A review of earth artificial intelligence

Z Sun, L Sandoval, R Crystal-Ornelas… - Computers & …, 2022 - Elsevier
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 …

[HTML][HTML] Advances in geocomputation and geospatial artificial intelligence (GeoAI) for mapping

Y Song, M Kalacska, M Gašparović, J Yao… - International Journal of …, 2023 - Elsevier
Geocomputation and geospatial artificial intelligence (GeoAI) have essential roles in
advancing geographic information science (GIS) and Earth observation to a new stage …

Toward a collective agenda on ai for earth science data analysis

D Tuia, R Roscher, JD Wegner… - … and Remote Sensing …, 2021 - ieeexplore.ieee.org
In past years, we have witnessed the fields of geosciences and remote sensing and artificial
intelligence (AI) become closer. Thanks to the massive availability of observational data …

Google Earth Engine and artificial intelligence (AI): a comprehensive review

L Yang, J Driscol, S Sarigai, Q Wu, H Chen, CD Lippitt - Remote Sensing, 2022 - mdpi.com
Remote sensing (RS) plays an important role gathering data in many critical domains (eg,
global climate change, risk assessment and vulnerability reduction of natural hazards …

Application of machine learning, deep learning and optimization algorithms in geoengineering and geoscience: Comprehensive review and future challenge

W Zhang, X Gu, L Tang, Y Yin, D Liu, Y Zhang - Gondwana Research, 2022 - Elsevier
Abstract The so-called Fourth Paradigm has witnessed a boom during the past two decades,
with large volumes of observational data becoming available to scientists and engineers …

Application of artificial intelligence in geotechnical engineering: A state-of-the-art review

A Baghbani, T Choudhury, S Costa, J Reiner - Earth-Science Reviews, 2022 - Elsevier
Geotechnical engineering deals with soils and rocks and their use in engineering
constructions. By their nature, soils and rocks exhibit complex behaviours and a high level of …

Artificial intelligence for remote sensing data analysis: A review of challenges and opportunities

L Zhang, L Zhang - IEEE Geoscience and Remote Sensing …, 2022 - ieeexplore.ieee.org
Artificial intelligence (AI) plays a growing role in remote sensing (RS). Applications of AI,
particularly machine learning algorithms, range from initial image processing to high-level …

[PDF][PDF] Big data and machine learning in geoscience and geoengineering: Introduction

W Zhang, J Ching, ATC Goh, AYF Leung - Geoscience …, 2020 - ira.lib.polyu.edu.hk
In recent years, we have entered the so-called Fourth Paradigm with the regular production
of huge amount of observational data. Big data is often characterized by the three 'V's …

Machine learning for data-driven discovery in solid Earth geoscience

KJ Bergen, PA Johnson, MV de Hoop, GC Beroza - Science, 2019 - science.org
BACKGROUND The solid Earth, oceans, and atmosphere together form a complex
interacting geosystem. Processes relevant to understanding Earth's geosystem behavior …

A survey of machine learning and deep learning in remote sensing of geological environment: Challenges, advances, and opportunities

W Han, X Zhang, Y Wang, L Wang, X Huang… - ISPRS Journal of …, 2023 - Elsevier
Due to limited resources and environmental pollution, monitoring the geological
environment has become essential for many countries' sustainable development. As various …