After 40 years of Earth Observation missions with both passive (multispectral, hyperspectral, etc.) and active (synthetic aperture radar, lidar, etc.) sensors, remote sensing data offer a unique opportunity to record, to analyze and to predict the evolution of our living planet. In the last decade, a large number of new satellite remote sensing missions have been launched, resulting in dramatic improvement in the image acquisition capabilities. The successful launching of the Sentinel-1 in 2014 and the launching of the coming satellites of the Copernicus program, with regular acquisition plans and free data access policy, result in new challenge for handling and processing such huge volume of data. This increasing number of Earth Observation systems involves an enhanced possibility to acquire multitemporal images of the Earth surface, with improved temporal and spatial resolution. Such new scenario significantly increases the interest of the time series processing in the remote sensing community. The development of novel data processing techniques to address new important and challenging applications seems promising.
Nonetheless, the properties of the images acquired by the last generation sensors (e.g. very high spatial resolution, long time series, etc.) raise new methodological problems that require the development of new methods for the analysis of multitemporal data. The potential of the technological development is strengthened with the increasing awareness of the importance of monitoring the Earth surface at local, regional and global scale. Assessing, monitoring and predicting the dynamics of natural land covers and of antrophic processes is on the basis of both the understanding of the problems related to climate changes and the definition of politics for sustainable development.
In the context of "Big Data” encountered in the remote sensing community, the objective of MultiTemp 2015 provides a scientific forum of discussions for methodology and application issues related to multitemporal data analysis. The workshop aims to propose novel solutions for technical problems related to the analysis of multitemporal data, to promote the use of the multitemporal images in an ever increasing number of strategic and challenging applications and to strengthen the connections between the scientists and the end-users. In this perspective, contributions are welcome from the methodological community dealing with novel technologies and methods for data analysis, as well as from the application sectors focusing on the use of multitemporal data in practical settings.
Cryosphere and global change
Frank Paul, University of Zurich, Switzerland
Ranga Raju Vatsavai, North Carolina State University, USA
Hervé Yesou, University of Strasbourg, France
Inverse Problems and Data Assimilation
Olivier Talagrand, Ecole Normale Supérieure, France
Multisource data for ecosystem monitoring
Michael Förster, Technical University of Berlin, Germany
SAR data analysis for ground monitoring
Michael Eineder, DLR, Germany
Olivier Hagolle, CNES, France
Urban analysis and monitoring
Florence Tupin, Télécom ParisTech, France
The general topics of the workshop will cover: