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A SAR ship dataset for detection, discrimination and analysis

Abstract: 

Synthetic Aperture Radar is a monitoring solution which is especially well fitted to maritime surveillance. The large swath widths, time-independent, weather resistant observations can be very useful for the detection of ships typically invisible to other forms of monitoring. A dataset which contains 43 Sentinel-1 Extended Wide Swath images and 3 RADARSAT-2 ScanSAR Narrow images between the 6th October 2014 to the 22 July 2015 is described and presented here. These images cover a large percentage of the South African Exclusive Economic Zone using multiple polarisations and three different resolutions. A detailed description of the dataset is given including: the entire generation process from the original compressed data to the geocoded images; the dataset organisational structure tailored to each step of the ship detection process; ship referencing and attribute extraction procedures; supplementary Automatic Identification System transponder information and matching; and ship reference and Automatic Identification System matched ship attribute analysis. A number of novel components are introduced, including a three-class discrimination dataset component which helps provide a more granular approach to ship discrimination performance analysis. The aim of the dataset is to introduce a single Synthetic Aperture Radar dataset which covers a wide range of possible requirements for scientific ship detection method analysis using the newest Synthetic Aperture Radar imagery available. The dataset held here is only the discrimination dataset and the authors can be contacted for the full set of SAR imagery. 

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Dataset Details

Citation Author(s):
C. P. Schwegmann, W. Kleynhans, B. P. Salmon, L. W. Mdakane, R. G. V. Meyer
Submitted by:
Colin Schwegmann
Last updated:
Mon, 10/16/2017 - 09:38
DOI:
10.21227/H2RK82
Data Format:
Links:
 
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[1] C. P. Schwegmann, W. Kleynhans, B. P. Salmon, L. W. Mdakane, R. G. V. Meyer, "A SAR ship dataset for detection, discrimination and analysis", IEEE Dataport, 2017. [Online]. Available: http://dx.doi.org/10.21227/H2RK82. Accessed: Nov. 24, 2017.
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doi = {10.21227/H2RK82},
url = {http://dx.doi.org/10.21227/H2RK82},
author = {C. P. Schwegmann; W. Kleynhans; B. P. Salmon; L. W. Mdakane; R. G. V. Meyer },
publisher = {IEEE Dataport},
title = {A SAR ship dataset for detection, discrimination and analysis},
year = {2017} }
TY - DATA
T1 - A SAR ship dataset for detection, discrimination and analysis
AU - C. P. Schwegmann; W. Kleynhans; B. P. Salmon; L. W. Mdakane; R. G. V. Meyer
PY - 2017
PB - IEEE Dataport
UR - 10.21227/H2RK82
ER -
C. P. Schwegmann, W. Kleynhans, B. P. Salmon, L. W. Mdakane, R. G. V. Meyer. (2017). A SAR ship dataset for detection, discrimination and analysis. IEEE Dataport. http://dx.doi.org/10.21227/H2RK82
C. P. Schwegmann, W. Kleynhans, B. P. Salmon, L. W. Mdakane, R. G. V. Meyer, 2017. A SAR ship dataset for detection, discrimination and analysis. Available at: http://dx.doi.org/10.21227/H2RK82.
C. P. Schwegmann, W. Kleynhans, B. P. Salmon, L. W. Mdakane, R. G. V. Meyer. (2017). "A SAR ship dataset for detection, discrimination and analysis." Web.
1. C. P. Schwegmann, W. Kleynhans, B. P. Salmon, L. W. Mdakane, R. G. V. Meyer. A SAR ship dataset for detection, discrimination and analysis [Internet]. IEEE Dataport; 2017. Available from : http://dx.doi.org/10.21227/H2RK82
C. P. Schwegmann, W. Kleynhans, B. P. Salmon, L. W. Mdakane, R. G. V. Meyer. "A SAR ship dataset for detection, discrimination and analysis." doi: 10.21227/H2RK82