Visual Abstract

Visual abstract

Abstract

Remote sensing is an essential tool in efficiently gathering information about the Earth's surface on a global scale. This information can be used in various areas ranging from agriculture and forest management to battling the effects of heat islands in urban environments.

There are many satellite missions with various types of sensors measuring different metrics. All come with their advantages and disadvantages. One of the most common trade-offs in remote sensing is spatial vs. temporal resolution due to physical constraints.

This thesis explores the existing ways of enhancing the spatial resolution of land surface temperature (LST) images using environmental variables obtained at finer resolution. Additionally, we form and evaluate a hypothesis that chosen predictors that model anthropogenic heat flux will aid in improving the accuracy of the overall sharpening model.

Slides

Presentation slides in PowerPoint format

Lecture recording

Readings

[1] Firozjaei Mohammad Karimi et al., Satellite-derived land surface temperature spatial sharpening: A comprehensive review on current status and perspectives, European Journal of Remote Sensing, 2022, https://doi.org/10.1080/22797254.2022.2144764