AIMC Topic: Climate Change
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Spatial prediction of forest fires in India: a machine learning approach for improved risk assessment and early warning systems.
Environmental science and pollution research international
Feb 1, 2025
Forest fires pose a significant ecological and environmental threat globally, and India has seen a marked increase in both the frequency and severity of these events in recent years. This has led to extensive damage to natural resources, including fo...
Integrating deep learning algorithms for forecasting evapotranspiration and assessing crop water stress in agricultural water management.
Journal of environmental management
Jan 31, 2025
The increasing impacts of climate change on global agriculture necessitate the development of advanced predictive models for efficient water management in crop fields. This study aims to enhance the forecasting of evapotranspiration (ET), potential e...
The use of multiple evidence base methods to enrich climate change research and knowledge in the Arctic.
Ambio
Jan 25, 2025
Indigenous and local knowledge (ILK) is increasingly used along with scientific knowledge (SK) to understand climate change. The multi evidence base (MEB) offers ways of combining knowledge systems together. Nonetheless, there is little guidance on h...
Spatiotemporal variation in biomass abundance of different algal species in Lake Hulun using machine learning and Sentinel-3 images.
Scientific reports
Jan 21, 2025
Climate change and human activities affect the biomass of different algal and the succession of dominant species. In the past, phytoplankton phyla inversion has been focused on oceanic and continental shelf waters, while phytoplankton phyla inversion...
Informing Risk Hotspots and Critical Mitigations for Rainstorms Using Machine Learning: Evidence from 268 Chinese Cities.
Environmental science & technology
Jan 16, 2025
Climate change is exacerbating rainstorms, increasing the risk of flooding and threatening urban sustainability, which could undermine climate action. Here, we propose a machine learning-based framework to assess heterogeneous risks and identify crit...
Understanding the spread of agriculture in the Western Mediterranean (6th-3rd millennia BC) with Machine Learning tools.
Nature communications
Jan 15, 2025
The first Neolithic farmers arrived in the Western Mediterranean area from the East. They established settlements in coastal areas and over time migrated to new environments, adapting to changing ecological and climatic conditions. While farming prac...
Spatiotemporal analysis of land surface temperature and land cover changes in Prešov city using downscaling approach and machine learning algorithms.
Environmental monitoring and assessment
Jan 3, 2025
In recent decades, global climate change and rapid urbanization have aggravated the urban heat island (UHI) effect, affecting the well-being of urban citizens. Although this significant phenomenon is more pronounced in larger metropolitan areas due t...
Soil temperature estimation at different depths using machine learning paradigms based on meteorological data.
Environmental monitoring and assessment
Dec 26, 2024
Knowledge of soil temperature (ST) is important for analysing environmental conditions and climate change. Moreover, ST is a vital element of soil that impacts crop growth as well as the germination of the seeds. In this study, four machine-learning ...
Advancing food security: Rice yield estimation framework using time-series satellite data & machine learning.
PloS one
Dec 12, 2024
Timely and accurately estimating rice yields is crucial for supporting food security management, agricultural policy development, and climate change adaptation in rice-producing countries such as Bangladesh. To address this need, this study introduce...
Investigating the Bromoform Membrane Interactions Using Atomistic Simulations and Machine Learning: Implications for Climate Change Mitigation.
The journal of physical chemistry. B
Dec 6, 2024
Methane emissions from livestock contribute to global warming. Seaweeds used as food additive offer a promising emission mitigation strategy because seaweeds are enriched in bromoform─a methanogenesis inhibitor. Therefore, understanding bromoform sto...
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