{"help":"https://catalogue.cioos.ca/api/3/action/help_show?name=package_show","success":true,"result":{"id":"a48161da-c603-43d6-9dc6-44b861984b49","ecv":[],"eov":["macroalgalCanopyCoverAndComposition"],"url":null,"name":"ca-cioos_7cafde4f-bdd5-4b95-a41d-7939ddcf08c6","tags":[],"type":"dataset","notes":"Ces fichiers de données représentent une série chronologique de la superficie du couvert végétal de varech géant, Macrocystis pyrifera, et de varech taureau, Nereocystis luetkeana, dérivée d'images Landsat corrigées sur le plan atmosphérique : Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI) et imagerie satellite Landsat 9 Operational Land Imager 2. Les observations sont effectuées sur un cycle de répétition de 16 jours, pour chaque instrument, mais la couverture temporelle est irrégulière en raison de la couverture nuageuse, de la défaillance de l'instrument et de la durée de la mission de chaque capteur (TM : 1984 — 2011, ETM+ : 1999 — présent, OLI : 2013 — présent). \n\nLa canopée de varech est composée de portions de frondes et de stipes flottant à la surface de l'eau. Les zones littorales (à moins d'un pixel Landsat, ~30 m) et les zones à marée basse (roches situées à proximité du rivage et au large) sont masquées au cours de ce processus. Par conséquent, la zone de canopée de varech dans ces zones est exclue de cet ensemble de données. Voir Bell et al. 2020 et 2023 pour plus de détails sur les méthodes. \n\nLes données sont organisées dans des fichiers géotif et contiennent les pourcentages trimestriels de détections pour chaque pixel Landsat sur les quatre capteurs. Par exemple, s'il y a 5 passes claires d'un pixel et que celui-ci a été classé comme varech dans 4 d'entre elles, la valeur du pixel est de 80. Les données de présence de varech sont fournies pour des pixels individuels de 30 x 30 mètres pour les zones côtières de la côte centrale de la Colombie-Britannique, au Canada. \n\nCes données sont appropriées pour étudier la dynamique du varech à de grandes échelles spatiales et il convient de tenir compte de leur utilisation pour toute analyse donnée. Les analyses à l'échelle locale pour lesquelles des données relatives à l'espèce sont nécessaires, ou lorsque le varech est frisonnant et clairsemé, devraient utiliser des images à plus haute résolution spatiale pour la cartographie (par exemple, relevés à voilure fixe ou relevés par drone). \n\nL'ensemble de données est actuellement mis à jour jusqu'en 2023 et est en cours de révision. Point de contact du jeu de données : Luba Reshitnyk, Henry Houskeeper et Tom Bell.\n\nPour une méthode détaillée, consultez ces articles :\n\nBell TW, Cavanaugh KC, Saccomanno VR, Cavanaugh KC, Houskeeper HF, Eddy N, et al. (2023) Kelpwatch : un nouvel outil de visualisation et d'analyse pour explorer la dynamique de la canopée de varech révèle une réponse et un rétablissement variables aux vagues de chaleur marines. PLoS ONE 18 (3) : e0271477. https://doi.org/10.1371/journal.pone.0271477\n\nBell, T. W., Allen, J. G., Cavanaugh, K. C. et Siegel, DA (2020). Trois décennies de variabilité dans les forêts de varech géantes de Californie à partir des satellites Landsat. Télédétection de l'environnement, 238, 110811.","state":"active","title":"Séries chronologiques de l'étendue trimestrielle de la canopée de varech à partir de Landsat 5, 7, 8 et 9 depuis 