Research

My Research

I study how biodiversity changes over time and space by analysing patterns in satellite-derived vegetation data. Plants grow, respond to climatic events, and recover from disturbance. Global vegetation has rhythms: seasonal cycles, multi-year fluctuations, and even less frequent patterns like El Niño. My research aims to detect these rhythms and understand what they reveal about ecosystem health.

To do this, I use wavelet analysis, a method that breaks time-series into their underlying cycles. Unlike traditional approaches, wavelets can show how patterns change through time, making them ideal for tracking vegetation dynamics over the past 25 years using global datasets such as MODIS EVI. 

This framework allows me to:

1. Identify annual, seasonal, and multi-year cycles in vegetation.

2. Detect changes in these cycles linked to climate variability or disturbance.

3. Compare vegetation patterns with environmental drivers using wavelet coherence, which shows whether two signals move together and how their relationship shifts over time.

4. Test and refine these methods using synthetic data to ensure they work reliably.

Ultimately, this research provides a flexible, scalable way to monitor biodiversity in a changing world. As ecological datasets become more consistent across time and space, wavelet-based tools offer a powerful path toward understanding ecosystem patterns that are otherwise hard to detect.