Detection of ship tracks in ATSR2 satellite imagery
Ships modify cloud microphysics by adding cloud condensation nuclei (CCN) to a developing or existing cloud. These create lines of larger reflectance in cloud fields that are observed in satellite imagery. Ship tracks are most frequently seen off the west coast of California, and the Atlantic coast...
| Үндсэн зохиолчид: | , , |
|---|---|
| Бусад зохиолчид: | |
| Формат: | Journal article |
| Хэл сонгох: | English |
| Хэвлэсэн: |
Copernicus Publications
2008
|
| Нөхцлүүд: |
| _version_ | 1826301640526790656 |
|---|---|
| author | Campmany, E Grainger, D Dean, S |
| author2 | European Geosciences Union |
| author_facet | European Geosciences Union Campmany, E Grainger, D Dean, S |
| author_sort | Campmany, E |
| collection | OXFORD |
| description | Ships modify cloud microphysics by adding cloud condensation nuclei (CCN) to a developing or existing cloud. These create lines of larger reflectance in cloud fields that are observed in satellite imagery. Ship tracks are most frequently seen off the west coast of California, and the Atlantic coast of both west Africa and south-western Europe. In order to automate their detection within the Along Track Scanning Radiometer 2 (ATSR2) data set an algorithm was developed and integrated with the Global Retrieval of ATSR Cloud Parameters and Evaluation (GRAPE) processing chain. The algorithm firstly identifies intensity ridgelets in clouds which have the potential to be part of a ship track. This identification is done by comparing each pixel with its surrounding ones. If the intensity of three adjacent pixels is greater than the intensity of its neighbours, then it is classified as a ridgelet. These ridgelets are then connected together, according to a set of connectivity rules, to form tracks which are classed as ship tracks if they are long enough. The algorithm has been applied to two years of ATSR2 data. A month of results have been compared with other satellite datasets to validate the algorithm. There is a high ratio of false detections. Nevertheless the global distribution of ship tracks shows a similar pattern to the ship emissions distribution. |
| first_indexed | 2024-03-07T05:35:26Z |
| format | Journal article |
| id | oxford-uuid:e3bc4d6c-abd7-44e3-b0fb-c06f0986248a |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T05:35:26Z |
| publishDate | 2008 |
| publisher | Copernicus Publications |
| record_format | dspace |
| spelling | oxford-uuid:e3bc4d6c-abd7-44e3-b0fb-c06f0986248a2022-03-27T10:11:31ZDetection of ship tracks in ATSR2 satellite imageryJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:e3bc4d6c-abd7-44e3-b0fb-c06f0986248aAtmospheric,Oceanic,and Planetary physicsPhysicsEnglishOxford University Research Archive - ValetCopernicus Publications2008Campmany, EGrainger, DDean, SEuropean Geosciences UnionShips modify cloud microphysics by adding cloud condensation nuclei (CCN) to a developing or existing cloud. These create lines of larger reflectance in cloud fields that are observed in satellite imagery. Ship tracks are most frequently seen off the west coast of California, and the Atlantic coast of both west Africa and south-western Europe. In order to automate their detection within the Along Track Scanning Radiometer 2 (ATSR2) data set an algorithm was developed and integrated with the Global Retrieval of ATSR Cloud Parameters and Evaluation (GRAPE) processing chain. The algorithm firstly identifies intensity ridgelets in clouds which have the potential to be part of a ship track. This identification is done by comparing each pixel with its surrounding ones. If the intensity of three adjacent pixels is greater than the intensity of its neighbours, then it is classified as a ridgelet. These ridgelets are then connected together, according to a set of connectivity rules, to form tracks which are classed as ship tracks if they are long enough. The algorithm has been applied to two years of ATSR2 data. A month of results have been compared with other satellite datasets to validate the algorithm. There is a high ratio of false detections. Nevertheless the global distribution of ship tracks shows a similar pattern to the ship emissions distribution. |
| spellingShingle | Atmospheric,Oceanic,and Planetary physics Physics Campmany, E Grainger, D Dean, S Detection of ship tracks in ATSR2 satellite imagery |
| title | Detection of ship tracks in ATSR2 satellite imagery |
| title_full | Detection of ship tracks in ATSR2 satellite imagery |
| title_fullStr | Detection of ship tracks in ATSR2 satellite imagery |
| title_full_unstemmed | Detection of ship tracks in ATSR2 satellite imagery |
| title_short | Detection of ship tracks in ATSR2 satellite imagery |
| title_sort | detection of ship tracks in atsr2 satellite imagery |
| topic | Atmospheric,Oceanic,and Planetary physics Physics |
| work_keys_str_mv | AT campmanye detectionofshiptracksinatsr2satelliteimagery AT graingerd detectionofshiptracksinatsr2satelliteimagery AT deans detectionofshiptracksinatsr2satelliteimagery |