1985","author":null,"extras":[{"key":"access_constraints","value":""},{"key":"contact-email","value":"luba.reshitnyk@hakai.org"},{"key":"encoding","value":"utf8"},{"key":"guid","value":"ca.cioos_7cafde4f-bdd5-4b95-a41d-7939ddcf08c6"},{"key":"h_job_id","value":"ad51821a-c51c-4914-8e02-04a2de1575d7"},{"key":"h_object_id","value":"e1813a85-803b-4831-b198-443562dcb7b7"},{"key":"h_source_id","value":"9704fc28-20f2-4eb1-92d5-b5b47fc23354"},{"key":"h_source_title","value":"CIOOS Pacific"},{"key":"h_source_url","value":"https://catalogue.cioospacific.ca"},{"key":"harvest_object_id","value":"e1813a85-803b-4831-b198-443562dcb7b7"},{"key":"harvest_source_id","value":"9704fc28-20f2-4eb1-92d5-b5b47fc23354"},{"key":"harvest_source_organization","value":"{\"id\": \"f6f187f7-19f2-4273-a45a-5d9406204873\", \"name\": \"cioos-pacific\", \"title\": \"SIOOC-Pacifique\", \"type\": \"organization\", \"description\": \"\", \"image_url\": \"\", \"created\": \"2026-07-31T15:58:21.015456\", \"is_organization\": true, \"approval_status\": \"approved\", \"state\": \"active\", \"description_translated\": {\"en\": \"The Canadian Integrated Ocean Observing System (CIOOS) Pacific is the regional hub of the National CIOOS for ocean data aggregation on Canada\\u2019s west coast.\", \"fr\": \"Le Syst\\u00e8me int\\u00e9gr\\u00e9 d\\u2019observation des oc\\u00e9ans canadien (SIOOC) Pacifique est la plaque tournante r\\u00e9gionale du SIOOC national pour l\\u2019agr\\u00e9gation des donn\\u00e9es oc\\u00e9aniques sur la c\\u00f4te ouest du Canada.\"}, \"display_name\": \"CIOOS-Pacific\", \"external_home_url\": \"https://cioospacific.ca\", \"image_display_url\": \"\", \"image_url_translated\": {\"en\": \"https://catalogue.cioos.ca/base/images/logos/cioos-pacific_logo_RA_EN.png\", \"fr\": \"https://catalogue.cioos.ca/base/images/logos/cioos-pacific_logo_RA_FR.png\"}, \"num_followers\": 0, \"title_translated\": {\"en\": \"CIOOS-Pacific\", \"fr\": \"SIOOC-Pacifique\"}, \"organization-uri\": [{\"authority\": \"\", \"code\": \"\", \"code-space\": \"\", \"version\": \"\"}]}"},{"key":"harvest_source_title","value":"CIOOS Pacific"},{"key":"legal-constraints-reference-code","value":"CC-BY-4.0"},{"key":"licence","value":"These satellite-derived data are estimates of canopy area for canopy kelp forests 30 m from shore at a 30 m pixel representation (sensor resolution). These data therefore are not intended for use in examining nearshore (<30 m) kelp canopy extent and dynamics. These data do not differentiate between giant kelp (Macrocystis pyrifera) and bull kelp (Nereocystis luetkeana). Satellite overflight frequency changed over time."},{"key":"metadata-date","value":"2026-06-26T15:48:41.950Z"},{"key":"metadata_created_source","value":"2026-01-30T19:02:14.028612"},{"key":"metadata_modified_source","value":"2026-06-26T21:00:20.119705"},{"key":"responsible-party","value":"[{\"name\": \"Hakai Institute\", \"roles\": [\"author\", \"custodian\", \"pointOfContact\", \"owner\", \"distributor\"]}, {\"name\": \"Tula Foundation\", \"roles\": [\"funder\"]}]"},{"key":"spatial_harvester","value":"true"},{"key":"uri","value":"https://catalogue.hakai.org/dataset/ca-cioos_7cafde4f-bdd5-4b95-a41d-7939ddcf08c6"},{"key":"use-constraints","value":"These satellite-derived data are estimates of canopy area for canopy kelp forests 30 m from shore at a 30 m pixel representation (sensor resolution). These data therefore are not intended for use in examining nearshore (<30 m) kelp canopy extent and dynamics. These data do not differentiate between giant kelp (Macrocystis pyrifera) and bull kelp (Nereocystis luetkeana). Satellite overflight frequency changed over time."