https://josis.org/index.php/josis/issue/feed 2024-09-20T02:57:54+00:00 Professor Ross Purves ross.purves@geo.uzh.ch Open Journal Systems <p>The <strong>Journal of Spatial Information Science</strong> (JOSIS) is an international, interdisciplinary, open-access journal dedicated to publishing high-quality, original research articles in spatial information science. The journal aims to publish research spanning the theoretical foundations of spatial and geographical information science, through computation with geospatial information, to technologies for geographical information use.</p> <p>JOSIS is run as a service to the geographic information science community, supported entirely through the efforts of volunteers. JOSIS does not aim to profit from the articles published in the journal, which are open access. We encourage you to become involved in JOSIS by <a href="http://josis.org/index.php/josis/user/register">registering as a reader, reviewer, or author</a>, or simply <a href="http://josis.org/index.php/josis/donations">making a donation to JOSIS</a>.</p> https://josis.org/index.php/josis/article/view/349 2023-12-14T19:49:56+00:00 Wenwen Li wenwen@asu.edu Samantha Arundel sarundel@usgs.gov Song Gao song.gao@wisc.edu Michael Goodchild good@geog.ucsb.edu Yingjie Hu yhu42@buffalo.edu Shaowen Wang shaowen@illinois.edu Alexander Zipf zipf@uni-heidelberg.de

<p>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.</p>

2024-09-20T00:00:00+00:00 Copyright (c) 2024 Wenwen Li, Samantha T. Arundel, Song Gao, Michael F. Goodchild, Yingjie Hu, Shaowen Wang, Alexander Zipf