Team #17 // SHIELD

Executive Summary

Climate models indicate that natural disasters and extreme weather conditions are becoming more frequent. Natural disasters such as earthquakes, tsunamis or hurricanes put many human lives at risk, not only during the disaster but afterwards as well. At SHIELD we use satellite data to provide situational awareness during and after disasters considering mainly assessment of the roads and building damage.


After a natural disaster has occurred, it is essential for the emergency personnel to arrive at the scene quickly to save as many people as possible and start recovery. Ruined roads and collapsed buildings slow down the response time of the emergency personnel making it difficult for them to get around efficiently.

Therefore, not only time but also valuable resources are wasted in such situations. Current solutions focus on using helicopters and drones for surveying the area and assessing the damage. Many of the cities most exposed to natural disasters are in developing countries where these drones and helicopters are not always immediately available.

Target user / Customer

The users of our product are the emergency personnel who go to the emergency area and help the victims. The emergency personnel will not be the ones paying for the solution rather, our main target customer is non governmental organizations like The Red Cross and other disaster response institutions.

Your solution and how the concept is feasible

Our solution does not require drones or helicopters to be available, which in some countries is just not possible. Instead, SHIELD uses Synthetic Aperture Radar (SAR) data from satellites covering large areas in order to detect where the roads have been damaged and assess the state of the infrastructure in the entire area. In the future we expect to have a high time resolution in SAR imaging over the Earth, which provides the necessary tool to have a quick response [1].

The way it is envisioned to work, is in the form of an algorithm that is activated as soon as an alarm by systems like Galileo Search And Rescue is received [2]. The area of interest is input into the algorithm, which downloads a stack of images before the catastrophe in order to map the prior roads. At that point, the algorithm would download the most recent available images over the same area, and starts detecting the change in every pixel falling within the roads and/or other infrastructures to assess stability of buildings and finding good areas for setting up shelter. The amount of change would be assessed by comparing to the statistics of the images prior to the natural disaster.

Moreover, we can differentiate between roads that have been affected by impediments such as rocks from landslides or trees verses roads that have been affected by flooding. A more accurate assessment is done as more images are acquired and constant update is provided.

The information would be provided by means of a phone app similar to the main navigation systems. The app will include the additional parameter of road damage, which would allow anyone to navigate through the area knowing which areas to avoid, which roads to take instead and even which unstable areas should not be entered (using geofencing or similar tools).

Although this app is thought for a soon to be mostly digitalized world, the feasibility of it can already be tested. By using existing roadmaps over a terrain, one can overlap those to satellite images and get the pixel values over them. This way, a multi-temporal statistic can be done and a distribution for each pixel can be derived, in order to determine in the post-disaster images if some change has happened.

Four unique value propositions

  1. Can be used during a hurricane, or during similar adverse weather conditions when helicopters and drones cannot be used to assess the damage.
  2. Frequently updated information on which roads and buildings are damaged.
  3. Allows the Red Cross or similar organisations to quickly find locations for helicopter landings or where to set-up shelter camps.
  4. Gives a complete overview of the disaster area and immediately identifies invaluable intel for the emergency personnel to act upon.


We would sell our product to the main disaster response institutions (mostly governments), non governmental organisations (such as the Red Cross) and international entities (such as EU or UN). In 2018 the Red Cross allocated 520 M DKK for funding disaster services worldwide [3].


The impact our solution is to save invaluable time during a crisis when people are at the most in need of help. By defining clear transportation routes for emergency personnel to move around in the disaster area, we can optimize the amount of people who get help per hour after a natural disaster, thus potentially saving lives. The sustainable development goals that at most meets our solution is number 3 (Good health and well being) as well as number 9 (Industry, innovation and infrastructure).


Our team specializes in Synthetic Aperture Radars and Earth Observation data analysis. Not only are we experienced with working with satellite data; we also have the business analytics, entrepreneurship and innovation experience for making this into a profitable business. Our main motivation is to provide those who suffer from such disasters with the best solution to save time and resources.

Group Members

List full name and e-mails (preferably not your student e-mail)

Jonathan Emil Gundorph Jansen,
Stefan Alvin Graham,
Johanne Høst Thorkilsdatter,
Martí Perpinyà Vallès.