The International Journal of Remote Sensing and Earth Sciences (IJReSES)
Vol. 9 No. 2 (2012)

SEMI-AUTOMATIC SHIP DETECTION USING PI-SAR-L2 DATA BASED ON RAPID FEATURE DETECTION APPROACH

Katmoko Ari Sambodo (Unknown)



Article Info

Publish Date
26 Nov 2025

Abstract

Synthetic Aperture Radar (SAR) satellite an active sensor offering unique high spatial resolution regardless of weather conditions can operate both day and night time with wide area coverage. Therefore, SAR satellite can be used for monitoring ship on sea surface. This study showed on an alternative method for ship detection of SAR data using Pi-SAR-L2 (L-band, JAXA-Airborne SAR) data. The ship detection method is this study was consisted of eight main stages. After the Pi-SAR data was registered and speckle was filtered, then the land was masked using SRTM-DEM (Shuttle Radar Topography Mission-Digital Elevation Model) data since most ship detectors produced false detections when it applied to land areas. A ship sample image was then selected (cropped). The next step was to detect some unique keypoints of ship sample image using Speeded Up Robust Features (SURF) detector. The maximum distance (‘MaxDist’) of keypoints was also calculated. The same detector was then applied to whole Pi-SAR imagery to detect all possible keypoints. Then, for each detected keypoint, we calculated distance to other keypoint (‘Dist’). If ‘Dist’ was smaller than ‘MaxDist’, then we marked these two (or more) keypoints as neighboring keypoints. If the number of neighbor keypoints was equal or greater than two, finally we marked these keypoints as ‘Detected Ship’ (draw rectangle and show its geographic position). Results showed that our method can detect successfully 32 ‘possible ships’ from Pi-SAR-L2 data acquired on the area of North Sulawesi, Indonesia (August 8, 2012).

Copyrights © 2012






Journal Info

Abbrev

ijreses

Publisher

Subject

Earth & Planetary Sciences

Description

The International Journal of Remote Sensing and Earth Sciences (IJReSES), published by Badan Riset dan Inovasi Nasional (BRIN) in collaboration with the Ikatan Geografi Indonesia (IGI) and managed by the Department of Geography Universitas Indonesia, is a pivotal platform in the global dissemination ...