BEGIN:VCALENDAR VERSION:2.0 PRODID:-//pretalx//talks.staging.osgeo.org//foss4g-europe-2025//speaker//ZB FPKS BEGIN:VTIMEZONE TZID:CET BEGIN:STANDARD DTSTART:20001029T040000 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=10 TZNAME:CET TZOFFSETFROM:+0200 TZOFFSETTO:+0100 END:STANDARD BEGIN:DAYLIGHT DTSTART:20000326T030000 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=3 TZNAME:CEST TZOFFSETFROM:+0100 TZOFFSETTO:+0200 END:DAYLIGHT END:VTIMEZONE BEGIN:VEVENT UID:pretalx-foss4g-europe-2025-JAEKT7@talks.staging.osgeo.org DTSTART;TZID=CET:20250716T173000 DTEND;TZID=CET:20250716T183000 DESCRIPTION:Where better to have an open discussion regarding the two impor tant facets that build and sustain FOSS4G - community and business - if no t at FOSS4G Europe? \nTo close a great first day of the FOSS4G Mostar conf erence\, we are honoured to invite our distinguished panelists to share th eir views\, lessons learned and pieces of advice on what it means to be ac tive an active human in the FOSS4G world as a community leader\, a fundrai ser\, a worker in the private or the public sector. \n\nJoin us for what w e promise will be an insightful conversation and a great discussion starte r for the Ice Breaker! DTSTAMP:20260527T015047Z LOCATION:EL11 (Geosolutions) SUMMARY:People and business: the two complementary facets of FOSS4G - Ilie Codrina\, Yuri Astrakhan\, Risto Ilves\, Gresa Neziri\, Bartosz Brzezińsk i URL:https://talks.staging.osgeo.org/foss4g-europe-2025/talk/JAEKT7/ END:VEVENT BEGIN:VEVENT UID:pretalx-foss4g-europe-2025-38KDUJ@talks.staging.osgeo.org DTSTART;TZID=CET:20250717T150500 DTEND;TZID=CET:20250717T151000 DESCRIPTION:Increased urbanization rates have had a significant effect on c hanging land surface characteristics\, leading to the rise of Urban Heat I slands (UHIs)\, localized regions where temperatures are considerably high er than in surrounding rural areas. This phenomenon is primarily driven by dense urban structures\, reduced vegetation cover\, and anthropogenic hea t discharge\, which collectively contribute to enhancing the absorption an d retention of heat in urban areas (Anjos et al.\, 2025\; Qin & Jiang\, 20 24). As climate change intensifies\, UHIs worsen environmental problems\, including increased energy consumption\, lower air quality\, and severe pu blic health concerns like heat stress and cardiovascular disease (Chanpich aigosol & Chaichana\, 2025). The rapid expansion of urban areas has elevat ed UHI mitigation to one of the highest priorities. Yet\, existing detecti on and analysis methods often lack scalability\, automation\, limiting the ir ability to produce high-resolution\, globally consistent assessments (F u et al.\, 2024). DTSTAMP:20260527T015047Z LOCATION:PA01 (Quarticle) SUMMARY:An Open-Source Deep Learning Framework for Scalable Urban Heat Isla nd Detection Using Geospatial Data - Mercy Ọ̀nàọpẹ́mipọ̀ Akin tola\, Gresa Neziri URL:https://talks.staging.osgeo.org/foss4g-europe-2025/talk/38KDUJ/ END:VEVENT BEGIN:VEVENT UID:pretalx-foss4g-europe-2025-VWG7HU@talks.staging.osgeo.org DTSTART;TZID=CET:20250718T121500 DTEND;TZID=CET:20250718T122000 DESCRIPTION:Flood is one of the most devastating natural hazards\, imposing enormous social\, economic\, and infrastructural impacts on nations world wide. Major flood events disrupt communities by damaging critical infrastr ucture\, displacing large populations\, and causing extensive financial lo sses. These disasters not only strain emergency response systems but also hinder long-term development\, emphasizing the urgent need for reliable\, timely\, and detailed spatial data to guide both immediate action and futu re mitigation planning. Flood disasters often expose critical gaps in the availability of timely and accurate geospatial data. \n\nThis study invest igates the role of open source data in enhancing disaster preparedness and response\, with a particular focus on community-mapped data\, using Jakan de housing estate\, 1st gate Platinum Wy Lekki Penninsula II Lekki 106104\ , presently located in the Eti-Osa Local government of Lagos State as a ca se study. By harnessing the power of volunteered geographic information co ntributed by local residents\, the research addresses critical data gaps i n under-mapped regions (Goodchild\, 2007\; Haworth & Bruce\, 2015). Commun ity mapping initiatives not only provide timely\, real‐time updates duri ng flood events but also incorporate localized insights that traditional m apping methods may overlook. This participatory approach enriches the spat ial dataset\, offering details on flood extents\, infrastructure damage\, and population displacement. In integrating these community-driven dataset s with advanced geospatial tools\, the study demonstrates a significant im provement in situational awareness\, ultimately supporting more informed a nd effective decision-making during emergency response efforts.\n\nThe met hodology comprises a multi-tiered approach. Initially\, high-resolution sa tellite imagery of the case study area was acquired over a six-year period \, enabling a temporal analysis of land cover changes and pre- and post-fl ood conditions. This remote sensing phase provided an extensive visual rec ord that served as a baseline for further spatial analysis. A review of ex isting OpenStreetMap (OSM) data revealed that the targeted area was largel y unmapped—a gap that hindered the region’s disaster response capacity (Herfort et al.