Cover Image

GeoAI for science and the science of GeoAI

This paper reviews trends in GeoAI research and discusses cutting-edge advances in GeoAI and its roles in accelerating environmental and social sciences. It addresses ongoing attempts to improve the predictability of GeoAI models and recent research aimed at increasing model explainability and repro...

Full description

Saved in:
Bibliographic Details
Main Authors: Li, Wenwen (Author) , Arundel, Samantha T. (Author) , Gao, Song (Author) , Goodchild, Michael F. (Author) , Hu, Yingjie (Author) , Wang, Shaowen (Author) , Zipf, Alexander (Author)
Format: Article (Journal)
Language:English
Published: 2024-09-20
In: Journal of spatial information science
Year: 2024, Volume: 29, Pages: 1-17
ISSN:1948-660X
DOI:10.5311/JOSIS.2024.29.349
Online Access:Resolving-System, kostenfrei, Volltext: https://doi.org/10.5311/JOSIS.2024.29.349
Verlag, kostenfrei, Volltext: https://josis.org/index.php/josis/article/view/349
Get full text
Author Notes:Wenwen Li, Samantha Arundel, Song Gao, Michael Goodchild, Yingjie Hu, Shaowen Wang, and Alexander Zipf
Description
Summary:This paper reviews trends in GeoAI research and discusses cutting-edge advances in GeoAI and its roles in accelerating environmental and social sciences. It addresses ongoing attempts to improve the predictability of GeoAI models and recent research aimed at increasing model explainability and reproducibility to ensure trustworthy geospatial findings. The paper also provides reflections on the importance of defining the "science" of GeoAI in terms of its fundamental principles, theories, and methods to ensure scientific rigor, social responsibility, and lasting impacts.
Item Description:Literaturverzeichnis: Seite 12-17
Gesehen am 23.06.2025
Physical Description:Online Resource
ISSN:1948-660X
DOI:10.5311/JOSIS.2024.29.349

Similar Items