Unsupervised learning (UL) has a long and successful history in untangling the complexity
of cities. As the counterpart of supervised learning, it discovers patterns from intrinsic data …

Abstract Machine learning presents opportunities for tracking evidence on climate change
adaptation, including text-based methods from natural language processing. In theory, such …

In the conditions of active socio-economic changes and reintegration of the economic
development of Ukraine, determining the place of agriculture in this process is relevant …

The multidimensional character of sustainable agriculture mandates a systematic
examination of this concept, necessitating methodological rigor for comprehensive analysis …

Despite its rising popularity, the novelty and merits of big data risk analysis are still debated.
This perspective article contributes to the debate by clarifying what constitutes big data in the …

Eight years after the first record in Italy, Kiwifruit Decline (KD), a destructive disease causing
root rot, has already affected more than 25% of the area under kiwifruit cultivation in Italy …

Providing adequate water supply to the growing number of urban residents will be a
challenge faced by many utility managers throughout the remainder of this century. Though …

Building community resilience in the face of climate disasters is critical to achieving a
sustainable future. Operational approaches to resilience favor systems' agile return to the …

This study aims to explore the application of artificial intelligence (AI) in the resolution of
sustainability challenges, with a specific focus on environmental studies. Given the rapidly …

Physical and societal risks across the natural, managed, and built environments are
becoming increasingly complex, multi-faceted, and compounding. Such risks stem from …