AIMC Topic: Conservation of Natural Resources

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Robots and animals teaming up in the wild to tackle ecosystem challenges.

Science robotics
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
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...

Predicting green technology innovation in the construction field from a technology convergence perspective: A two-stage predictive approach based on interpretable machine learning.

Journal of environmental management
The construction industry, as a major global energy consumer and carbon emitter, plays a crucial role in achieving global sustainability. A key strategy for the green transformation of this industry-without compromising development-involves fostering...

Online public opinion attention, digital transformation, and green investment: A deep learning model based on artificial intelligence.

Journal of environmental management
The digital economy is rising at an unprecedented pace, becoming a key driver of the comprehensive transformation and upgrading of the global economy and society. Existing research widely demonstrates the multifaceted positive impacts of green invest...

Multi-temporal image analysis of wetland dynamics using machine learning algorithms.

Journal of environmental management
Wetlands play a crucial role in enhancing groundwater quality, mitigating natural hazards, controlling erosion, and providing essential habitats for unique flora and wildlife. Despite their significance, wetlands are facing decline in various global ...

Can urban digital intelligence transformation promote corporate green innovation? Evidence from China.

Journal of environmental management
Can urban digital intelligence transformation (DIT) facilitate corporate green innovation (CGI)? This research uses the staggered difference-in-differences (DID) approach to study how urban DIT, represented by the Artificial Intelligence Innovation D...

ONDL: An optimized Neutrosophic Deep Learning model for classifying waste for sustainability.

PloS one
Sustainability has become a key factor on our planet. If this concept is applied correctly, our planet will be greener and more eco-friendly. Nowadays, waste classification and management practices have become more evident than ever. It plays a cruci...

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...