DIGITAL

39th annual EARSeL Symposium

"DIGITAL | EARTH | OBSERVATION"

01.07.2019 - 04.07.2019

09:00 - 18:00

University of Salzburg

Faculty of Natural Sciences

Symposium

EARSeL is a scientific network of European remote sensing institutes, coming from both academia and the commercial/industrial sector. The 39th annual EARSeL Symposium - subtitled "DIGITAL | EARTH | OBSERVATION" - will explore the challenges and opportunities of recent technical transformations in Earth Observation. It will address topics such as big data, machine learning, data cubes, cloud processing, Copernicus missions and many more... Researchers from DIGITAL and their science partners are presenting results from recent EO projects in poster sessions and oral presentations.

 

ORAL PRESENTATIONS:

 

Using Multiple Along and Across Track Pleiades Stereo Images for Improved Digital Surface Model Generation

Roland Perko, Manuela Hirschmugl, Janik Deutscher, Mathias Schardt (JOANNEUM RESEARCH, Austria),

Markus Hollaus (Technical University of Vienna, Austria),

Peter M. Roth (Graz University of Technology, Austria)

 

Using Time Series of Sentinel-2 Data to Improve Alpine Forest Map Products

Janik Deutscher, Martin Puhm, Andreas Wimmer, Klaus Granica, Mathias Schardt (JOANNEUM RESEARCH, Austria)

 

POSTERS:

 

Employing Copernicus data and Time Series Analysis for the Identification and Promotion of Underutilised Lands for Bioenergy Production

Manuela Hirschmugl, Carina Sobe, Mathias Schardt (JOANNEUM RESEARCH, Austria),

Cosette Khawaja, Rainer Janssen, Dominik Rutz (WIP Renewable Energies, Germany),

Marie-Alice Budniok (European Landowners' Organization, Belgium),

Alfonso Calera, David Cifuentes (Universidad de Castilla – La Mancha, Spain),

Marco Colangeli, Michela Morese, Lorenzo Traverso (Food and Agriculture Organization of the United Nations, Italy)

 

Near Real-Time Change Detection in Forest Areas Using Kalman Filtering

Martin Puhm, Andreas Wimmer, Mathias Schardt (JOANNEUM RESEARCH, Austria)

 

Symposium Programme

EARSeL

Remote Sensing and Geoinformation @ DIGITAL