},{"key":"use-constraints-code","value":"licence"},{"key":"xml_modified_date","value":"2026-06-26 15:48:00"}],"groups":[{"id":"1b19a03b-cb31-4258-92b2-e1e2f74235ca","name":"resorg_hakai-institute","type":"resorg","state":"active","title":"Hakai Institute","created":"2026-07-31T16:03:25.855614","image_url":"","description":"","display_name":"Hakai Institute","num_followers":0,"approval_status":"approved","is_organization":false,"title_translated":{"en":"Hakai Institute","fr":"Hakai Institute"},"image_display_url":"","image_url_translated":{},"description_translated":{}},{"id":"d2c4272c-15f9-4fd8-9829-ac17f7580508","name":"resorg_woods-hole-oceanographic-institution","type":"resorg","state":"active","title":"Woods Hole Oceanographic Institution","created":"2026-07-31T16:17:37.699747","image_url":"","description":"","display_name":"Woods Hole Oceanographic 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\"https://doi.org/10.1016/j.rse.2018.06.039\", \"authority\": \"\", \"code-space\": \"\", \"version\": \"\"}, \"onlineResource\": {\"url\": \"https://doi.org/10.1016/j.rse.2018.06.039\", \"function\": \"\", \"name\": \"\", \"description\": \"\", \"protocol\": \"WWW:LINK\", \"protocol-request\": \"\", \"application-profile\": \"\", \"distribution-format\": [], \"distributor-format\": [], \"offline\": [], \"transfer-size\": \"\", \"units-of-distribution\": \"\"}, \"title_translation_method\": \"{\\\"en\\\": \\\"\\\", \\\"fr\\\": \\\"text translated using the Amazon translate service / texte traduit \\\\u00e0 l'aide du service de traduction Amazon\\\"}\"}"]},{"scope":"collectionSession","source":["{\"description\": \"{\\\"en\\\": \\\"Peer review paper\\\", \\\"fr\\\": \\\"Document d'\\\\u00e9valuation par les pairs\\\"}\", \"citation\": {\"title\": \"{\\\"en\\\": \\\"Kelpwatch: A new visualization and analysis tool to explore kelp canopy dynamics reveals variable response to and recovery from marine heatwaves\\\", \\\"fr\\\": \\\"Kelpwatch\\\\u00a0: un nouvel outil de visualisation et d'analyse pour explorer la dynamique de la canop\\\\u00e9e de varech r\\\\u00e9v\\\\u00e8le une r\\\\u00e9ponse et un r\\\\u00e9tablissement variables aux vagues de chaleur marines\\\"}\", \"identifier\": {\"code\": \"https://doi.org/10.1371/journal.pone.0271477\", \"authority\": \"\", \"code-space\": \"\", \"version\": \"\"}, \"onlineResource\": {\"url\": \"https://doi.org/10.1371/journal.pone.0271477\", \"function\": \"\", \"name\": \"\", \"description\": \"\", \"protocol\": \"WWW:LINK\", \"protocol-request\": \"\", \"application-profile\": \"\", \"distribution-format\": [], \"distributor-format\": [], \"offline\": [], \"transfer-size\": \"\", \"units-of-distribution\": \"\"}, \"title_translation_method\": \"{\\\"en\\\": \\\"\\\", \\\"fr\\\": \\\"text translated using the Amazon translate service / texte traduit \\\\u00e0 l'aide du service de traduction Amazon\\\"}\"}, \"description_translation_method\": \"{\\\"en\\\": \\\"\\\", \\\"fr\\\": \\\"text translated using the Amazon translate service / texte traduit \\\\u00e0 l'aide du service de traduction Amazon\\\"}\"}"],"statment":{"en":"Kelpwatch