/\/it-u.at\/en\/events\/earth-observation-and-geoai-for-climate-resilient-urban-systems-grss-school\/","title":{"rendered":"Earth Observation and GeoAI for Climate-Resilient Urban Systems : IEEE GRSS School"},"content":{"rendered":"\n<ul>\n<li><strong>Host:<\/strong> Interdisciplinary Transformation University (IT:U), Linz, Austria<\/li>\n\n\n\n<li><strong>Address:<\/strong> IT:U Research Campus, Freist\u00e4dter Str. 400, OG1 4040 Linz, Austria (Gold Meeting room)<\/li>\n\n\n\n<li><strong>Dates: <\/strong>14\u201316 October 2026<\/li>\n\n\n\n<li><strong>Format:<\/strong> In-person, 3-day program<\/li>\n\n\n\n<li><strong>Organizing body:<\/strong> IEEE GRSS (with Austrian, Italian and Polish chapters),\u00a0 IT:U and PLUS<\/li>\n\n\n\n<li><strong>Organizing committee:<\/strong> Shaily Gandhi,&nbsp; Bernd Resch,&nbsp; Martin Sudmanns, Karima Hadj-Rabah, Getachew Gella, Pawel Netzel<\/li>\n\n\n\n<li><strong>Participants:<\/strong> ~30 (young professionals + graduate students)<\/li>\n\n\n\n<li><strong>Speakers:<\/strong> 10 +<\/li>\n\n\n\n<li><strong>Language:<\/strong> English<\/li>\n\n\n\n<li><strong>Registration will open soon<\/strong><\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">About the school<\/h3>\n\n\n\n<p>Earth Observation and GeoAI for Climate-Resilient Urban Systems is an advanced school designed to equip the next generation of researchers, practitioners, and decision-makers with state-of-the-art Earth Observation (EO), geospatial artificial intelligence (GeoAI), and data fusion methodologies to analyze, quantify, and mitigate climate-driven risks and effects in urban systems.<\/p>\n\n\n\n<p>Within this framework, climate-resilient Urban Systems are understood as complex socio-technical systems composed of buildings, critical infrastructure, transportation networks, public spaces, and human communities. The program emphasizes how Earth Observation (EO), multi-sensor data fusion (including optical, SAR, and microwave EO), geospatial artificial intelligence (GeoAI), and participatory sensing can be integrated to strengthen urban resilience under conditions of climate change and multi-hazard exposure.<\/p>\n\n\n\n<p>The school combines expert lectures, structured hands-on laboratories, and a Digital City Studio living-lab experience to advanced EO analytics, GeoAI model development, and operational decision-making contexts. Participants will work with satellite imagery (Sentinel, Landsat, SAR, microwave missions), airborne data, in-situ measurements, geo-social media data and human-generated datasets using open-source tools and AI-driven methodologies to develop scalable scalable, explainable, and transferable workflows for urban risk intelligence, infrastructure vulnerability assessment, and climate perception analysis.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Learning Outcomes<\/h3>\n\n\n\n<p>By the end of the school, participants will be able to:<\/p>\n\n\n\n<ol start=\"1\">\n<li>Analyze and quantify climate-related hazards affecting built environments using multi-source Earth Observation datasets (including optical, SAR, and climate data).<\/li>\n\n\n\n<li>Design and implement multimodal workflows integrating satellite, in-situ, and human-generated data.<\/li>\n\n\n\n<li>Understand the value of GeoAI-based methodologies for analysing geo-social media data to deconstruct climate perception, narratives, and socio-environmental interactions in urban contexts.<\/li>\n\n\n\n<li>Develop AI-based classification models for disaster damage and infrastructure vulnerability assessment.<\/li>\n\n\n\n<li>Adapt remote sensing methodologies to low-resource and humanitarian contexts using open-access tools.