Data Driven Multi-Hazard Risk Visualization

Abstract
This work presents an approach for visualizing aggregate spatial risk data for natural hazards in a way which is not restricted by fixed geographical boundaries and is intended to improve multi-risk awareness in at-risk populations. First, spatial proximity is analyzed to organize occurrences in clusters and the convex hull of each cluster is created in order to define our visualization regions. Then, each region is assigned a risk factor value which is visualized by selecting a color scheme specific to the data variation. The application of this technique is demonstrated using the state of California as a region of interest.
Description

        
@inproceedings{
10.2312:eurp.20201117
, booktitle = {
EuroVis 2020 - Posters
}, editor = {
Byška, Jan and Jänicke, Stefan
}, title = {{
Data Driven Multi-Hazard Risk Visualization
}}, author = {
Sharma, Ritesh
and
Tomson, Ayme
and
Lobato, Emilio
and
Kallmann, Marcelo
and
Padilla, Lace
}, year = {
2020
}, publisher = {
The Eurographics Association
}, ISBN = {
978-3-03868-105-2
}, DOI = {
10.2312/eurp.20201117
} }
Citation