Programme - Topics

The MultiTemp bi-annual conference’s primary objective is to advance the knowledge on using EO time series to address a wide range of applications. Since its foundation in 2001, the scientific development in time series analysis has evolved from change detection methods to signal-processing methods, and from single-sensor approaches to multi-sensor synergy and fusion methods. This evolution originates from the technological development of sensor systems, the availability of a multitude of high quality EO data from a wide range of instruments, but also from evolving societal challenges that require different approaches and are reflected in more stringent user requirements.

These evolutions demand advanced methodologies, not only on the methods with which the EO time series are analysed, but also on the establishement of suitable EO time series  derived from from various instruments. Harmonization of the data sets from various sensors is therefore often needed. Another emerging requirement is the traceability and uncertainty characterization of the derived information from the time series. To be able to assess whether user requirements are met, appropriate validation strategies and adequate fiducial reference measurements are a prerequisite.

MultiTemp 2017 places the methodological improvements within the different application fields central, in order to facilitate the cross-fertilization between different approaches. We welcome scientists, students, representatives from national, European and international agencies, operational end-users and value adding industries to join this discussion.


Application fields that can be addressed are  

  • Climate
  • Agriculture
  • Hydro/cryosphere
  • Biodiversity and ecosystems
  • Land cover and land use dynamics
  • Forestry
  • Disaster assessment
  • Mapping
  • Water & coast

Contributions to all the issues related to multitemporal data processing, to the analysis of time series acquired by passive and active sensors at all ranges of spatial resolutions and to the related applications fields listed above are welcome, including:

  • Multitemporal image calibration, correction and registration techniques
  • Multitemporal image analysis techniques
  • Analysis of time series
  • Multitemporal SAR and InSAR data analysis
  • Big data mining
  • Data mining in time series
  • Change detection methods
  • Fusion of multitemporal data
  • Classification of multitemporal data
  • Phenology monitoring
  • New satellite missions for acquiring time series
  • Data harmonisation
  • Uncertainty propagation
  • Uptake of Sentinel missions
  • Synergetic use of different imaging systems
  • Validation approaches for multi-temporal data analysis