A review of Earth Artificial Intelligence

Обзор искусственного интеллекта для исследования Земли
S. Mostafa Mousavi, Thomas E. Gill, Ziheng Sun, Nicoleta Cristea, Pablo Rivas, Robert Crystal‐Ornelas, Sanjay Purushotham, Jianwu Wang, Chandana Gangodagamage, Jinbo Wang, James A. Bednar, Benjamin Holt, Xiaogang Ma, Julien Chastang, Cindy Lin, L. Sandoval, Daniel Tong, Wendy Hawley Carande, Yuhan Rao, Amanda Tan, Daniel L. Howard, Peisheng Zhao, Zachary Chester, Javier Orduz, Aji John
2022-01-05

Earth artificial intelligenceEarth science data systemsEarth system sciencesgeosciencesmachine learning
In recent years, Earth system sciences are urgently calling for innovation on improving accuracy, enhancing model intelligence level, scaling up operation, and reducing costs in many subdomains amid the exponentially accumulated datasets and the promising artificial intelligence (AI) revolution in computer science. This paper presents work led by the NASA Earth Science Data Systems Working Groups and ESIP machine learning cluster to give a comprehensive overview of AI in Earth sciences. It holistically introduces the current status, technology, use cases, challenges, and opportunities, and provides all the levels of AI practitioners in geosciences with an overall big picture and to “blow away the fog to get a clearer vision” about the future development of Earth AI. The paper covers all the majorspheres in the Earth system and investigates representative AI research in each domain. Widely used AI algorithms and computing cyberinfrastructure are briefly introduced. The mandatory steps in a typical workflow of specializing AI to solve Earth scientific problems are decomposed and analyzed. Eventually, it concludes with the grand challenges and reveals the opportunities to give some guidance and pre-warnings on allocating resources wisely to achieve the ambitious Earth AI goals in the future.
1
It decomposes and analyzes the mandatory steps in workflows for adapting AI methods to Earth-science problems.
2
It reviews representative AI research spanning all major Earth-system domains, offering a holistic perspective on the current state of Earth AI.
3
The paper identifies grand challenges and future opportunities to guide resource allocation and development toward ambitious Earth AI goals.
4
The paper provides a comprehensive overview of artificial intelligence applications, technologies, use cases, challenges, and opportunities across Earth system sciences.
5
The review introduces widely used AI algorithms and computing cyberinfrastructure relevant to geoscientific applications.

Artificial intelligence applications in Earth system sciences across the major Earth-system domains

The current status, representative use cases, workflows, challenges, opportunities, and future development of Earth AI

Publication Details
Publication Date
2022-01-05
Journal
Publisher
ISSN
Cited by
272
Access Type
Author Information
Authors
S. Mostafa Mousavi
Thomas E. Gill
Ziheng Sun
Nicoleta Cristea
Pablo Rivas
Robert Crystal‐Ornelas
Sanjay Purushotham
Jianwu Wang
Chandana Gangodagamage
Jinbo Wang
James A. Bednar
Benjamin Holt
Xiaogang Ma
Julien Chastang
Cindy Lin
L. Sandoval
Daniel Tong
Wendy Hawley Carande
Yuhan Rao
Amanda Tan
Daniel L. Howard
Peisheng Zhao
Zachary Chester
Javier Orduz
Aji John
Explore further
Open the scid.ai AI chat with a ready-made request: it will find papers on a similar topic and help build a literature review.
Find similar papers in the chat →
Make a presentation
100%