Leipzig is a vibrant hotspot for creativity in eastern Germany, known for its world-class research in biodiversity and ecosystem research and related areas. The Faculty of Physics and Earth System Sciences at Leipzig University and the Helmholtz Centre for Environmental Research (UFZ) haved teamed up and established the Remote Sensing Centre for Earth System Research to expand research in this area and better understand ecosystems in a changing world
How will geo- and ecosystem functions respond to the global environmental and societal transformations?
What are the spatiotemporal dynamics of change in the land-atmosphere water, energy, and carbon feedback systems?
How can we quantify and assess Biodiversity-Ecosystem-Functioning (BEF) relationships across scales?
How can we best integrate remote sensing techniques and modeling frameworks to improve our understanding of the Earth system?
Answering fundamental research questions of this kind and developing the right tools for this endeavour is the scientific mission of the RSC4Earth. Also key to our mission is preparing the next generation of Earth system sciences for addressing this quest.
A ready-to-use curated list of Spectral Indices for Remote Sensing applications.
COping CAPacity of nations facing systemic crisis – a global intercomparison exploring the SARS-CoV-2 pandemic.
Easily create EO mini cubes from STAC in Python.
Develop and test novel artificial intelligence explanatory tools to decipher compound events (e.g., drought and heatwave) based on “mini-cubes” with high spatial resolution.
This project aims to create an holistic datacube with latent space variables based on Sentinel-2 spectral indices
Develop a near real-time forest monitoring concept and capitalize on latest advances in AI for predicting major impacts of climate extremes.
The Earth System Data Lab is a virtual laboratory providing global earth observation data sets and processing tools.
Establishing a national forest monitor to assess and visualise vegetation condition for a better risk-management of German forests.
Deliver novel AI techniques for earth observation satellite data for studies in earth and climate sciences
The project MoDEV (Model-Data fusion for understanding Environmental Variability) investigates the interplay between carbon and water cycles for three biomes: forest, grassland and agriculture with special focus on the impacts of extreme hydrologic and climatic events as well their long-term trends.
Deliver practical tools for researchers and improve data availability for environmental studies/ecology.
Addresses the digital needs of researchers in Earth System Sciences with the aim to understand the functioning of all subsystems of the Earth system and their interactions.
Biodiversity effects on Plant-Atmosphere interactions analysed with Remote Sensing (PARSe Biodiversity)
Project to derive long-term, near-global ground heat flux estimates from satellite remote sensing data. These estimates will improve our understanding of the recent changes in subsurface conditions and will allow to estimate global changes in ground heat storage during the last 10 to 20 years
Time-varying AI-based mapping of ecosystem conditions and extents using multi-source Earth observation data cubes - TEE cube
The Virtual Lab provides computing infrastructure for teaching.