<\/li>\n<\/ol>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Travel Grant Criteria<\/strong><\/h2>\n\n\n\n<p>A limited number of travel grants (up to 10 participants) are available to support attendance at the IEEE GRSS School <em>\u201cEarth Observation and GeoAI for Climate-Resilient Urban Systems.\u201d<\/em> These grants aim to promote accessibility, diversity, and inclusion.<\/p>\n\n\n\n<p><strong>Eligibility<\/strong><\/p>\n\n\n\n<p>Applicants must:<\/p>\n\n\n\n<ul>\n<li>Apply for in-person participation<\/li>\n\n\n\n<li>Be students, early-career researchers, or young professionals<\/li>\n\n\n\n<li>Demonstrate a basic background in GIS and\/or programming<\/li>\n\n\n\n<li>Submit a complete application, including motivation statement and CV<\/li>\n<\/ul>\n\n\n\n<p><strong>Selection Criteria<\/strong><\/p>\n\n\n\n<p>Travel grants will be awarded based on the following factors:<\/p>\n\n\n\n<p>1. Motivation and Relevance<\/p>\n\n\n\n<ul>\n<li>Quality and clarity of the motivation statement<\/li>\n\n\n\n<li>Alignment of applicant\u2019s work\/interests with Earth Observation, GeoAI, and climate-resilient urban systems<\/li>\n\n\n\n<li>Potential to benefit from and contribute to the summer school<\/li>\n<\/ul>\n\n\n\n<p>2. Academic and Professional Merit<\/p>\n\n\n\n<ul>\n<li>Educational background and research experience<\/li>\n\n\n\n<li>Demonstrated engagement in relevant domains (EO, geospatial analytics, urban\/climate studies)<\/li>\n\n\n\n<li>Supporting evidence from CV<\/li>\n<\/ul>\n\n\n\n<p>3. Financial Need<\/p>\n\n\n\n<ul>\n<li>Clear justification for requiring financial support<\/li>\n\n\n\n<li>Lack of alternative funding sources<\/li>\n<\/ul>\n\n\n\n<p>4. Diversity and Inclusion<\/p>\n\n\n\n<ul>\n<li>Priority may be given to:\n<ul>\n<li>Applicants from low- and middle-income countries<\/li>\n\n\n\n<li>Underrepresented groups in geospatial and AI fields<\/li>\n\n\n\n<li>Candidates from resource-constrained institutions<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\n\n\n<p><strong>What will be Covered<\/strong><\/p>\n\n\n\n<p>Travel grants are intended to partially or fully cover:<\/p>\n\n\n\n<ul>\n<li>Travel expenses<\/li>\n\n\n\n<li>Accommodation (up to 3 nights)&nbsp;<\/li>\n<\/ul>\n\n\n\n<h4 class=\"wp-block-heading\">More information will be provided soon.<\/h4>\n","protected":false},"excerpt":{"rendered":"<p>About the school Earth Observation and GeoAI for Climate-Resilient Urban Systems is an advanced school designed to equip the next generation of researchers, practitioners, and decision-makers with state-of-the-art Earth Observation (EO), geospatial artificial intelligence (GeoAI), and data fusion methodologies to analyze, quantify, and mitigate climate-driven risks and effects in urban systems. Within this framework, climate-resilient [&hellip;]<\/p>\n","protected":false},"featured_media":19203,"template":"","tags":[],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v22.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Earth Observation and GeoAI for Climate-Resilient Urban Systems : IEEE GRSS School | IT:U<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/it-u.at\/en\/events\/earth-observation-and-geoai-for-climate-resilient-urban-systems-grss-school\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Earth Observation and GeoAI for Climate-Resilient Urban Systems : IEEE GRSS School | IT:U\" \/>\n<meta property=\"og:description\" content=\"About the school Earth Observation and GeoAI for Climate-Resilient Urban Systems is an advanced school designed to equip the next generation of researchers, practitioners, and decision-makers with state-of-the-art Earth Observation (EO), geospatial artificial intelligence (GeoAI), and data fusion methodologies to analyze, quantify, and mitigate climate-driven risks and effects in urban systems. 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