AIMC Topic: Conservation of Natural Resources
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AI-driven participatory environmental management: Innovations, applications, and future prospects.
Journal of environmental management
Jan 2, 2025
The rapid advancement of Artificial Intelligence (AI) presents unprecedented opportunities for participatory environmental management. This paper explores the integration of AI technologies into participatory approaches, which engage diverse stakehol...
Do circular innovations and carrying capacity of natural environment enhance circular economy in the European Union? Evidence from simulation and machine learning methods.
Journal of environmental management
Dec 27, 2024
The longevity of the natural environment is fundamental for sustainable production and consumption. The circular economy conserves natural resources, ensures sustainable production and consumption, and protects the natural environment. The role of ci...
PoachNet: Predicting Poaching Using an Ontology-Based Knowledge Graph.
Sensors (Basel, Switzerland)
Dec 20, 2024
Poaching poses a significant threat to wildlife and their habitats, necessitating advanced tools for its prediction and prevention. Existing tools for poaching prediction face challenges such as inconsistent poaching data, spatiotemporal complexity, ...
The potential for AI to revolutionize conservation: a horizon scan.
Trends in ecology & evolution
Dec 17, 2024
Artificial Intelligence (AI) is an emerging tool that could be leveraged to identify the effective conservation solutions demanded by the urgent biodiversity crisis. We present the results of our horizon scan of AI applications likely to significantl...
Does smart city construction promote urban green development? Evidence from a double machine learning model.
Journal of environmental management
Dec 17, 2024
The issue of whether smart city construction (SCC) can promote urban green development (UGD) is controversial. To address this problem, first, a UGD evaluation index system with four dimensions, namely, green production, green living, green growth, a...
Assessing the performance of machine learning algorithms for analyzing land use changes in the Hyrcanian forests of Iran.
Environmental science and pollution research international
Nov 30, 2024
Land use changes are of critical importance in understanding and managing environmental sustainability and resource utilization. Machine learning algorithms (MLAs) have emerged as powerful tools for analyzing and predicting land use changes, offering...
Harnessing Artificial Intelligence for Sustainable Bioenergy: Revolutionizing Optimization, Waste Reduction, and Environmental Sustainability.
Bioresource technology
Nov 27, 2024
Assessing the mutual benefits of artificial intelligence (AI) and bioenergy systems, to promote efficient and sustainable energy production. By addressing issues with conventional bioenergy techniques, it highlights how AI is revolutionising optimisa...
Understanding ecosystem services of detailed forest and wetland types using remote sensing and deep learning techniques in Northern China.
Journal of environmental management
Nov 20, 2024
Spanning both temperate and sub-frigid zones, Northeast China boasts typical boreal forests and abundant wetland resources. Because of these attributes, the region is critically significant for global climate regulation, carbon sequestration, and bio...
Robots and animals teaming up in the wild to tackle ecosystem challenges.
Science robotics
Nov 20, 2024
Interactively teaming up animals and robots could facilitate basic scientific research and address environmental and ecological crises.
A spatial machine learning approach to exploring the impacts of coal mining and ecological restoration on regional ecosystem health.
Environmental research
Nov 19, 2024
Ecosystem health is an important approach to measuring urban and regional sustainability. In previous studies, the spatiotemporal changes of ecosystem health have been addressed using comprehensive assessment index system. However, the quantitative c...
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