Abstract
The European Space Agency satellites Sentinel-1 radar and Sentinel-2 optical data are widely used in water surface mapping and management. In this work, we exploit the potentials of both radar and optical images for satellite-based quick detection and extent mapping of inundations/water raising events over Shkodër area, which occurred in the two last years (2017–2018). For instance, in March 2018 the Shkodër district (North Albania) was affected twice by the overflow of the Drin and Buna (Bojana) Rivers and by the Shkodër lake plain inundation. Sentinel-1 radar data allowed a rapid mapping of seasonal fluctuations and provided flood extent maps by discriminating water surfaces (permanent water and flood areas) from land/non-flood areas over all the informal zones of Shkodër city. By means of Sentinel-2 data, two color composites maps were produced and the Normalized Difference Water Index was estimated, in order to further distinguish water/moisturized soil surfaces from built-up and vegetated areas. The obtained remote sensing-based maps were combined and discussed with the urban planning framework in order to support a sustainable urban and environmental management. The provided multi-temporal analysis could be easily exploited by the local authorities for flood prevention and management purposes in the inherited territorial context. The proposed approach outputs were validated by comparing them with official Copernicus EMS (Emergency Management Service) maps available for one of the chosen events. The comparison shows good accordance results. As for a further enhancement in the future perspective, it is worth to highlight that a more accurate result could be obtained by performing a post-processing edit to further refine the flooded areas, such as water mask application and supervised classification to filter out isolated flood elements, to remove possible water-lookalikes and weed out false positives.
Highlights
Detection and quick mapping of the extent and distribution of overflowed water surfaces during major flood events on urban areas can be significant for quantifying possible hazard maps within spatial and environmental planning strategies [1]
In this work we exploit the potentials of both radar Sentinel-1 and optical Sentinel-2 images for a satellite-based quick detection and extent mapping of recent inundation/water raising events over Shkodër area
In order to validate our results, the official delineation maps were downloaded from the Copernicus Emergency Management Service and were used to cross-compare products
Summary
Detection and quick mapping of the extent and distribution of overflowed water surfaces during major flood events on urban areas can be significant for quantifying possible hazard maps within spatial and environmental planning strategies [1]. The wide lowland areas are characterized by very small gradients and subjected to pervasive minor inundations due to seasonal fluctuations of water levels These water variations are important to be studied and to be spatially defined in comprehensive maps, since the related surface water circulation can adversely interfere with some of the waterside anthropic activities and, at the same time, can severely impact the ecosystem balance of wetlands, influencing the existing bioma. Throughout the quick detection of seasonal water fluctuations extent, useful and immediate information can be provided for the realization of a large scale mapping, the collection of local vulnerability related to the urban and natural arrangement, as well as for the criticality categorization to include in ordinary planning and management of extraordinary emergency situations In such a perspective, the currently available remote sensing space-borne Earth Observation (EO) sensors are useful sources of information on inundation events over wide areas. Both of the two satellite imagery types, i.e., optical and radar data, can help with the rapid tracing of inundated areas by exploiting their time- and cost-efficiency as well as their wide area coverage, and can successfully detect spatial and temporal water level variations and fluctuations extent maps [2,3]
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