The environmental challenges the world faces nowadays have never been greater or more
complex. Global areas covered by forests and urban woodlands are threatened by natural …

Abstract Machine learning (ML) has proven to be a powerful tool for utilizing the rapidly
increasing amounts of remote sensing data for environmental monitoring. Yet ML models …

Unmanned aerial vehicles (UAVs) or remotely piloted aircraft systems are new platforms that
have been increasingly used over the last decade in Europe to collect data for forest …

Wildfires represent a significant natural risk causing economic losses, human death and
environmental damage. In recent years, the world has seen an increase in fire intensity and …

Remote sensing images are useful for a wide variety of planet monitoring applications, from
tracking deforestation to tackling illegal fishing. The Earth is extremely diverse---the amount …

Coherent interconversion of signals between optical and mechanical domains is enabled by
optomechanical interactions. Extreme light-matter coupling produced by confining light to …

The challenge of wildfire management and detection is recently gaining increased attention
due to the increased severity and frequency of wildfires worldwide. Popular fire detection …

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

In the absence of effective and scalable human intervention, up to 95% of the world's
ecosystems will be affected by anthropogenic degradation by 2050. Therefore, immediate …

The number of scientific studies that consider possible applications of remotely piloted
aircraft systems (RPASs) for the management of natural hazards effects and the …