Introduction

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.

Workshop Topics

Contributions to all the issues related to multitemporal data processing, to the analysis of time series acquired by passive and active sensors and to the related applications are welcome, including:

• Multitemporal image analysis techniques
• Image registration, calibration and correction techniques
• Classification of multitemporal data
• Fusion and assimilation of multitemporal data
• Data mining and analysis of remote sensing time series
• Change detection methods
• Change detection accuracy assessment
• Multitemporal SAR and InSAR data analysis
• Multitemporal LiDAR data analysis
• Timelaps and multitemporal photogrammetric data analysis
• Land-cover and land-use dynamics
• Phenology product development and monitoring applications
• Applications of multitemporal data and time series
• Sea‐ice dynamics and cryospheric monitoring and modeling
• Ocean dynamics, modelling and prediction
• Water and ecosystem resources monitoring and modeling
• Environmental reclamation monitoring and modeling
• Drought monitoring and predictive modeling
• Vegetation dynamics and productivity
• Forestry and agriculture monitoring
• Stress and damage assessment
• New satellite missions for high temporal resolution time series
• New satellite missions for very high spatial resolution time series

Notice

The proceedings of the workshop will be published by IEEE and made available on IEEE Xplore Digital Library. Only accepted papers that will be presented at the Workshop in Annecy will be included in the proceedings.