Paper
6 August 2018 From a change detection image to an operational alert system with Sentinel-1 time series
Bénédicte Navaro, Angela Trabelsi, Nicolas Saporiti
Author Affiliations +
Proceedings Volume 10773, Sixth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2018); 107730G (2018) https://doi.org/10.1117/12.2326221
Event: Sixth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2018), 2018, Paphos, Cyprus
Abstract
Full automatic change detection is a great challenge for many institutions, and many teams are involved in it: teams in charge of monitoring designated sites, teams in charge of imagery acquisition, and teams producing maps. The large availability and repetitiveness of free Sentinel-1 imagery appears like an opportunity to monitor change detection on designated sites or on larger areas. This paper presents a change detection workflow built on SNAP and Sentinel-1 time series answering operational needs: automation, scalability and usable information. It also details the tests drove on various sites and changing contexts (refugee camps, airport infrastructures, earth wall, etc.). The robustness of the process is discussed, the way to move from site monitoring to a whole regional area change detection and how external data and post-processing on a change detection image can strengthen the process in order to provide an operational full automatic alert service.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Bénédicte Navaro, Angela Trabelsi, and Nicolas Saporiti "From a change detection image to an operational alert system with Sentinel-1 time series", Proc. SPIE 10773, Sixth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2018), 107730G (6 August 2018); https://doi.org/10.1117/12.2326221
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KEYWORDS
Image processing

Synthetic aperture radar

Satellites

Composites

Radar

Visual analytics

Visualization

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