Collection

Progress of Geoinformatics in Earth and Environmental Sciences

Submission status
Closed
In the past two decades, big data, data mining, machine learning, ontologies, and knowledge graphs have enabled many new methods and technologies in geoinformatics. A cyberinfrastructure ecosystem for Earth and environmental sciences is emerging. Correspondingly, data-intensive scientific discoveries have been reported in various fields, such as mineralogy, paleontology, paleobiology, geochemistry, geophysics, hydrology, mineral exploration, geohazards, and more. Very recently, researchers in the field of artificial intelligence (AI) began the discussion on knowledge-infused machine learning and neuro-symbolic AI. As a natural reaction to the thriving of AI, geoinformatics and GIScience researchers proposed Earth AI and GeoAI as umbrella topics to highlight the adaptation and application of AI in Earth science and geography. Is AI leading to more updates in different parts of geoinformatics? Are the new geoinformatics methods and technologies changing the way geoscientists do their work? Can other researchers benefit from existing successful applications and make breakthroughs in their own work? To answer those questions and give a big picture of the recent progress of geoinformatics in Earth and environmental sciences, we propose this special issue with the journal Earth Science Informatics. We welcome submissions on reviews, methods and technologies of different components/steps in geoinformatics, including but not limited to knowledge modeling and representation, ontology and knowledge graph, open data infrastructure, new techniques in data collection and mapping, new methods in statistics and machine learning, and data visualization. We also welcome submissions demonstrating significant applications of geoinformatics methods and technologies that solve a need from Earth and environmental sciences in the real world.

Editors

  • Xiaogang Ma Xiaogang Ma , 

    Xiaogang Ma

    Xiaogang (Marshall) Ma is an associate professor of computer science at the University of Idaho, USA. He received his Ph.D. degree of Earth Systems Science and GIScience from University of Twente, Netherlands in 2011, and then completed postdoctoral training of Data Science at Rensselaer Polytechnic Institute. His research focuses on deploying data science in the Semantic Web to support cross-disciplinary collaboration and scientific discovery, with broad interests in complex systems in Earth and environmental sciences, data interoperability and provenance, and visualized exploratory analysis of Big and Small Data.

  • Qiyu Chen Qiyu Chen , 

    Qiyu Chen

    Qiyu Chen is a professor of geoinformatics at the China University of Geosciences, Wuhan. He received his Ph.D. degree of Geoscience Information Engineering from China University of Geosciences in 2018, with one year (12/2026 to 12/2027) as a visiting Ph.D. student at University of Lausanne. His research interests include 3D characterization, simulation and modeling for subsurface heterogeneous structures and phenomena, development of algorithms and applications of multiple-point geostatistics and machine/deep learning methods in earth and environmental sciences, and design and development of tools for visual analysis of geospatial data.

  • Xiang Que Xiang Que  &

    Xiang Que

    Xiang Que is a postdoctoral researcher of computer science at the University of Idaho, USA. He received his PhD degree of Geoscience Information Engineering from China University of Geoscience in 2015. His research focuses on spatiotemporal data modeling and statistical analysis, with broad interests in geoinformatics technologies such as applying parallel computing and knowledge graphs. He received the May Fourth Youth Individual Medal and the Fujian Province Surveying, Mapping, and GIScience and Technology Award - First Prize in 2021. He is a director of the China Industrial Statistics Teaching Research Association.

  • Gang Liu Gang Liu

    Gang Liu

    Gang Liu is a professor of computer science at the China University of Geosciences, Wuhan. He received his Ph.D in Geodetection and Information Technology from China University of Geosciences in 2004. From 2006 to 2007 he studied at University of Ottawa, Canada as a Post-doctorate Fellow. His research interests include geoscience big data, 3D geographical information system and spatio-temporal data analysis. He has authored and co-authored 90+ peer-reviewed journal papers, and 20+ conference abstracts/papers. In 2020, he received the John Cedric Griffiths Teaching Award from the International Association for Mathematical Geosciences.

Articles (23 in this collection)