Research Directions & Ongoing Projects

🌍 Monitoring Ecosystem Dynamics from Space

Monitoring vegetation dynamics and ecosystem responses across the Mongolian Steppe using Earth Observation data and time-series analyses.


🔥 Fire Ecology and Ecosystem Responses in the Mongolian Steppe

🐟 Freshwater Biodiversity Monitoring

European freshwater macroinvertebrate richness trend explorer.

🔗 Launch Shiny App


Interactive exploration of freshwater biodiversity patterns and temporal trends across Europe.


🚗 Human Mobility and Urban Socio-Ecological Systems

Exploratory implementation of MATSim to simulate mobility patterns across Munich and investigate potential links between human movement, accessibility, and urban socio-ecological systems.



On going project

MORE STEP – Mobility at risk: Sustaining the Mongolian Steppe Ecosystem Website

This is a collaborative and interdisciplinary research project of Mongolian and German partners funded by the German Federal Ministry of Education and Research.

Finished project

Air Surface Temperature (Ta) Estimation using MODIS LST

Phan et al. (2016)
Selected the best predictors for daily max/min Ta estimation
Phan et al. (2017)
Compared linear models vs. Machine Learning (Random Forest)
Phan & Kappas (2018)
Systematic Review & Meta-analysis of MODIS LST applications
Phan et al. (2019)
Investigated LST data quantity & quality for Ta estimation

Machine Learning Approaches for Land Cover Classification and Mapping

Phan & Kappas (2018)
(Highly Cited Paper)
A comparative analysis of multiple machine learning algorithms and related techniques for high-accuracy land cover classification.

Phan et al. (2020)
(Highly Cited Paper)
Investigates the impact of image composition strategies on land cover classification performance.

Phan et al. (2022)
Proposes a simple, fast, and accurate method for large-scale land cover mapping.