Skip to main content
Search
Menu
thomas vimare unsplash
Photo: Thomas Vimare

Cascading Natural Hazards: Visualizing, Learning and Understanding

In this project we wanted to explore when, where and how cascading natural hazards occur - and why. What are the societal consequences of flooding, erosion, landslide? How can we visualise the effects and impact of these cascading natural hazards; and how can we communicate this in a better way?

The aim of the project was to develop methods to analyze and understand cascading natural hazards and their multiple effects and impacts. We designed scenarios and developed visualisations of the natural and societal consequences in a Swedish watercourse. We collaborated with secondary school students and additional public stakeholders.

A motivation for the project was to investigate how we can communicate and visualize nature-related information in a better way and change perspectives. We wanted to create commitment, interest and a sense of what is possible to achieve and thus counter and prevent feelings of helplessness.

On the RISE end of the project, the practical outcome was a web-based visualization which was designed around so called scrollytelling and which was used as an opportunity to explore the opportunities and challenges of using prominent digital tools for image generation to visualize natural events and hazards.

Summary

Project name

CAZULU

Status

Completed

RISE role in project

Project member

Project start

Duration

5 years

Partner

SGI, Swedish Geotechnical Institute

Funders

MSB, The Swedish Civil Contingencies Agency

Project website

Coordinators

Project members

Supports the UN sustainability goals

11. Sustainable cities and communities
László Sall Vesselényi

Contact person

László Sall Vesselényi

Forskare

+46 10 228 42 44

Read more about László

Contact László
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.

* Mandatory By submitting the form, RISE will process your personal data.