Article
Details
Citation
Lanz P, Marino A, Brinkhoff T, Koster F & Moller M (2021) The InflateSAR Campaign: Testing SAR Vessel Detection Systems for Refugee Rubber Inflatables. Remote Sensing, 13 (8), Art. No.: 1487. https://doi.org/10.3390/rs13081487
Abstract
Countless numbers of people lost their lives at Europe’s southern borders in recent years in the attempt to cross to Europe in small rubber inflatables. This work examines satellite-based approaches to build up future systems that can automatically detect those boats. We compare the performance of several automatic vessel detectors using real synthetic aperture radar (SAR) data from X-band and C-band sensors on TerraSAR-X and Sentinel-1. The data was collected in an experimental campaign where an empty boat lies on a lake’s surface to analyse the influence of main sensor parameters (incidence angle, polarization mode, spatial resolution) on the detectability of our inflatable. All detectors are implemented with a moving window and use local clutter statistics from the adjacent water surface. Among tested detectors are well-known intensity-based (CA-CFAR), sublook-based (sublook correlation) and polarimetric-based (PWF, PMF, PNF, entropy, symmetry and iDPolRAD) approaches. Additionally, we introduced a new version of the volume detecting iDPolRAD aimed at detecting surface anomalies and compare two approaches to combine the volume and the surface in one algorithm, producing two new highly performing detectors. The results are compared with receiver operating characteristic (ROC) curves, enabling us to compare detectors independently of threshold selection.
Keywords
constant false alarm rate (CFAR) detector; polarimetric detector; sub-look detector; vessel detection systems; ship detection; synthetic aperture radar (SAR); disaster mitigation
Journal
Remote Sensing: Volume 13, Issue 8
Status | Published |
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Publication date | 30/04/2021 |
Publication date online | 13/04/2021 |
Date accepted by journal | 04/04/2021 |
URL | http://hdl.handle.net/1893/32553 |
Publisher | MDPI AG |
eISSN | 2072-4292 |
People (1)
Associate Professor, Biological and Environmental Sciences