dataset","fr":"Ensemble de données Kelpwatch"},"processing-step":[],"additional-documentation":[]}],"private":false,"spatial":{"type":"Polygon","coordinates":[[[-130.5,54.75],[-133.5,54.36],[-133.0,53.09],[-126.0,48.92],[-123.6,48.28],[-123.2,48.8],[-123.8,49.61],[-127.6,51.04],[-128.4,52.4],[-130.4,54.24],[-130.5,54.75]]]},"citation":{"en":"[{\\\"type\\\": \\\"dataset\\\", \\\"id\\\": \\\"ca.cioos_7cafde4f-bdd5-4b95-a41d-7939ddcf08c6\\\", \\\"author\\\": [{\\\"given\\\": \\\"Luba\\\", \\\"family\\\": \\\"Reshitnyk\\\"}, {\\\"given\\\": \\\"Ashland\\\", \\\"family\\\": \\\"Aguilar\\\"}, {\\\"given\\\": \\\"Henry\\\", \\\"family\\\": \\\"Houskeeper\\\"}, {\\\"given\\\": \\\"Lauren\\\", \\\"family\\\": \\\"Man\\\"}, {\\\"given\\\": \\\"Tom\\\", \\\"family\\\": \\\"Bell\\\"}], \\\"issued\\\": [{\\\"date-parts\\\": [\\\"2026\\\", \\\"01\\\", \\\"27\\\"]}], \\\"abstract\\\": \\\"These data files represents a time series of surface kelp canopy area of giant kelp, Macrocystis pyrifera, and bull kelp, Nereocystis luetkeana, derived from atmospherically corrected Landsat imagery: Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), and Landsat 9 Operational Land Imager 2 satellite imagery. Observations are made on a 16 day repeat cycle, for each instrument, but the temporal coverage is irregular because of cloud cover, instrument failure, and the mission length of each sensor (TM: 1984 \\u2013 2011, ETM+: 1999 \\u2013 present, OLI: 2013 \\u2013 present). \\n\\nThe kelp canopy is composed of the portions of fronds and stipes floating on the surface of the water. Nearshore (within one Landsat pixel, ~30m) and low tide areas (both nearshore and offshore rocks) are masked during this process, therefore kelp canopy area within those areas are excluded in this dataset. See Bell et al. 2020 and 2023 for more details on methods. \\n\\nData are organized into geotif files and contain the quarterly percent detections for each Landsat pixel across the four sensors. For example, if there were 5 clear passes of a pixel, and it was classified as kelp in 4 of them, then the pixel value is 80. Kelp presence data are given for individual 30 x 30 meter pixels for coastal areas the Central Coast of British Columbia, Canada. \\n\\nThese data are suitable for investigating kelp dynamics at large spatial scales and consideration should be made in their use for any given analysis. Local-scale analyses where species level data are needed, or where kelp is fringing and sparse should use higher spatial resolution imagery for mapping (e.g. fixed-wing surveys or drone surveys). \\n\\nDataset currently updated through 2023 and is under review. Dataset point of contact: Luba Reshitnyk, Henry Houskeeper and Tom Bell.\\n\\nFor detailed method refer to these articles:\\n\\nBell TW, Cavanaugh KC, Saccomanno VR, Cavanaugh KC, Houskeeper HF, Eddy N, et al. (2023) Kelpwatch: A new visualization and analysis tool to explore kelp canopy dynamics reveals variable response to and recovery from marine heatwaves. PLoS ONE 18(3): e0271477. https://doi.org/10.1371/journal.pone.0271477\\n\\nBell, T.W., Allen, J.G., Cavanaugh, K.C., & Siegel, D.A. (2020). Three decades of variability in California's giant kelp forests from the Landsat satellites. Remote Sensing of Environment, 238, 110811.