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Two case studies of recent floods in Jakarta (Indonesia) and York (United Kingdom) were evaluated. For both case studies a dataset of Tweets was constructed, from which both locations and water depths were derived. As a first step the sets of Tweets collected for these cases and the locations and water depths derived from them, were investigated. The magnitude of errors in location and water depth derived from the Tweets was investigated by comparing them to locations and water depths derived from photographs attached to some of the Tweets. Iin Jakarta, the majority of the Tweet’s locations are pinpointed within 200 m of their actual location, however, outliers of up to 3.5 km still exist in the dataset.The characteristics of both datasets are given in the table below.
Karakteristieken gefilterde twitter data
| Jakarta | York | |
|---|---|---|
| date | 8/2-11/2 2015 | 25/12-30/12 2015 |
| total number of filtered tweets | 219 | 87 |
| tweets with a water depth observation | 123 | 0 |
| average location error streets | 659 m | 287 m |
| average location error POI | 236 m | 52 m |
Besides analysing the Tweets gathered for both case studies, different methods of creating flood maps were evaluated. The flood extents created for the Jakarta case study were validated using information derived from photographs and the flood extents created for the York case study were validated using actual recorded flood extents. Using the method that created the most accurate flood maps, the uncertainty in flood extent, resulting from locational errors of Tweets, errors in water depths mentioned by Tweets and errors in the elevation data, was evaluated using Monte Carlo simulations. Also the effects of choosing a different default water depth value and using different resolutions on the uncertainty in flood extent was investigated. The comparison of the flood extents generated using the different flood mapping methods with validation datasets showed that for both the Jakarta and York case studies, the best results were obtained by interpolating water levels along the flow paths downstream of observations.
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