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The first European app to empower citizens against floods, fires and extreme weather events

Today is a happy day for every single person that is part of I-REACT. After 3 years of hard work, we are finally releasing to the public the first free European app to help citizens against disasters: our smartphone app. With it, you can help keep yourself and your community safe. Did you spot a wildfire? Go to a safe place, snap a picture and upload it, along with some information. The rest of the users will be able to see your report and stay safe. Or maybe you have seen in the news that heavy rain is coming. With our app, you can check if you are at risk of suffering a flood, and be prepared!

We are launching the app today, on the International Day for Disaster Reduction. We want to contribute as much as we can to diminish the impact that disasters have. Just last year, events like floods and wildfires affected more than 95 million people, they killed more than 9,600, and cost a whopping €285 billion, making 2017 the second costliest year on record. Unfortunately, it doesn’t look like it will get better: climate change is making extreme weather events more frequent and intense. We want you to be prepared and to have all the tools you need to fight against disasters. That’s why the app also includes a set of tips & quizzes on what to do before, during and after a weather-related emergency. All of this can be in your pocket: go to Google Play and download the app for free.

 

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I-REACT celebrates the first in-field demonstration at the Sava River basin

Over the last 5 years, Western Balkans have been severely hit by extreme flooding events. Major floods in 2010, 2013, 2014 and 2015 affected hundreds of thousands of people, causing extensive damage and a high casualty toll.

We chose this region to hold the first demonstration of our disaster management tool. In this way, we wanted to show how it can facilitate the work of authorities and civil protection in the fight against floods, but also highlight how it can aid in the coordination of different countries when a disaster hits more than one nation.

Over the three days of the workshop, the participants worked together in a simulated scenario based on the May 2014 historical Sava River flood. This flood killed 79 people, affected 2.6 million people and caused 3.8 million € in damages and losses across the Sava River Basin. The workshop linked the management of these events to the different functionalities of the I-REACT system, showing how technology can play a crucial role in the fight against disasters.

In the in-field demo of I-REACT, participants could test the crowdsourcing functionalities of the mobile app. They also tested different technologies specially devised for first responders: augmented reality glasses to provide them with live information, or a wearable that allows for detailed geolocalization.

The simulation of a control room demonstrated how a great variety of data coming from different sources, and serving different purposes, could be easily visualised by authorities. These easy visualization helps authorities making decisions in the event of an emergency.

Overall, the demo was a success. It highlighted the potential of an integration tool for disaster management, while helping authorities and responders both to save time and make more informed decisions when all variables are at play. Additionally, the I-REACT team gathered important feedback from professionals. Together with the information that we obtained in Paris, this will help us fine-tune the system and facilitate the use and integration of I-REACT within different operational procedures.

The next demonstration of our system will follow to continue bringing I-REACT closer to users and to ultimately improve future response to floods, and other disasters, mitigating their impact and help saving lives.

I-REACT group photo

The workshop was organised thanks to the support of the UNESCO Regional Bureau for Science and Culture in Europe in collaboration with the Sava River Basin Commission and other technical partners such as Deltares, the Royal Haskoning DHV from the Netherlands, the CIMA Research Foundation and ISMB (Instituto Superiore Mario Boella) from Italy.

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Forecasting more than just weather

“Today we can expect a 50% chance of rain…” How many times have you heard these words on the TV weather forecast? Have you ever wondered why weather-people talk about percentages? Rain, winds, temperatures… all these phenomena come with their number attached: the chance they might occur. This is the result of complex mathematical formulas of the physics behind the meteorological processes, inserted in computational models that forecasters use to predict the way weather will behave.

Since all weather forecasts models are chaotic, tiny variations on the parameters on those models lead to different results of the forecasts. These results imply different scenarios in the real life: it may rain cats and dogs, it may be a gentle rain or it may not even rain at all, but how likely is each option? In the case of rain, they combine two different factors: the confidence that it will rain someplace in the forecast area, and the percentage of that area that will receive rain if it rains. This is what meteorologist call probability of precipitation.

