http://repository.socib.es/repository/search/type/project_dataset2024-03-28T17:55:03ZHourly in situ data of ocean temperature in the near-shore Balearic Islands over 2012-2020http://repository.socib.es/repository/entry/show?entryid=d8ef9c99-50da-48fe-8e0a-6177bdb60d612021-12-01T18:04:31Z2021-12-11T17:07:41Z2021-12-01T18:04:31Z2021-12-01T18:04:31ZJuan Gabriel Fernándezhttp://repository.socib.es/repository/entry/showAlborexPerseus2014_LabSamplesNutrients_L1.nchttp://repository.socib.es/repository/entry/show?entryid=07ebf505-bd27-4ae5-aa43-c4d1c85dd5002018-12-19T16:26:19Z2021-12-01T18:11:07Z2018-12-19T16:26:19Z2018-12-19T16:26:19ZJuan Gabriel Fernándezhttp://repository.socib.es/repository/entry/showNumber of underway vessels in the Western Mediterranean (2016/01-2020/06)http://repository.socib.es/repository/entry/show?entryid=7108e550-63a2-4f77-8215-61061f52ac322020-07-20T17:13:54Z2021-12-01T18:10:33Z2020-07-20T17:13:54Z2020-07-20T17:13:54ZJuan Gabriel Fernándezhttp://repository.socib.es/repository/entry/show 545 million AIS messages). In addition to the vessel tracks, the database also included information associated with each vessel, such as the vessel type or length. A first pre-processing of the raw data included the removal of duplicates, invalid identification numbers (i.e. Maritime Mobile Service Identity -MMSI- codes without 9 digits) and codes outside the correct numerical range (i.e. MMSI codes with first digits between 2 and 7 are those intended for individual ships). In order to address inconsistencies in the vessel and MMSI combinations (e.g., changes of MMSI across years), we selected the more frequent combination of MMSI and vessel characteristics (e.g. vessel name and vessel type) for each calendar year. We used a similar vessel categorization as the S-AIS dataset, but were able to derive a sixth category from the AIS metadata, separating “recreational” vessels from “other” vessels. Therefore, vessels were classified into six categories: cargo, tanker, passenger (included high speed crafts and passenger vessels), fishing, recreational (included sailing vessels and pleasure crafts), and others (included all other ship types). We excluded ship type codes 20 to 29 (i.e. wing-in-ground-effect and search and rescue aircraft), as well as codes that had an invalid value (i.e. empty or null) or the value was not listed in the previous type codes. We calculated the number of vessels per day taking into account only those that were underway, thus removing moored vessels inside ports that were inactive. T-AIS coverage was not homogenous in the study area (Holmes et al. 2020) due to a non-uniformly distribution of antennas (i.e. few antennas in north Africa, see www.marinetraffic.com). Based on a previous analysis of the AIS coverage (Holmes et al 2020), we filtered vessels within the coastal zone (44.4 km, ~24 nautical miles) of EU countries (i.e. a total area of 164,318.2 km2 comprised by Spain, France and Italy), thus reducing potential bias due to temporal gaps in signal reception.
This home page contains all versions of this dataset.]]>Automatic Identification System (AIS)Big Data ResearchBlue EconomyCOVID-19 dataVessel Traffic Systemhuman mobilityocean healthA decade of morphodynamical data of a microtidal semiembayed beach, Cala Millorhttp://repository.socib.es/repository/entry/show?entryid=f27d7be3-783d-455b-b842-b07fdd8e2b1d2022-10-24T10:14:04Z2022-10-24T13:28:08Z2022-10-24T10:14:04Z2022-10-24T10:14:04ZFrancisco Fabián Criadohttp://repository.socib.es/repository/entry/show