Open AccessFishing boat detection using Sentinel-1 validated with VIIRS Data
Author(s) -
Marza Ihsan Marzuki,
Rinny Rahmania,
Penny Dyah Kusumaningrum,
Rudhy Akhwady,
Daud S.A. Sianturi,
Yustisia Firdaus,
Agus Sufyan,
Cecep Ahmad Hatori,
Handy Chandra
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/925/1/012058
Subject(s) - fishing , archipelago , remote sensing , constant false alarm rate , computer science , environmental science , geography , fishery , artificial intelligence , oceanography , geology , biology
Detecting fishing boat activity is still a challenge for the biggest archipelago countries, such as Indonesia, to monitor the huge marine area. Space technology using sensors SAR to detect ships has been developed since 1985. However, the cost of using SAR images is one of the barriers to operational aspects, mainly for detecting fishing boats to deter IUU fishing activities. This research aims to evaluate the use of Sentinel 1-SAR imagery for identifying fishing boats from space. We used VIIRS data for validating the purposes. Both data sources could be accessed freely. The object detection process can be derived into three steps: pre-processing, object detection and object validation. We used the constant false alarm rate (CFAR) method to discriminate against objects at sea. To identify fishing vessels, we used the size of the vessels and the intensity of light captured by VIIRS. According to the findings, 21 boats were discovered using sentinel 1-SAR imagery and four boats using VIIRS data based on the the area of interest.