Multi Temporal Data Processing

Processing of the multi-temporal images and change detection has been an active research field in the remote sensing for decades. Although plenty successful application cases have been reported on monitoring and detecting the environmental change, there are enormous challenges on applying the multi-temporal imagery to derive timely information on earth’s environment and human activities. In recent years, a great progress has been observed to overcome the technological obstacles by development of new platforms and sensors. The wider availability of the large archives of historical images are also makes long-term change detection and modelling possible. Such a development stimulates further investigation in developing more advanced image processing methods and the new approaches in handling image data in the time dimension. Over the past years, researchers have put forward large numbers of the   change detection techniques of the remote sensing image and summarized or classified them from different viewpoints. It has been generally agreed that the change detection is a complicated and integrated process. No existing approach is optimal and applicable to all cases. 


  • 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
  • Environmental reclamation monitoring and modeling
  • Vegetation dynamics and productivity
  • Water and ecosystem resources monitoring and modeling
  • New satellite missions for high temporal resolution time series
  • New satellite missions for very high spatial resolution time series

Related Conference of Multi Temporal Data Processing

Multi Temporal Data Processing Conference Speakers