And, if this is important for your day-to-day forecast (so you know whether to take your umbrella or your sunglasses), imagine how important it is when we talk about extreme weather-related disasters and how to prevent them. Emergency responders and decision makers need to have at their tables all the different possible scenarios and know how likely is each one of them to happen, so they can take the best possible decisions. That is why at I-REACT we are including weather-related data and models into our I-REACTOR, the system that will integrate this information altogether with satellite and UAVs images, crowdsourced information and many other data sources and technologies, to provide detailed disaster risk maps for Europe.

Forecasting extreme events (like high levels of precipitations or strong winds) is key for preventing disasters. And to do this, special forecasts, different from the weather forecasts you see on TV, must be designed. Our colleagues at the Finnish Meteorological Institute are in charge of providing the extreme weather-related data. This means that they feed different extreme weather scenarios to the system, each one of them accompanied by a number: the chance that that particular scenario may happen. By doing so, FMI is able to provide different thresholds for risks: a probability that may seem tiny for normal events can be of huge importance when associated with extreme weather events.

Instead of delivering a unique weather prediction, FMI runs several simulations with slightly different initial conditions, so we can know the different scenarios and know how likely is each one of them to happen. This is called the Ensemble method. To calculate these different scenarios, FMI uses complex numerical models that run on supercomputers. The accuracy of those models depends highly on the initial conditions: the starting points of the simulation, consisting on real data taken from satellite images, meteorological stations and other sources.

To provide the most reliable results, FMI is feeding their models the best available data at the moment: high resolution maps gathered from weather systems across Europe, with a resolution down to 7 kilometres on a European scale, and a 3 Km resolution on a national scale. a much higher resolution in comparison with the usual map in you TV weather forecast which resolutions usually goes down to 20 km.

By combining better resolution maps and more accurate probabilities for extreme events, I-REACT will be of great help in saving lives thanks to cutting-edge technological advances. Against disasters, we have a fighting chance. And now, we are better at calculating these chances.

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A tweet can save lives

When Hurricane Katrina hit the American coast in 2005 Facebook was a newcomer to a still-to-be-developed world wide web, there was no Twitter to have news updates and less than 70% of citizens owned a mobile phone. Today, with more portable devices than citizens and an ever-constant interaction through social networks, the way we obtain and share information during crisis has drastically improved. This is proving very helpful in recent crisis like the 2013 super typhoon Haiyan in the Philippines where Twitter was the single greatest information source for response and recovery efforts.

Social media is becoming essential for authorities to access vital information provided by citizens that would not be available otherwise, which improves the prevention and response to critical events. However, social network information is largely unstructured arising from the fact that everyone can be an information source. From eyewitnesses to emergency responders or NGOs, that can provide information from the ground, to mass media that amplifies the message, or even outsiders showing sympathy and emotional support. In this context, there are many factors that affect how the information flows, such as the use of hashtags which is very diverse and can sometimes hamper the identification of relevant data. Thus, it is necessary to analyse social media to place the pieces of the puzzle together.

The extraction and analysis of social media information is an important part within the I-REACT project. This information obtained from citizens will complement data coming from earth observations, UAVs, or emergency responders, among others, to provide real time data on floods, wildfires, earthquakes and other natural disasters. For this, Natural Language Processing (NLP) technologies developed by the I-REACT partner CELI, are being used to analyse big data streams from social media.

To do this, great amounts of information are initially collected from social networks by using searches on generic keywords such as “earthquake” or “flood”. Although this information will be unstructured, all or most of the emergency-related material will be gathered this way. Since this data can be compared to that of past events and to “regular” behaviours on social networks, a vital information will be generated: detecting if something unexpected is going on and spotting the occurrence of an emergency in real time.

This information will then be validated through linguistic analysis and machine learning techniques. Here, it is possible to select the emergency-related contents and identify useful information such as the type and location of event, the casualties, or the damage to infrastructures and services. In addition, we can also have information about the sentiment of the message, which is important to create panic maps and to prioritise actions on the ground. And once the event is concluded, the system keeps collecting data so that it can be continuously tested in spotting new emergencies from social media. This way, this tool will progressively learn and refine its ability to identify disasters.

Overall, social media analysis provides fast and relevant information during emergencies, highlighting the fact that these communication channels are not only changing the way we live and interact with each other, but also making every citizen an essential part in the fight against disasters.

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