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2018成都洪涝灾害多源时空数据集
A multi-source spatiotemporal dataset of floods in Chengdu (2018)
: 2018 - 12 - 14
: 2019 - 01 - 11
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摘要&关键词
摘要:随着防灾、减灾与救灾技术的不断进步,有效的涉灾数据来源也愈广泛。在洪涝事件中,传统的遥感影像、地面GIS数据以及社会经济发展状况作为主要灾害数据来源已得到一致认可,同时作为“移动传感器”的新兴灾害数据——社交媒体数据以其广泛的参与性和多源的传播性也得到了广泛的应用。本文以2018年7月成都洪涝事件为研究对象,基于多源时空数据融合的理念,收集整理了洪涝事件中不同时期的河流情况、遥感影像、新浪微博数据以及该区域的地形条件与社会经济发展状况数据。在传统灾害数据的基础上,结合灾区公众视角,较为完整地展现了此次洪涝灾害的影响程度与灾情进展,为后续的洪涝灾害风险区域划分、淹没范围建模以及灾情评估提供完整有效的数据支持。
关键词:洪涝灾害;社交媒体;GIS;多源时空数据
Abstract & Keywords
Abstract: With the continuous development of disaster prevention, mitigation and relief means, disaster-related data are becoming increasingly effective and extensive. In flood events, traditional remote sensing images, terrestrial GIS data, and socio-economic development data are widely recognized as the major sources of disaster data. In the meantime, social media data emerged as a "mobile sensor" of disasters, which have been widely used for its extensive participation and multi-source dissemination. Based on the concept of multi-source spatiotemporal data fusion, this paper collects and collates river situation data, remote sensing images, Sina Weibo data, terrain condition and socio-economic development data of the region in different periods in the flood event. On the basis of traditional disaster data, this study engages a public perspective of the disaster area to show the impact of flood disaster and the progress of the disaster, which provides complete and effective data support for subsequent flood risk zoning, flooding range modeling and disaster assessment.
Keywords: flood disaster; social media; GIS; multi-source spatiotemporal data
稿件与作者信息
李振宇
Li Zhenyu
牟乃夏
Mou Naixia
mounaixia@163.com
出版历史
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中国科学数据
csdata