Using machine learning and explainable AI to model disaster effects on human migration in the United States

Category

Published in:

Abstracts of the ICA
Vol. 10.2025 (12.12.2025), art. no. 172, p. 1-2

Volume:

10.2025

Publication date:

12.12.2025

URN:

urn:nbn:de:0307-20260217-006-6

DOI:

10.5194/ica-abs-10-172-2025

Language:

English

Type of Resource:

Text

Extent:

1 Online-Ressource (Seite 1-2, 1,32 MB) : 2 Illustrationen, 1 Textdatei (PDF)

Keywords:

human migration; evacuation; spatial analysis; geovisualization; disasters; Evakuierung^GND; Raumanalyse; Geovisualisierung; Katastrophe^GND

DDC subject of DNB:

520 Astronomy & allied sciences

URL:

https://doi.org/10.5194/ica-abs-10-172-2025

URL:

https://ica-abs.copernicus.org/articles/10/172/2025/

Link to Raw Object:

https://ica-abs.copernicus.org/articles/10/172/2025/ica-abs-10-172-2025.pdf

Hosting institution:

University of South Florida (USF) [US]

Hosting institution:

Internationale Forschungseinrichtungen

Statement of responsibility:

Xiang Li, Yi Qiang

Bibliographic notes:

Published in: Abstracts of the ICA, Volume 10, 2025 - 32nd International Cartographic Conference (ICC 2025); 17–22 August 2025, Vancouver, Canada; Editors: Mir Abolfazl Mostafavi, Jonathan Li, and Emmanuel Stefanakis | https://ica-abs.copernicus.org/articles/10/index.html