GeoAI Reproducibility and Replicability: a computational and spatial perspective

arXiv:2404.10108v1 Announce Type: cross
Abstract: GeoAI has emerged as an exciting interdisciplinary research area that combines spatial theories and data with cutting-edge AI models to address geospatial problems in a novel, data-driven manner. While GeoAI research has flourished in the GIScience literature, its reproducibility and replicability (R&R), fundamental principles that determine the reusability, reliability, and scientific rigor of research findings, have rarely been discussed. This paper aims to provide an in-depth analysis of this topic from both computational and spatial …

abstract ai models arxiv computational cs.cv cs.lg data data-driven edge edge ai geospatial literature novel perspective reproducibility research spatial type