\\\", \\\"edition-date\\\": \\\"\\\", \\\"publisher\\\": \\\"Hakai Institute\\\", \\\"title\\\": \\\"Time series of quarterly kelp canopy extent from Landsat 5, 7, 8, and 9 since 1985\\\", \\\"version\\\": \\\"1.0\\\", \\\"DOI\\\": \\\"10.21966/xc7x-9207\\\", \\\"language\\\": \\\"en\\\", \\\"URL\\\": \\\"https://catalogue.hakai.org/dataset/ca-cioos_7cafde4f-bdd5-4b95-a41d-7939ddcf08c6?local=en\\\"}]","fr":"[{\\\"type\\\": \\\"dataset\\\", \\\"id\\\": \\\"ca.cioos_7cafde4f-bdd5-4b95-a41d-7939ddcf08c6\\\", \\\"author\\\": [{\\\"given\\\": \\\"Luba\\\", \\\"family\\\": \\\"Reshitnyk\\\"}, {\\\"given\\\": \\\"Ashland\\\", \\\"family\\\": \\\"Aguilar\\\"}, {\\\"given\\\": \\\"Henry\\\", \\\"family\\\": \\\"Houskeeper\\\"}, {\\\"given\\\": \\\"Lauren\\\", \\\"family\\\": \\\"Man\\\"}, {\\\"given\\\": \\\"Tom\\\", \\\"family\\\": \\\"Bell\\\"}], \\\"issued\\\": [{\\\"date-parts\\\": [\\\"2026\\\", \\\"01\\\", \\\"27\\\"]}], \\\"abstract\\\": \\\"Ces fichiers de donn\\u00e9es repr\\u00e9sentent une s\\u00e9rie chronologique de la superficie du couvert v\\u00e9g\\u00e9tal de varech g\\u00e9ant, Macrocystis pyrifera, et de varech taureau, Nereocystis luetkeana, d\\u00e9riv\\u00e9e d'images Landsat corrig\\u00e9es sur le plan atmosph\\u00e9rique\\u00a0: Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI) et imagerie satellite Landsat 9 Operational Land Imager 2. Les observations sont effectu\\u00e9es sur un cycle de r\\u00e9p\\u00e9tition de 16 jours, pour chaque instrument, mais la couverture temporelle est irr\\u00e9guli\\u00e8re en raison de la couverture nuageuse, de la d\\u00e9faillance de l'instrument et de la dur\\u00e9e de la mission de chaque capteur (TM\\u00a0: 1984 \\u2014 2011, ETM+\\u00a0: 1999 \\u2014 pr\\u00e9sent, OLI\\u00a0: 2013 \\u2014 pr\\u00e9sent). \\n\\nLa canop\\u00e9e de varech est compos\\u00e9e de portions de frondes et de stipes flottant \\u00e0 la surface de l'eau. Les zones littorales (\\u00e0 moins d'un pixel Landsat, ~30 m) et les zones \\u00e0 mar\\u00e9e basse (roches situ\\u00e9es \\u00e0 proximit\\u00e9 du rivage et au large) sont masqu\\u00e9es au cours de ce processus. Par cons\\u00e9quent, la zone de canop\\u00e9e de varech dans ces zones est exclue de cet ensemble de donn\\u00e9es. Voir Bell et al. 2020 et 2023 pour plus de d\\u00e9tails sur les m\\u00e9thodes. \\n\\nLes donn\\u00e9es sont organis\\u00e9es dans des fichiers g\\u00e9otif et contiennent les pourcentages trimestriels de d\\u00e9tections pour chaque pixel Landsat sur les quatre capteurs. Par exemple, s'il y a 5 passes claires d'un pixel et que celui-ci a \\u00e9t\\u00e9 class\\u00e9 comme varech dans 4 d'entre elles, la valeur du pixel est de 80. Les donn\\u00e9es de pr\\u00e9sence de varech sont fournies pour des pixels individuels de 30 x 30 m\\u00e8tres pour les zones c\\u00f4ti\\u00e8res de la c\\u00f4te centrale de la Colombie-Britannique, au Canada. \\n\\nCes donn\\u00e9es sont appropri\\u00e9es pour \\u00e9tudier la dynamique du varech \\u00e0 de grandes \\u00e9chelles spatiales et il convient de tenir compte de leur utilisation pour toute analyse donn\\u00e9e. Les analyses \\u00e0 l'\\u00e9chelle locale pour lesquelles des donn\\u00e9es relatives \\u00e0 l'esp\\u00e8ce sont n\\u00e9cessaires, ou lorsque le varech est frisonnant et clairsem\\u00e9, devraient utiliser des images \\u00e0 plus haute r\\u00e9solution spatiale pour la cartographie (par exemple, relev\\u00e9s \\u00e0 voilure fixe ou relev\\u00e9s par drone). \\n\\nL'ensemble de donn\\u00e9es est actuellement mis \\u00e0 jour jusqu'en 2023 et est en cours de r\\u00e9vision. Point de contact du jeu de donn\\u00e9es\\u00a0: Luba Reshitnyk, Henry Houskeeper et Tom Bell.