MRSS19 - Call for Papers


The importance of remote sensing for the observation of our Earth and other planets is continuously growing, especially since more and more spaceborne data has become freely available to the public via the Landsat and Sentinel missions. In order to reach the goal of remote sensing, i.e. to map our environment both semantically and topographically, methods and algorithms from fields such as signal processing, image processing, computer vision and machine learning need to be combined with sensor- and target-specific domain expertise. MRSS19 seeks to foster the development of approaches from those fields dedicated to remote sensing data analysis. In this context, the following topics shall be addressed:


  • Exploitation of high resolution space images
  • Semantic segmentation for object detection and land cover mapping
  • 3D reconstruction from remote sensing data
  • Geospatial data update and change detection
  • Super-resolution of imagery
  • Hyperspectral image processing
  • Information extraction from synthetic aperture radar (SAR)
  • Fusion of multi-sensor, multi-resolution and multi-temporal data
  • Feature extraction and machine learning for earth observation data
  • Neural networks and deep learning
  • Domain adaptation and transfer learning for remote sensing
  • Benchmark datasets for machine learning models
  • Large-scale mapping and big data
  • Rapid mapping for environmental applications and disaster management
  • Extraction of buildings, roads, and vegetation
  • Aplications in agriculture, forestry, hydrography, and geology
  • Small satellites and satellite constellations for mapping

Automated extraction of objects from remotely sensed data is an important topic of research in Computer Vision, Photogrammetry, Remote Sensing, and Geoinformation Science. In order to discuss recent developments and future trends in research and their influence on sensors and processing techniques, the two conferences Munich Remote Sensing Symposium (MRSS) and Photogrammetric Image Analysis (PIA) and will be held as a common event at TUM in Munich, Germany. The joint event addresses experts from research, government, and private industry. It consists of high quality papers, and provides an international forum for discussion of leading research and technological developments as well as applications in the field.