This paper explores the evolution of geoscientific inquiry, tracing the progression from
traditional physics-based models to modern data-driven approaches facilitated by significant …

Extreme events such as heat waves and cold spells, droughts, heavy rain, and storms are
particularly challenging to predict accurately due to their rarity and chaotic nature, and …

Major advances in smartphones and tablets in terms of their built-in sensors (esp. cameras),
available computational power and on-board memory are transforming the role of such …

Multi-hazard susceptibility prediction is an important component of disasters risk
management plan. An effective multi-hazard risk mitigation strategy includes assessing …

Integrating Artificial Intelligence (AI) techniques with remote sensing holds great potential for
revolutionizing data analysis and applications in many domains of Earth sciences. This …

Exploration seismology uses reflected and refracted seismic waves, emitted from a
controlled (active) source into the ground, and recorded by an array of seismic sensors …

Vegetation phenology has been viewed as the nature's calendar and an integrative indicator
of plant‐climate interactions. The correct representation of vegetation phenology is important …

Geohazard prevention and mitigation are highly complex and remain challenges for
researchers and practitioners. Artificial intelligence (AI) has become an effective tool for …

Predicting the temperature, pressure, and permeability at depth is crucial for understanding
natural-state geothermal systems. As direct observations of these quantities are limited to …

Brain-inspired algorithms have become a new trend in next-generation artificial intelligence.
Through research on brain science, the intelligence of remote sensing algorithms can be …