\\n\\nPour une m\\u00e9thode d\\u00e9taill\\u00e9e, consultez ces articles\\u00a0:\\n\\nBell TW, Cavanaugh KC, Saccomanno VR, Cavanaugh KC, Houskeeper HF, Eddy N, et al. (2023) Kelpwatch\\u00a0: un nouvel outil de visualisation et d'analyse pour explorer la dynamique de la canop\\u00e9e de varech r\\u00e9v\\u00e8le une r\\u00e9ponse et un r\\u00e9tablissement variables aux vagues de chaleur marines. PLoS ONE 18 (3)\\u00a0: e0271477. https://doi.org/10.1371/journal.pone.0271477\\n\\nBell, T. W., Allen, J. G., Cavanaugh, K. C. et Siegel, DA (2020). Trois d\\u00e9cennies de variabilit\\u00e9 dans les for\\u00eats de varech g\\u00e9antes de Californie \\u00e0 partir des satellites Landsat. T\\u00e9l\\u00e9d\\u00e9tection de l'environnement, 238, 110811.\\\", \\\"edition-date\\\": \\\"\\\", \\\"publisher\\\": \\\"Hakai Institute\\\", \\\"title\\\": \\\"S\\u00e9ries chronologiques de l'\\u00e9tendue trimestrielle de la canop\\u00e9e de varech \\u00e0 partir de Landsat 5, 7, 8 et 9 depuis 1985\\\", \\\"version\\\": \\\"1.0\\\", \\\"DOI\\\": \\\"10.21966/xc7x-9207\\\", \\\"language\\\": \\\"fr\\\", \\\"URL\\\": \\\"https://catalogue.hakai.org/dataset/ca-cioos_7cafde4f-bdd5-4b95-a41d-7939ddcf08c6?local=fr\\\"}]"},"keywords":{"en":["oceans","remote-sensing","satellite","canopy-kelp","populations","british-columbia","landsat-5","landsat-7","landsat-8","landsat-9","macroalgalcanopycoverandcomposition","geospatial","nearshore"],"fr":["composition-et-couverture-de-la-canopee-de-macroalgues"]},"num_tags":0,"progress":"onGoing","projects":["Geospatial","Nearshore"],"owner_org":"f6f187f7-19f2-4273-a45a-5d9406204873","resources":[{"id":"1a1f4a41-c6bc-4238-a127-c4094d15b4a5","url":"https://hecate.hakai.org/auth/access-request.php?ref=https://doi.org/10.21966/xc7x-9207","hash":"","name":"Formulaire de demande d'accès aux données","size":null,"state":"active","format":"HTML","created":"2026-06-26T21:00:20.138658","mimetype":null,"position":0,"url_type":null,"cache_url":null,"package_id":"a48161da-c603-43d6-9dc6-44b861984b49","description":"Le jeu de données contient une géodatabase des caractéristiques matricielles des détections trimestrielles et annuelles de varech dérivées de la constellation de satellites Landsat (1985-2023).","last_modified":null,"resource_type":null,"created_source":"2026-06-26T21:00:20.138658","mimetype_inner":null,"name_translated":{"en":"Data Access Request Form","fr":"Formulaire de demande d'accès aux données"},"datastore_active":false,"metadata_modified":"2026-09-16T20:33:14.535303","cache_last_updated":null,"description_translated":{"en":"Compressed folder containing a geodatabase of .tif files for quarterly, annual kelp detections derived from the Landsat satellites constellation (1985-2023).","fr":"Le jeu de données contient une géodatabase des caractéristiques matricielles des détections trimestrielles et annuelles de varech dérivées de la constellation de satellites Landsat (1985-2023)."