Moien Rangzan

Moien Rangzan is a Researcher at the Max Planck Institute for Biogeochemistry, affiliated with the International Max Planck Research School for Global Biogeochemical Cycles (IMPRS-gBGC) and the Biogeochemical Integration (BGI) department. His work focuses on cutting-edge applications of remote sensing and machine learning.

Research interests include:

• Remote Sensing (SAR, LiDAR)
• Deep Learning for Environmental Sciences
• Explainable AI (XAI) in Earth Observation
• Foundation Models for Spatio-temporal Analysis
• Digital Soil Mapping

Recent publications highlight his contributions to:

• Transformer-based frameworks for soil carbon prediction
• Optical-to-SAR translation techniques
• Frequency domain approaches for satellite image denoising

His technical expertise spans spatio-temporal modeling, GANs, and attention mechanisms applied to environmental data.

Current projects include:

• SoilNet - A framework for soil property prediction
• TemporalGAN - Optical-to-SAR translation GAN
• Wave-AR - Wave polarization augmented reality
• CropMapping - Time series satellite image analysis