Remote sensing of ecosystems
The Remote Sensing of Ecosystems research group integrates environmental science and geoinformatics to better understand spatial and temporal effects on the ecological patterns we observe and the processes that create them. We do this in part by analysing both raw remote sensing observations (such as from satellites) and remote sensing-based data (such as from drones or autonomous sensors) to quantify ecosystem structure and function.
Ecosystem structure is the arrangement of different elements such as land cover or forest types across the landscape. Ecosystem function refers to the interactions between these structural elements and ecological processes (such as photosynthesis) or energy flows (such as land surface temperature).
Since ecosystems have an inherent complexity, we apply advanced machine learning algorithms to process large amounts of remote sensing observations for predictive modelling of ecological phenomena such as drought, or to extract information, such as plant biomass, from the data.
Our research has important implications for public policy. For example, climate change and changes in land cover and land use influence each other, as changes in land cover and land use (such as deforestation) drive climate change, e.g. land moving from sequestering carbon to becoming a carbon source.
In turn, climate change affects how people use ecosystems. We aim to better understand the interactions between these drivers and their impact on ecosystems, as they cause accelerating and sometimes destabilising feedbacks that can have consequences for society and biodiversity at local and global scales.
TreeSpec - Mapping of tree species through satellite observations
E-mail: hakim [dot] abdi [at] cec [dot] lu [dot] se (hakim[dot]abdi[at]cec[dot]lu[dot]se)