2016 · 43 citations · 18 references
ComputingData ScienceVisualizationRemote SensingSocial Media AnalyticsVisual AnalyticsEvent DetectionRemote Sensing Image AnalysisSatellite Image InterpretationSocial MediaDisaster Event DetectionEvent RetrievalSatellite Remote Sensing Data
The availability of satellite images for academic or commercial purpose is increasing rapidly due to efforts made by governmental agencies (NASA, ESA) to publish such data openly or commercial startups (PlanetLabs) to provide real-time satellite data. Beyond many commercial application, satellite data is helpful to create situation awareness in disaster recovery and emergency situations such as wildfires, earthquakes, or flooding. To fully utilize such data sources, we present a scalable system for the contextual enrichment of satellite images by crawling and analyzing multimedia content from social media. This information stream can provide vital information from the ground and help to complement remote sensing in situations. We use Twitter as main data source and analyze its textual, visual, temporal, geographical and social dimensions. Visualizations show different aspects of the event allowing high-level comprehension and provide deeper insights into the event as complemented by social media.
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Deep Residual Learning for Image Recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren et al. · 2016 · 222.1K citations · Full text
Going deeper with convolutions
Christian Szegedy, Wei Liu, Yangqing Jia et al. · 2015 · 46.8K citations
Earthquake shakes Twitter users
Takeshi Sakaki, Makoto Okazaki, Yutaka Matsuo · 2010 · 3.7K citations
Natural Sciences, Data Science, Natural Language Processing +14
David Lazer, Alex Pentland, Lada A. Adamic et al. · Science · 2009 · 3.3K citations · Full text