Research

My research interests connect remote sensing, vegetation phenology, and spatial analysis. The central question is how Earth-observation data can be translated into ecological evidence without losing sight of uncertainty and scale.

Current themes

Phenology from Earth observation

I am interested in retrieving seasonal vegetation dynamics from time-series data, comparing phenology indicators, and understanding what those indicators represent ecologically.

Spatial-scale effects

Patterns and relationships can change when observations are aggregated or resampled. I study how resolution and scale choices affect ecological inference and model interpretation.

Reproducible geospatial workflows

I use Python-based workflows for remote-sensing data preparation, spatial analysis, and transparent computational research.

Methods

• Time-series remote sensing
• Geospatial data processing
• Spatial statistics and scale analysis
• Reproducible scientific computing in Python