MSc thesis topic: Analysing forest disturbance/recovery cycles in tropical forest ecosystems

This is of particular interest for studying tropical forest ecosystems, where historical information on the time and intensity of disturbance is often not available. Furthermore, currently ground data exists with limited historical disturbance information, which when coupled with remotely-sensed insights on forest disturbance, can shed light on the effect of disturbance on forest carbon (biomass) stocks.

This topic will aim to explore the effects that different disturbance events have on aboveground biomass in tropical forests. For this, you will explore forest disturbance/recovery dynamics through satellite time series analysis of one or more vegetation indices, and combine information on forest disturbance with ground data to assess the effect of disturbances on forest biomass.

Relevance to research/projects

This topic is relevant to (1) the satellite time-series development of the GRS group in general and (2) Daniela’s research on combining remote sensing techniques with forest plot data to study forest disturbance in tropical forest ecosystems.

Objectives

• Using one or more vegetation indices, map forest disturbance/recovery cycles using the AVOCADO algorithm (Decuyper et al, 2022).
• Combine RS-derived results on forest disturbances with spatial datasets (e.g. biomass maps)and ground data to analyse the effects that disturbances have on aboveground biomass.

Literature

• Decuyper, M., et al. (2022). Continuous monitoring of forest change dynamics with satellite time series.,, 112829.
• Requena Suarez, D. (2021). Variation in aboveground biomass in forests and woodlands in Tanzania along gradients in environmental conditions and human use. ,(4), p.044014.
• Bustamante, M.M. et al. (2016). Toward an integrated monitoring framework to assess the effects of tropical forest degradation and recovery on carbon stocks and biodiversity. Global change biology, 22(1), pp.92-109.

Requirements

• Knowledge of  tropical forest ecosystems

Theme(s): Sensing & measuring; Integrated Land Monitoring