Artificial intelligence for geoscience: Progress, challenges and perspectives
This paper explores the evolution of geoscientific inquiry, tracing the progression from
traditional physics-based models to modern data-driven approaches facilitated by significant …
traditional physics-based models to modern data-driven approaches facilitated by significant …
[HTML][HTML] Deep learning for urban land use category classification: A review and experimental assessment
Map** the distribution, pattern, and composition of urban land use categories plays a
valuable role in understanding urban environmental dynamics and facilitating sustainable …
valuable role in understanding urban environmental dynamics and facilitating sustainable …
Collaboration between artificial intelligence and Earth science communities for mutual benefit
Collaboration between artificial intelligence and Earth science communities for mutual benefit |
Nature Geoscience Skip to main content Thank you for visiting nature.com. You are using a …
Nature Geoscience Skip to main content Thank you for visiting nature.com. You are using a …
Knowledge co-creation during urban simulation computation to enable broader participation
Z Ma, H Li, K Zhang, J Wang, S Yue, Y Wen… - Sustainable Cities and …, 2025 - Elsevier
Preparing knowledge on urban simulation computation is necessary to help participants
build consensus, reduce expertise gaps, and guide participatory sustainable urban …
build consensus, reduce expertise gaps, and guide participatory sustainable urban …
Simulation-driven strategies for enhancing water treatment processes in chemical engineering: addressing environmental challenges
NC Obiuto, N Ninduwezuor-Ehiobu, EC Ani… - Engineering Science & …, 2024 - fepbl.com
Water treatment processes in chemical engineering play a critical role in addressing
environmental challenges and ensuring the sustainability of water resources. This paper …
environmental challenges and ensuring the sustainability of water resources. This paper …
Inversion of soil organic carbon content based on the two-point machine learning method
C Wang, B Gao, K Yang, Y Wang, C Sukhbaatar… - Science of the Total …, 2024 - Elsevier
Soil organic carbon (SOC) is vital for the global carbon cycle and environmentally
sustainable development. Meanwhile, the fast, convenient remote sensing technology has …
sustainable development. Meanwhile, the fast, convenient remote sensing technology has …
Boundary delineator for martian crater instances with geographic information and deep learning
Detecting impact craters on the Martian surface is a critical component of studying Martian
geomorphology and planetary evolution. Accurately determining impact crater boundaries …
geomorphology and planetary evolution. Accurately determining impact crater boundaries …
Promoting forest landscape dynamic prediction with an online collaborative strategy
Modeling and predicting forest landscape dynamics are crucial for forest management and
policy making, especially under the context of climate change and increased severities of …
policy making, especially under the context of climate change and increased severities of …
Exploring geospatial digital twins: a novel panorama-based method with enhanced representation of virtual geographic scenes in Virtual Reality (VR)
J Zhang, J Zhu, Y Zhou, Q Zhu, J Wu… - International Journal …, 2024 - Taylor & Francis
An important step in implementing geospatial digital twins is to enhance the expressiveness
of virtual geographical scenes for the physical world. However, the existing virtual …
of virtual geographical scenes for the physical world. However, the existing virtual …
[HTML][HTML] Reproducing computational processes in service-based geo-simulation experiments
Geo-simulation experiments (GSEs) are experiments allowing the simulation and
exploration of Earth's surface (such as hydrological, geomorphological, atmospheric …
exploration of Earth's surface (such as hydrological, geomorphological, atmospheric …