Automatic Boat Identification System for VIIRS Low Light Imaging Data
The ability for satellite sensors to detect lit fishing boats has been known since the 1970s. However, the use of the observations has been limited by the lack of an automatic algorithm for reporting the location and brightness of offshore lighting features arising from boats. An examination of lit...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2015-03-01
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| Series: | Remote Sensing |
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| Online Access: | http://www.mdpi.com/2072-4292/7/3/3020 |
| _version_ | 1818321337865732096 |
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| author | Christopher D. Elvidge Mikhail Zhizhin Kimberly Baugh Feng-Chi Hsu |
| author_facet | Christopher D. Elvidge Mikhail Zhizhin Kimberly Baugh Feng-Chi Hsu |
| author_sort | Christopher D. Elvidge |
| collection | DOAJ |
| description | The ability for satellite sensors to detect lit fishing boats has been known since the 1970s. However, the use of the observations has been limited by the lack of an automatic algorithm for reporting the location and brightness of offshore lighting features arising from boats. An examination of lit fishing boat features in Visible Infrared Imaging Radiometer Suite (VIIRS) day/night band (DNB) data indicates that the features are essentially spikes. We have developed a set of algorithms for automatic detection of spikes and characterization of the sharpness of spike features. A spike detection algorithm generates a list of candidate boat detections. A second algorithm measures the height of the spikes for the discard of ionospheric energetic particle detections and to rate boat detections as either strong or weak. A sharpness index is used to label boat detections that appear blurry due to the scattering of light by clouds. The candidate spikes are then filtered to remove features on land and gas flares. A validation study conducted using analyst selected boat detections found the automatic algorithm detected 99.3% of the reference pixel set. VIIRS boat detection data can provide fishery agencies with up-to-date information of fishing boat activity and changes in this activity in response to new regulations and enforcement regimes. The data can provide indications of illegal fishing activity in restricted areas and incursions across Exclusive Economic Zone (EEZ) boundaries. VIIRS boat detections occur widely offshore from East and Southeast Asia, South America and several other regions. |
| first_indexed | 2024-12-13T10:39:18Z |
| format | Article |
| id | doaj.art-cc502b214d07404ab362cecc1f83b130 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-12-13T10:39:18Z |
| publishDate | 2015-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-cc502b214d07404ab362cecc1f83b1302022-12-21T23:50:36ZengMDPI AGRemote Sensing2072-42922015-03-01733020303610.3390/rs70303020rs70303020Automatic Boat Identification System for VIIRS Low Light Imaging DataChristopher D. Elvidge0Mikhail Zhizhin1Kimberly Baugh2Feng-Chi Hsu3Earth Observation Group, NOAA National Geophysical Data Center, 325 Broadway, Boulder, CO 80305, USACooperative Institute for Research in the Environmental Sciences, University of Colorado, Boulder, CO 80303, USACooperative Institute for Research in the Environmental Sciences, University of Colorado, Boulder, CO 80303, USACooperative Institute for Research in the Environmental Sciences, University of Colorado, Boulder, CO 80303, USAThe ability for satellite sensors to detect lit fishing boats has been known since the 1970s. However, the use of the observations has been limited by the lack of an automatic algorithm for reporting the location and brightness of offshore lighting features arising from boats. An examination of lit fishing boat features in Visible Infrared Imaging Radiometer Suite (VIIRS) day/night band (DNB) data indicates that the features are essentially spikes. We have developed a set of algorithms for automatic detection of spikes and characterization of the sharpness of spike features. A spike detection algorithm generates a list of candidate boat detections. A second algorithm measures the height of the spikes for the discard of ionospheric energetic particle detections and to rate boat detections as either strong or weak. A sharpness index is used to label boat detections that appear blurry due to the scattering of light by clouds. The candidate spikes are then filtered to remove features on land and gas flares. A validation study conducted using analyst selected boat detections found the automatic algorithm detected 99.3% of the reference pixel set. VIIRS boat detection data can provide fishery agencies with up-to-date information of fishing boat activity and changes in this activity in response to new regulations and enforcement regimes. The data can provide indications of illegal fishing activity in restricted areas and incursions across Exclusive Economic Zone (EEZ) boundaries. VIIRS boat detections occur widely offshore from East and Southeast Asia, South America and several other regions.http://www.mdpi.com/2072-4292/7/3/3020VIIRSday/night bandDNBnighttime lightsfishing boatsboat detection |
| spellingShingle | Christopher D. Elvidge Mikhail Zhizhin Kimberly Baugh Feng-Chi Hsu Automatic Boat Identification System for VIIRS Low Light Imaging Data Remote Sensing VIIRS day/night band DNB nighttime lights fishing boats boat detection |
| title | Automatic Boat Identification System for VIIRS Low Light Imaging Data |
| title_full | Automatic Boat Identification System for VIIRS Low Light Imaging Data |
| title_fullStr | Automatic Boat Identification System for VIIRS Low Light Imaging Data |
| title_full_unstemmed | Automatic Boat Identification System for VIIRS Low Light Imaging Data |
| title_short | Automatic Boat Identification System for VIIRS Low Light Imaging Data |
| title_sort | automatic boat identification system for viirs low light imaging data |
| topic | VIIRS day/night band DNB nighttime lights fishing boats boat detection |
| url | http://www.mdpi.com/2072-4292/7/3/3020 |
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