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Towards Time Series Sensor Data to Accurately Map Flood Hazard and Assess Damages under Climate Change Using Google Earth Engine Cloud Platform and GIS – Case of the Cities of Tetouan and Casablanca (Morocco)

El Yacoubi Yousra, Wahbi Miriam, Maatouk Mustapha, El Kharki Omar, Boulaassal Hakim, Alaoui Otmane Yazidi

Ecological Engineering & Environmental Technology

2023

Vol. 24, iss. 5

238--253

Climate change poses a major challenge in terms of urban planning management for the sake of a sustainable future. It is affecting the hydrological cycle around the world, leading to extreme weather conditions. Floods rank as the most frequent and widespread disaster in the world, they adversely affect inhabitants in terms of property damage and threat to human safety (and lives, in the worst cases). Uncontrolled urban sprawl also exacerbates floods by expanding impervious surfaces and affecting flow paths. Other factors that trigger flooding (apart from the rainfall intensity) are human involvement in the main waterways, thereby significantly impacting the hydraulic flow characteristics, structural engineering breakdowns, compounded by potential deforestation. For the purpose of monitoring the aftermath of floods experienced by the cities of Casablanca and Tetouan (Morocco) respectively in January and March 2021 and estimating their damages, optical and radar satellite images derived from the Google Earth Engine (GEE) cloud platform were used along with the Geographic Information System (GIS). In this study, a novel technique for extracting flooded areas from high-resolution Synthetic Aperture Radar (SAR) time series images has been developed. A comparison was carried out subsequently between the time-series approach and other traditional approaches including radiometric thresholding method, spectral indices namely Normalized Difference Water Index (NDWI) and Modified Normalized Difference Water Index (MNDWI) as well as Flood Water Index (FWI). Based on the above approach, the water levels were estimated and the damages were assessed and mapped, notably the number of people exposed to flood hazard and the amount of built-up areas and cropland affected. The results demonstrated that Casablanca city has witnessed a higher flood level than Tetouan city, putting a large number of people at risk and affecting a significant area of land use. The findings can also provide local authorities with a comprehensive view of flooding and enable them to make decisions on preparedness, mitigation, and adaptation to flood-related disasters.

Flooded wetlands mapping from Sentinel-2 imagery with spectral water index : a case study of Kampinos National Park in central Poland

Solovey Tatiana

Geological Quarterly

2020

Vol. 64, No. 2

492--505

Flood monitoring of wetlands and floodplains is a new issue in remote sensing, as compared to the mapping of open water bodies. The method based on spectral water indices, calculated on the basis of green, red and shortwave infrared bands, is one of the most popular methods for the recognition of a water body in multispectral images. The recently introduced Sentinel-2 satellite can provide multispectral images with high spatial resolution. This new data set is potentially of great importance for flood mapping, due to its free access and the frequent revisit capabilities. In this study, three popular water indices (Modified Normalized Difference Water Index, Normalized Difference Pond Index and Normalized Difference Turbidity Index) were used. The efficiency of the proposed method was tested experimentally using the Sentinel-2 image for the Kampinos National Park in Poland. The experiment compared four extraction algorithms including three based on individual water indicators and one on a combination of them. The results showed that the 10-metre false colour composite produced significantly improved the recognition of flooding in wetland areas by comparison with single spectral water indices. In this way, flooded wetlands were mapped based on the Sentinel-2 data set for the years 2017-2018.