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Investigating the accuracy of georeferenced social media data for flood mapping: The PetaJakarta.org case study

机译:调查洪水映射的地理学社交媒体数据的准确性:Petajakarta.org案例研究

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摘要

Georeferenced social media data are gaining increased application in creating near real-time flood maps needed to improve situational awareness in data-starved regions. However, there is growing concern that the georeferenced locations of flood-related social media contents do not always correspond to the actual locations of the flooding event. But to what extent is this true? Without this knowledge, it is difficult to ascertain the accuracy of flood maps created using georeferenced social media contents. This study aims to improve understanding of the extent to which georeferenced locations of social media flood reports deviate from the actual locations of floods. The study analyses flood-related tweets acquired as part of the PetaJakarta.org project implemented in the coastal mega-city of Jakarta and provides insight into the level of accuracy expected with using georeferenced social media data for flood mapping. Importantly, the results reveal that the accuracy of flood maps generated with georeferenced social media data reduces with increase in the size of the minimum mapping unit of the flood map. Finally, an approach is recommended for creating more accurate real time flood maps from crowdsourced social media data.
机译:地理参考的社交媒体数据正在增加在提高数据匮乏地区的态势意识所需的近实时洪水地图方面的应用程序增加。然而,越来越担心泛滥相关的社交媒体内容的地理参考位置并不总是对应于洪水事件的实际位置。但在多大程度上是真实的?如果没有这种知识,很难确定使用地理学社交媒体内容创建的洪水贴图的准确性。本研究旨在改善社会媒体洪水报告偏离洪水实际位置的地理位置程度的理解。该研究分析了作为Petajakarta.org项目中获得的泛滥相关推发,该项目在雅加达沿海大众市实施,并在洪水映射中使用地理学的社交媒体数据来了解预期的准确性水平。重要的是,结果表明,使用地理学媒体数据产生的洪水图的准确性随着洪水映射的最小映射单元的大小而减小。最后,建议采用一种方法来创建来自众群社交媒体数据的更准确的实时洪水映射。

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