\, 2021). In response\, a dedicated mapping task was initi ated using the Humanitarian OpenStreetMap Team (HOT) Tasking Manager to in vite contributions from volunteer mappers\, thereby creating an up-to-date geographic dataset. Furthermore\, the presented methodology offers insigh ts into how to verify OSM data and contribute to the improvement of its ac curacy and thoroughness.\n\nTo augment the remote mapping effort\, on-grou nd data collection was undertaken using Open Data Kit (ODK). Field surveys focused on gathering real-time information on the condition of local infr astructure and documenting patterns of population displacement due to floo ding. The data collection process incorporated stringent quality checks by cross-referencing field findings with local community insights\, ensuring both accuracy and contextual relevance. This integrated approach highligh ts the synergy between remote sensing\, open-sourced mapping\, and communi ty-based data acquisition—a combination increasingly recognized as criti cal for effective disaster management.\n\nSubsequent spatial analysis was performed using QGIS\, First\, a multi-temporal change detection algorithm was applied by comparing classified satellite imagery from pre- and post- flood periods. This method\, which utilized indices such as the Normalized Difference Vegetation Index (NDVI)\, allowed us to assess changes in land cover dynamics over time. Overlay analysis was then performed by intersec ting the delineated flood extent polygons with mapped infrastructure layer s—including residential\, commercial\, and roads—to pinpoint areas whe re vulnerable structures were concentrated. Additionally\, spatial queries \, including buffer and proximity analysis\, were executed to delineate hi gh-risk zones where flood extents and population clusters overlapped which allowed for a comprehensive assessment of flood-induced damage\, identifi cation of vulnerable infrastructure\, and quantification of displacement m etrics and to provide a clearer picture of the flood’s spatial extent. T he spatial analysis outputs were visualized as detailed maps that conveyed spatial patterns and risk zones to emergency responders and policymakers. \n\nThe spatial analysis revealed that the flood inundated a vast portion of the study area\, with a significant concentration of affected housing a nd critical infrastructure. Detailed overlay analysis showed that more tha n 40% of the mapped residential zones were located in high-risk flood area s. In addition\, clusters of commercial and public service facilities—su ch as police stations—were clearly delineated within these zones\, many of which had not been previously mapped in OpenStreetMap. This data gap hi ghlighted the urgent need for community-driven mapping\, which was address ed through a dedicated task via the Humanitarian OpenStreetMap Team. These findings provide crucial guidance for targeted emergency response and inf rastructure reinforcement (Rajabifard et al.\, 2004). However\, the study faced limitations\, including variability in data resolution and gaps in r eal-time field verification. Notably\, attempts to obtain Sentinel-2 satel lite imagery from NASA for the study area were unsuccessful\, limiting the spectral analysis capabilities. Future research should focus on integrati ng higher resolution satellite imagery and advanced predictive modeling to further refine flood impact assessments and enhance the overall effective ness of disaster management strategies.\n\n\nThe research underscorse the transformative role of open source geodata in disaster response. By integr ating satellite imagery with OSM-derived mapping\, the study not only fill s important data gaps but also enables rapid situational awareness during and after flood events (Grippa et al.\, 2022). The participatory mapping approach—combining remote sensing with field-collected data—proved to be an effective model for generating reliable spatial information in data- scarce environments. This framework demonstrates that the use of free and open-source geospatial tools can enhance both immediate response and long- term resilience planning in communities affected by natural hazards. The r esults of the study provide practical insights into the integration of div erse data sources for improved emergency management and suggest that such methodologies can be readily adapted to address various types of natural h azards. Future work should focus on refining these methods and exploring a dditional data fusion techniques to further enhance the effectiveness of d isaster management strategies. DTSTAMP:20260527T015047Z LOCATION:PA01 (Quarticle) SUMMARY:The Role of Open Source Data in Disaster Preparedness and Response: A Case Study on Flood Impact in Local Communities - Gresa Neziri\, Adeola Anthonia OYETUNDE URL:https://talks.staging.osgeo.org/foss4g-europe-2025/talk/VWG7HU/ END:VEVENT END:VCALENDAR