TEMA Project - Trustely Extreme precise MApping and prediction for emergency management

TEMA

The Project
in a Nutshell

TEMA is a four year long project funded by the European Union flagship research and Innovation programme Horizon Europe, under the call HORIZON-CL4-2022-DATA-01-01 “Methods for exploiting data and knowledge for extremely precise outcomes (analysis, prediction, decision support), reducing complexity and presenting insights in understandable way”.

The objectives of TEMA are specifically to:

Improve Natural Disaster Management using new digital technologies and extreme data analytics;
Improve and accelerate extreme data analytics, by increasing trustworthiness, accuracy and responsiveness of extreme data analysis algorithms;
Improve and accelerate emergency phenomenon modeling, evolution predictions, simulation and interactive visualization;

The goal of TEMA is to deliver a technical solution that is supportive in disaster response and management by bringing situational data to relevant end-users, enabling transferability to tackle different disaster types in various geographic region thus providing the relevant information that can help make the best possible operative decisions. TEMA will provide a tool that:

is an AI-enabled Natural Disaster Management platform that will allow precise replication and modeling of real events;
offers precise semantic 3D area mapping and NDM event prediction over a long time period;
has interactive, intuitive and accessible visualization enabled by advanced augmented reality.

It will allow human operators to understand complex Natural Disaster Management phenomena and easily evaluate alternative response strategies by a smart selection of platform parameters and by novel ways of combining heterogeneous (visual and non-visual) data and/or augmented reality.

Why is it important?

TEMA will improve Natural Disaster Management by providing a state-of-the-art disaster management support system, dynamically exploiting multiple data sources and AI technologies for providing an accurate assessment of an evolving crisis situation.

TEMA solution, that will be able to provide predictions on the evolution of phenomena in (near) real time, will be useful to stakeholders like Civil Protection Agencies and First Responders for increase situational awareness for defining recommendations and guidelines to adopt when dealing with a complex emergency.

TEMA

The Project’s
Numbers

20

PARTNERS

involved in the project

4

YEARS

of project duration

11

MILLIONS

of € funded

TEMA

Project Pilots

Central-European Regional Floods (Germany)

Central Europe, due to presence of big rivers, can experience heavy persistent rains that cause regional floods, as happened during July 2021 in the German region of Ahrtal. In this pilot, a flood model will be set-up for the area and calibrated based on information retrieved from historic flood events, including the Ahrtal flood. The objective of TEMA is to provide information to be used to warn the responsible authorities, population and public protection, and provide information about the accessibility of the affected region leading to improved NDM.

Mediterranean Flash Floods (Greece)

The geomorphology and hydrological characteristics of Mediterranean catchments render such areas particularly prone to flash floods. The Greek pilot land area is among these, therefore, considering also the mega-fire occurred in August 2021, a flood model will be set up for the area and calibrated based on information retrieved from historic flood events as well as near-real-time information coming from the observations of streamflow gauges. The model will support (near-)real-time flood forecasting and flood warnings and can be used to examine and enhance the relevant NDM procedures.

Mediterranean Forest Fires (Italy)

The Autonomous Region of Sardinia (RAS) faced a severe crisis on July 2021, when a widespread 15.000-hectare forest fire provoked serious damages at Montiferru (central Sardinia). This scenario will be played out in real time for TEMA validation, with available data about the area vegetation, geomorphological data, damage details and safety procedures that have been adopted, output of meteorological models, forecast fire danger bulletins, satellite images, videos from drones filming the burnt area. The TEMA platform will also be used for examining the conditions of post-event territory, with...

Finnish Forest Fires (Finland)

Forest fires and the general extreme weather conditions in the Nordic countries, cause concern among Finnish emergency professionals. The pilot will be based on the historical scenario of the 2021 Kalajoki forest fire. This will provide a study case on forest fire management operations through the aggregation of environmental data sources, both existing and collected during the project. These datasets will be enriched with earlier reports on prevention strategies, as well as guidelines of the Finnish authorities for the boreal vegetation environment. By using TEMA solution, it will be...

Naapurinvaara in Sotkamo, Kainuu, Finland, 2022 August

Background Image: a night photo of a forest

TEMA

News

Ethics in action: Building a Co-Design Framework for Responsible Disaster Response

Fri, 13/12/2024 - 11:00

Incorporating ethics into the use of emerging technologies for Natural Disaster Management (NDM) is not just a responsibility; it is a necessity. Recognising these imperatives, TEMA adopted a collaborative, co-design methodology to align technological innovation with ethical responsibility.

Town after a flood with diffusion models, ATOS Spain

Using Diffusion Models to Generate Datasets of Images Affected by Natural Disasters

Wed, 11/12/2024 - 16:00

In recent years, diffusion models have become powerful tools in the field of artificial intelligence for image generation. Their applications extend beyond traditional creative or artistic uses, proving highly valuable for scientific, engineering, and crisis management purposes.

Drowning in the information flood: Identifying relevant social media posts for disaster management

Thu, 05/12/2024 - 12:30

Data from geo-social media can provide great added value for disaster management, as they offer a wide range of information (texts, images, videos, etc.) in near-real time. In order to be able to offer such an automated workflow, researchers at the University of Salzburg developed a methodology for relevance classification of Tweets for disaster management.

Fire behaviour modelling for operational decision-making

Tue, 26/11/2024 - 16:30

Wildfire is an integral component of many ecosystems, often necessary for habitat renewal and biodiversity. However, as recent events have shown, wildfires can also inflict severe damage and impacts on communities, infrastructure and the environment. Wildfires pose a growing threat globally, with their frequency and intensity exacerbated by climate change, urbanisation and changes in land use. Predicting fire behaviour is critical for ensuring safety, optimising resource deployment and mitigating damage.

Adopting global standards for interoperable communication and coordination in NDM: Common Alert Protocol and NGSI-LD

Thu, 31/10/2024 - 13:00

This articles dives into the decision to adopt the Common Alerting Protocol (CAP), a globally recognised OASIS standard designed to facilitate the dissemination of emergency alerts, to ensure that TEMA's platform can communicate efficiently and uniformly across heterogeneous systems and stakeholders, including civil protection agencies, first responders, and local authorities.

TEMA

TRUSTED
EXTREMELY PRECISE
MAPPING AND PREDICTION
FOR EMERGENCY
MANAGEMENT

The Project
in a Nutshell

Why is it important?

The Project’s
Numbers

Project Pilots