Thesis subject

MSc thesis topic: Data Fusion of Satellite and Weather Station Datafor Modelling Urban Heat Stress Mitigation by Green Infrastructure

Heat waves are becoming more frequent and intense across Europe, including the Netherlands, due to climate change. Urban Green Infrastructure (UGI), such as parks, green roofs, and tree-lined streets, is a key strategy for mitigating heat stress. However, accurately assessing its effectiveness requires high-resolution thermal data.

Background

Currently, remote sensing (e.g., Landsat, MODIS, Sentinel) provides Land Surface Temperature (LST) with both space and time, but limiting detailed microclimate analysis and UGI cooling. Conversely, weather station data offers precise air temperature measurements but patchy in both space and time. Fusing these datasets can enhance spatial accuracy and enable robust modelling of UGI’s cooling effects. This research aims to develop such an integrated approach to combine the strengths of station and satellite temperature data.

Relevance to research/projects at GRS or other groups

This study builds on two recent MSc projects supervised by Lixia at Environmental technology group. The two MSc projects examined microclimate impacts of UGI in Amsterdam and Berlin using weather station data. By incorporating satellite-derived LST, this work will extend those findings with:

  • Longer time-series analysis (combining historical satellite and weather data).
  • Higher spatial resolution (downscaling LST using station measurements).
  • Improved heat stress modelling.

Objectives and Research questions

Primary Objective:
Develop a data fusion framework integrating satellite LST and weather station data to model urban heat stress and quantify UGI cooling effects.

  • How can Land Surface Temperature (LST) from satellites (MODIS/Landsat/Sentinel) be downscaled using weather station data to improve accuracy?
  • How can fused satellite and station data improve urban heat stress modelling, particularly for UGI cooling effects?

Requirements

  • Are interested in the MODIS, Landsat or Sentinel data
  • Basic programming (Python/R for data analysis) is better.

Literature and information

Expected reading list before starting the thesis research

Theme(s): Sensing & measuring; Modelling & visualisation