Abstract

Flood risk prediction requires consistent and accurate sensor measurements, usually provided from traditional in-situ environmental monitoring systems. Crowd-sourced data can complement these official data sources, allowing authorities to improve and fill gaps in the hazard assessment process. However, collecting this information from volunteers, with no technical knowledge and while using low-cost equipment such their smart phones and tablets, raises the question of quality and consistency. To alleviate this barrier two mobile applications were developed in the context of H2020 Scent project (grant agreement No. 688930). The Scent Explore guides volunteers to areas of interests and supports them in the collection of video and images. These multimedia are processed in the back-end, image recognition techniques extract the water level from images containing a measuring tape and video processing algorithms extract the water surface velocity from video containing a predefined floating object moving on the surface of a water body, to extract river measurements as needed. The Scent Measure communicates with the portable sensors available at the area of interest and records the air temperature and the soil moisture. We present here a complete monitoring system where crowd-sourced environmental measurements are harmonised and integrated as complementary to the in-situ monitoring system, installed at the Kifisos basin, in the process of developing improved flood models.

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