Related papers: Floods impact dynamics quantified from big data so…
Disaster mobile apps play an increasingly important role in disseminating hazard information and supporting communities during emergency situations. This study presents a comprehensive analysis of these mobile applications, focusing on…
Flash floods in urban areas occur with increasing frequency. Detecting these floods would greatlyhelp alleviate human and economic losses. However, current flood prediction methods are eithertoo slow or too simplified to capture the flood…
The analysis of natural disaster-related multimedia content got great attention in recent years. Being one of the most important sources of information, social media have been crawled over the years to collect and analyze disaster-related…
The rapid spread of radical ideologies in recent years has led to a worldwide string of terrorist attacks. Understanding how extremist tendencies germinate, develop, and drive individuals to action is important from a cultural standpoint,…
Flooding is the world's most costly type of natural disaster in terms of both economic losses and human causalities. A first and essential procedure towards flood monitoring is based on identifying the area most vulnerable to flooding,…
Significant negative impacts are observed in productivity, economy, and social wellbeing because of the reduced human activity due to extreme events. Community resilience is an important and widely used concept to understand the impacts of…
Climate change is a major threat to humanity, and the actions required to prevent its catastrophic consequences include changes in both policy-making and individual behaviour. However, taking action requires understanding the effects of…
Social media have been widely exploited to detect and gather relevant information about opinions and events. However, the relevance of the information is very subjective and rather depends on the application and the end-users. In this…
Accurate flood detection from visual data is a critical step toward improving disaster response and risk assessment, yet datasets for flood segmentation remain scarce due to the challenges of collecting and annotating large-scale imagery.…
Floods are the most common form of natural disaster and accurate flood forecasting is essential for early warning systems. Previous work has shown that machine learning (ML) models are a promising way to improve flood predictions when…
Socio-economic data mining has a great potential in terms of gaining a better understanding of problems that our economy and society are facing, such as financial instability, shortages of resources, or conflicts. Without large-scale data…
Floods are large-scale natural disasters that often induce a massive number of deaths, extensive material damage, and economic turmoil. The effects are more extensive and longer-lasting in high-population and low-resource developing…
Social media have the potential to provide timely information about emergency situations and sudden events. However, finding relevant information among millions of posts being posted every day can be difficult, and developing a data…
Floods are among the most frequent and catastrophic natural disasters and affect millions of people worldwide. It is important to create accurate flood maps to plan (offline) and conduct (real-time) flood mitigation and flood rescue…
Climate change has increased the severity and frequency of weather disasters all around the world. Flood inundation mapping based on earth observation data can help in this context, by providing cheap and accurate maps depicting the area…
The frequency of extreme flood events is increasing throughout the world. Daily, high-resolution (30m) Flood Inundation Maps (FIM) observed from space play a key role in informing mitigation and preparedness efforts to counter these extreme…
The massive amounts of geolocation data collected from mobile phone records has sparked an ongoing effort to understand and predict the mobility patterns of human beings. In this work, we study the extent to which social phenomena are…
Increasingly available high-frequency location datasets derived from smartphones provide unprecedented insight into trajectories of human mobility. These datasets can play a significant and growing role in informing preparedness and…
With the rapid advancement of information and communication technologies, many researchers have adopted alternative data sources from private data vendors to study human movement dynamics in response to large-scale natural or societal…
With the explosion of social media sites and proliferation of digital computing devices and Internet access, massive amounts of public data is being generated on a daily basis. Efficient techniques/ algorithms to analyze this massive amount…