07-18, 12:10–12:15 (Europe/Sarajevo), PA01
Flooding is one of the most damaging natural disasters, intensified by climate change, urban development, and land-use changes. Effective flood monitoring and management are crucial to mitigating the negative impacts, especially in regions with complex hydrological dynamics. This study focuses on the Kupa River basin in Croatia, a flood-prone region, and presents an integrated approach for flood mapping and climate impact assessment using open-source Earth observation (EO) data and free tools. Combining a different remote sensing datasets; Sentinel-1 Synthetic Aperture Radar (SAR), Sentinel-2 Normalized Difference Vegetation Index (NDVI), and Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) precipitation datasets, all accessed through Google Earth Engine (GEE), this research demonstrates a cost-effective and scalable solution for monitoring flood dynamics and climate change insights on a focused area. Sentinel-1 SAR, with its cloud-penetrating capabilities, is used to detect surface water changes, while Sentinel-2 through the NDVI complemented vegetation health before and after flood events. CHIRPS data, with daily precipitation estimates, contextualizes the meteorological conditions that contribute to flooding. The integration of these datasets offers a comprehensive analysis of flood events and their environmental impacts, providing actionable insights for local flood management and climate change adaptation. The use of open-access and freely available data and free tools highlights the potential for replicable flood monitoring in regions with limited infrastructure, further supporting the development of early-warning systems and informed decision-making.
Copernicus datasets, CHRIPS
Assign a number between 1 and 3 indicating the level of technical complexity of your contribution. –2 - background knowledge helpful
Give indication of resources (video, web pages, papers, etc.) to read in advance, that will help get up to speed on advanced topics. –Zhang, Q., Zhang, Z., Wang, X., Xu, Z., & Wang, Y. (2024). Monitoring of Glacier Area Changes in the Ili River Basin during 1992–2020 Based on Google Earth Engine. Land, 13(9), 1417. https://doi.org/10.3390/land13091417
Ali, M., Ali, T., Gawai, R., Dronjak, L., & Elaksher, A. (2024). The Analysis of Land Use and Climate Change Impacts on Lake Victoria Basin Using Multi-Source Remote Sensing Data and Google Earth Engine (GEE). Remote Sensing, 16(24), 4810. https://doi.org/10.3390/rs16244810
Johary, R., Révillion, C., Catry, T., Alexandre, C., Mouquet, P., Rakotoniaina, S., Pennober, G., & Rakotondraompiana, S. (2023). Detection of Large-Scale Floods Using Google Earth Engine and Google Colab. Remote Sensing, 15(22), 5368. https://doi.org/10.3390/rs15225368
Data processing and analysis, FOSS4G for crisis / disaster response, civil defence, Drones, sensors, lasers, and remote sensing, FOSS4G and environmental observations
Olga Bjelotomić Oršulić is an assistant professor at Deprtment of Geodesy and Geomatics at University North, Varaždin, Croatia. She obtained her PhD in geodesy at Faculty of Geodesy at University of Zagreb. She worked both in academy and industry being an enthusiast in geoid modelling, gravity field, remote sensing, open free geospatial community and data and project management of large geoinformation implementations.