Hans Jarett Ong

Hans Jarett Ong

PhD candidate at NAIST specializing in Causal AI. My research connects theory with practical applications to build robust and fair AI systems, drawing on my experience deploying ML models.

Aerosol Types from 25 Southeast Asian AERONET Sites Obtained Using Specified Clustering and Mahalanobis Distance

Published in Japan Geoscience Union, Chiba, Japan, 2018

This presentation identifies aerosol types across 25 Southeast Asian AERONET sites using a 5-dimensional Mahalanobis distance classification.

Seven aerosol clusters were defined, including mineral dust, polluted dust, marine aerosols, and both white/dark biomass burning types.

Key findings:

  • Polluted dust (PD) and urban industrial developing (UID) were dominant in most sites.
  • Seasonal trends showed PD prevalent during dry months.
  • Biomass burning aerosols (BBW/BBD) were detected in September–October, linked to agricultural burning.

The methodology offers a scalable framework for regional aerosol monitoring using satellite and ground-based data.

Recommended citation: Ong, Hans Jarett J., et al. (2018). "Aerosol Types from 25 Southeast Asian AERONET Sites Obtained Using Specified Clustering and Mahalanobis Distance." Oral Presentation, Japan Geoscience Union.