Multi-Sensor Data Fusion and Analysis of Multi-Temporal Remote Sensed Imagery

Dear Colleagues,

The increasing amount of freely available satellite data is attracting new users outside the scientific community. Currently, we are experiencing a democratization of the Earth Observation (EO) data, which is largely due to the Copernicus Sentinel and NASA Landsat missions, as well as to the recent and rapid development of unmanned aircraft systems. At the same time, this plethora of satellite data offers new possibilities and challenges for EO scientists and experts. On one hand, the short revisit time (high temporal resolution) of the new generation satellite imagers allows the enhancement of multi-temporal analysis; on the other hand, the large variability of remote sensing data raises the issue of the implementation of data fusion techniques for big data. This variability concerns the type of sensor (optical, SAR, thermal, LIDAR, etc.), as well as the platform on which the sensor is placed (spaceborne, airborne, UAV). Multi-sensor data fusion techniques allow data from different sources to be combined, enriching and enhancing EO time series and, consequently, improving multi-temporal analysis.

This Special Issue will present a collection of valuable and rigorous research works that advance current knowledge on the multi-temporal and multi-source analysis of remote sensed imagery.

Specific topics include, but are not limited to

• Multi-temporal image pre-processing and harmonization;
• Implementation of multi-sensor and multi-temporal data fusion techniques;
• Multi-temporal image analysis for the monitoring of dynamic factors, trend analysis, classification, clustering, and regression.

The above-listed topics can be applied to several dynamic applications (agriculture, geomorphology, soil, marine and freshwater environments, forest, land use change, biodiversity, climate change, environmental disasters, etc.). Any kind of sensor data (optical, SAR, LIDAR, TIR, etc.), as well as any kind of spectral, radiometric, spatial, or temporal resolution can be considered. The choice of papers for publication will be based on quality, soundness, and rigor of research.

Dr. Fabio Castaldi
Dr. Anne Gobin
Dr. Simone Pascucci
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.