Natural hazards can be likened to the Earth falling ill, with their manifestations classified into acute and chronic types based on onset patterns, symptom characteristics, and developmental trajectories. Acute natural hazards are characterized by their sudden onset, rapid progression, and severe immediate impacts, including landslides, earthquakes, floods, and wildfires. Chronic natural hazards tend to develop insidiously, progressing over long periods with ambiguous onset and multifactorial causes, as observed in phenomena such as land subsidence and sea level rise. Subacute hazards occupy an intermediate category, with symptom dynamics that are sufficiently complex to obscure clear diagnosis-often leading to misdiagnosis, under-detection, or even overtreatment-exemplified by permafrost degradation and thermokarst processes. This presentation showcases how we may harnessing remote sensing and AI to monitor the progression of these natural hazards and to unravel the complex mechanisms underlying their evolution.