},"metadata_modified_source":"2026-06-26T21:00:20.129435","resource_locator_function":"","resource_locator_protocol":"WWW:LINK"}],"datacentre":[],"license_id":"CC-BY-4.0","maintainer":null,"distributor":[{"role":["distributor"],"individual-name":"","organisation-name":"Hakai 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Canadian Integrated Ocean Observing System (CIOOS) Pacific is the regional hub of the National CIOOS for ocean data aggregation on Canada’s west coast.","fr":"Le Système intégré d’observation des océans canadien (SIOOC) Pacifique est la plaque tournante régionale du SIOOC national pour l’agrégation des données océaniques sur la côte ouest du Canada."}},"license_title":"Creative Commons Attribution 4.0","num_resources":1,"resource-type":"dataset","bbox-east-long":"-123.2","bbox-north-lat":"48.28","bbox-south-lat":"54.75","bbox-west-long":"-133.5","creator_user_id":"fe6035ee-ed91-4ead-b5b2-4048232a22bb","temporal-extent":[{"begin":"1985-04-01"}],"vertical-extent":[{"max":"0","min":"0"}],"aggregation-info":[{"initiative-type":"","association-type":"dependency","aggregate-dataset-name":{"en":"SBC LTER: Time series of quarterly NetCDF files of kelp biomass in the canopy from Landsat 5, 7 and 8, since 1984 (ongoing)","fr":"SBC LTER : Séries chronologiques de fichiers NetCDF trimestriels sur la biomasse de varech dans la canopée à partir de Landsat 5, 7 et 8, depuis 1984 (en cours)"},"aggregate-dataset-identifier_code":"https://doi.org/10.6073/pasta/18874c2802c4defd4b331cac827676c5"},{"initiative-type":"","association-type":"dependency","aggregate-dataset-name":{"en":"KelpWatch Data","fr":"Données KelpWatch"},"aggregate-dataset-identifier_code":"https://kelpwatch.org/methodology"}],"maintainer_email":null,"maintenance-note":"Generated from https://hakaiinstitute.github.io/hakai-metadata-entry-form#/en/hakai/owhqxLMKaJdQBPGxgc2FH82HfLp1/-OZGbDlZ5dgF0dD-ceZ7","metadata_created":"2026-07-31T16:25:53.506176","notes_translated":{"en":"These data files represents a time series of surface kelp canopy area of giant kelp, Macrocystis pyrifera, and bull kelp, Nereocystis luetkeana, derived from atmospherically corrected Landsat imagery: Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), and Landsat 9 Operational Land Imager 2 satellite imagery. Observations are made on a 16 day repeat cycle, for each instrument, but the temporal coverage is irregular because of cloud cover, instrument failure, and the mission length of each sensor (TM: 1984 – 2011, ETM+: 1999 – present, OLI: 2013 – present). \n\nThe kelp canopy is composed of the portions of fronds and stipes floating on the surface of the water. Nearshore (within one Landsat pixel, ~30m) and low tide areas (both nearshore and offshore rocks) are masked during this process, therefore kelp canopy area within those areas are excluded in this dataset. See Bell et al. 2020 and 2023 for more details on methods. \n\nData are organized into geotif files and contain the quarterly percent detections for each Landsat pixel across the four sensors. For example, if there were 5 clear passes of a pixel, and it was classified as kelp in 4 of them, then the pixel value is 80. Kelp presence data are given for individual 30 x 30 meter pixels for coastal areas the Central Coast of British Columbia, Canada. \n\nThese data are suitable for investigating kelp dynamics at large spatial scales and consideration should be made in their use for any given analysis. Local-scale analyses where species level data are needed, or where kelp is fringing and sparse should use higher spatial resolution imagery for mapping (e.g. fixed-wing surveys or drone surveys). \n\nDataset currently updated through 2023 and is under review. Dataset point of contact: Luba Reshitnyk, Henry Houskeeper and Tom Bell.