Big data and artificial intelligence in earth science: recent progress and future advancements

• Autorzy: Verdu, Elena , Nieto, Yuri Vanessa , Saleem, Nasir
• Języki publikacji: EN

Abstrakty

EN

Earth science informatics has experienced significant growth in recent decades due to advancements in computational efficiency and processing power. The fourth industrial revolution has had a major impact on the environment, making earth science informatics crucial for detecting and predicting changes in the ecosystem and understanding the interactions between the land, ocean, and climate system. To tackle these challenges, data-driven approaches such as big data analytics and artificial intelligence (AI) are being utilized with increasing frequency. Big data analytics and AI allow researchers to analyse and acquire insights more efficiently, making predictions with observed data more effective. AI algorithms learn patterns from input and output data to establish a relationship and create a training model. The optimization of AI algorithms can improve the efficiency of earth science data computation even with complex datasets, uncovering hidden relationships and correlations between data sources. This Special Issue aims to bring together some of the leading experts in the field to share their latest research findings, as well as their perspectives on the future of Big data analytics and AI. Each of the fourteen articles published in this Special Issue has been rigorously peer-reviewed to ensure that they meet the highest standards of quality and scientific rigour. We are pleased to present the following highlights of these carefully selected contributions.

• Czasopismo: Acta Geophysica
• Rocznik: 2023
• Tom: Vol. 71, no. 3
• Strony: 1373--1375
• Opis fizyczny: Bibliogr. 14 poz.

Twórcy

autor

Verdu, Elena

• Universidad Internacional de la Rioja, Logroño, Spain,

autor

Nieto, Yuri Vanessa

• Universidad Nacional Abierta y a Distancia UNAD, Bogotá, Colombia,

autor

Saleem, Nasir

• Faculty of Engineering and Technology, Gomal University, Dera Ismail Khan, Pakistan,

Bibliografia

• 1. Chen X, Liang J, He X et al (2022) Process evaluation of soil treatment effect in Mu Us sandy land of Daji Khan in northern Shaanxi province based on fuzzy set. Acta Geophys. https://doi.org/10.1007/s11600-022-00936-y
• 2. Chi H, Sun J, Zhang C et al (2022) Remote sensing data processing and analysis for the identification of geological entities. Acta Geophys. https://doi.org/10.1007/s11600-022-00871-y
• 3. Cui Y (2022) Research on garden landscape reconstruction based on geographic information system under the background of deep learning. Acta Geophys. https://doi.org10.1007/s11600-022-00831-6
• 4. He T, Wang Y, Shi Z (2022) The effect of mulching films on the temporal and spatial distribution of soil water in semiarid hilly area. Acta Geophys. https://doi.org/10.1007/s11600-022-00841-4
• 5. Jiang Hl (2022) Molecular scale of network structure and water absorption of soil moisture gel. Acta Geophys. https://doi.org/10.1007/s11600-022-00778-8
• 6. Ma G, Xiao J, Li Q et al (2022) Impact of the evolution of Plateau Lake landscape pattern on ecosystem service value in the Pearl River basin: a case study of Yilong Lake Basin in Yunnan Province, China. Acta Geophys. https://doi.org/10.1007/s11600-022-00777-9
• 7. Renfei T, Tao L, Min O (2022) Method for wavelet denoising of multi-angle prestack seismic data. Acta Geophys. https://doi.org/10.1007/s11600-022-00842-3
• 8. Riaño MA, Rodriguez AOR, Velandia JB et al (2022) Design and application of an ontology to identify crop areas and improve land use. Acta Geophys. https://doi.org/10.1007/s11600-022-00808-5
• 9. Wang S, Su P, Li H et al (2022) Analysis of accumulation mechanism of Guantao Formation in Matouying Uplift of Jidong Oilfield and its exploration inspiration. Acta Geophys. https://doi.org/10.1007/s11600-022-00815-6
• 10. Yang X (2022) Sustainable and adaptable measures to address climate change in China: a strategic analysis in urban planning. Acta Geophys. https://doi.org/10.1007/s11600-022-00812-9
• 11. Yu L (2022) Automatic design optimization of landscape space based on improved genetic algorithm in tropical environment. Acta Geophys. https://doi.org/10.1007/s11600-022-00813-8
• 12. Zhang Y, Zhang J, Wang Q (2022) Scene analysis of landslide geoscience and characterization of scene evolution. Acta Geophys. https://doi.org/10.1007/s11600-022-00845-0
• 13. Zhu B, Zhou J (2022) Rainfall erosion of mountain environment and people flow planning of Leshan giant Buddha site based on big data GIS. Acta Geophys. https:/doi.org/10.1007/s11600-022-00803-w
• 14. Zhu S, Li H, Xu W et al (2022) Dynamic process and model simulation of soil water content during citrus growth period. Acta Geophys. https://doi.org/10.1007/s11600-022-00848-x

Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).

Identyfikatory

DOI

10.1007/s11600-023-01051-2