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Conservation of Natural Resources

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Towards sustainable coastal management: aerial imagery and deep learning for high-resolution mapping.

PeerJ
The massive arrival of pelagic on the coasts of several countries of the Atlantic Ocean began in 2011 and to date continues to generate social and environmental challenges for the region. Therefore, knowing the distribution and quantity of in the o...

Addressing pollution challenges for enterprises under diverse extreme climate conditions: artificial intelligence-driven experience and policy support of top Chinese enterprises.

Frontiers in public health
INTRODUCTION: This study investigates the experiences of leading Chinese companies in environmental conservation under varying extreme climate conditions, focusing on the role of artificial intelligence (AI) and governmental assistance.

A machine learning approach to map the potential agroecological complexity in an indigenous community of Colombia.

Journal of environmental management
Agroecological systems are potential solutions to the environmental challenges of intensive agriculture. Indigenous communities, such as the Kamëntšá Biyá and Kamëntšá Inga from the Sibundoy Valley (SV) in Colombia, have their own ancient agroecologi...

AI-based green technology implementation simulation for achieving carbon neutrality: exploring the role of subsidies and knowledge management.

Environmental science and pollution research international
This study investigates the role of green technology implementation (GTI) based on artificial intelligence (AI) at the household level to achieve carbon neutrality by addressing gaps in the existing research. The research focuses on understanding how...

Does artificial intelligence affect the ecological footprint? -Evidence from 30 provinces in China.

Journal of environmental management
Artificial intelligence (AI) technology serves as a powerful tool to optimize energy efficiency and lessen ecological footprints. Using data from 30 provinces in China over the period from 2018 to 2022, this study investigates how regional AI develop...

Predicting Prayagraj's Urbanization Trajectory using CA-ANN Modelling: Population Pressures and Land Use Dynamics.

Journal of environmental management
Land Use/Land Cover (LULC) dynamics provide a crucial role in the monitoring, planning, and management of resources. They also offer valuable information for developing strategies to balance conservation efforts, resolve conflicts between different l...

Artificial intelligence correctly classifies developmental stages of monarch caterpillars enabling better conservation through the use of community science photographs.

Scientific reports
Rapid technological advances and growing participation from amateur naturalists have made countless images of insects in their natural habitats available on global web portals. Despite advances in automated species identification, traits like develop...

How does green manufacturing enhance corporate ESG performance? - Empirical evidence from machine learning and text analysis.

Journal of environmental management
Green manufacturing, widely recognized as a crucial avenue for companies to achieve sustainable competitive advantages, exerts significant spillover effects on both environmental protection and social responsibility. Accordingly, this can significant...

Do China's ecological civilization advance demonstration zones inhibit fisheries' carbon emission intensity? A quasi-natural experiment using double machine learning and spatial difference-in-differences.

Journal of environmental management
China's National Ecological Civilization Demonstration Zone (NECDZ) policy has a significant role in ensuring national ecological security, and it is essential to investigate how the NECDZ policy affects the carbon emissions intensity of fisheries (C...

Digital brains, green gains: Artificial intelligence's path to sustainable transformation.

Journal of environmental management
The environmental impacts of artificial intelligence on a global scale remain underexplored. This study utilizes a balanced panel dataset to examine artificial intelligence's complex role in enhancing global green productivity between 2008 and 2019. ...