\n\nFor detailed method refer to these articles:\n\nBell TW, Cavanaugh KC, Saccomanno VR, Cavanaugh KC, Houskeeper HF, Eddy N, et al. (2023) Kelpwatch: A new visualization and analysis tool to explore kelp canopy dynamics reveals variable response to and recovery from marine heatwaves. PLoS ONE 18(3): e0271477. https://doi.org/10.1371/journal.pone.0271477\n\nBell, T.W., Allen, J.G., Cavanaugh, K.C., & Siegel, D.A. (2020). Three decades of variability in California's giant kelp forests from the Landsat satellites. Remote Sensing of Environment, 238, 110811.","fr":"Ces fichiers de données représentent une série chronologique de la superficie du couvert végétal de varech géant, Macrocystis pyrifera, et de varech taureau, Nereocystis luetkeana, dérivée d'images Landsat corrigées sur le plan atmosphérique : Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI) et imagerie satellite Landsat 9 Operational Land Imager 2. Les observations sont effectuées sur un cycle de répétition de 16 jours, pour chaque instrument, mais la couverture temporelle est irrégulière en raison de la couverture nuageuse, de la défaillance de l'instrument et de la durée de la mission de chaque capteur (TM : 1984 — 2011, ETM+ : 1999 — présent, OLI : 2013 — présent). \n\nLa canopée de varech est composée de portions de frondes et de stipes flottant à la surface de l'eau. Les zones littorales (à moins d'un pixel Landsat, ~30 m) et les zones à marée basse (roches situées à proximité du rivage et au large) sont masquées au cours de ce processus. Par conséquent, la zone de canopée de varech dans ces zones est exclue de cet ensemble de données. Voir Bell et al. 2020 et 2023 pour plus de détails sur les méthodes. \n\nLes données sont organisées dans des fichiers géotif et contiennent les pourcentages trimestriels de détections pour chaque pixel Landsat sur les quatre capteurs. Par exemple, s'il y a 5 passes claires d'un pixel et que celui-ci a été classé comme varech dans 4 d'entre elles, la valeur du pixel est de 80. Les données de présence de varech sont fournies pour des pixels individuels de 30 x 30 mètres pour les zones côtières de la côte centrale de la Colombie-Britannique, au Canada. \n\nCes données sont appropriées pour étudier la dynamique du varech à de grandes échelles spatiales et il convient de tenir compte de leur utilisation pour toute analyse donnée. Les analyses à l'échelle locale pour lesquelles des données relatives à l'espèce sont nécessaires, ou lorsque le varech est frisonnant et clairsemé, devraient utiliser des images à plus haute résolution spatiale pour la cartographie (par exemple, relevés à voilure fixe ou relevés par drone). \n\nL'ensemble de données est actuellement mis à jour jusqu'en 2023 et est en cours de révision. Point de contact du jeu de données : Luba Reshitnyk, Henry Houskeeper et Tom Bell.\n\nPour une méthode détaillée, consultez ces articles :\n\nBell TW, Cavanaugh KC, Saccomanno VR, Cavanaugh KC, Houskeeper HF, Eddy N, et al. (2023) Kelpwatch : un nouvel outil de visualisation et d'analyse pour explorer la dynamique de la canopée de varech révèle une réponse et un rétablissement variables aux vagues de chaleur marines. PLoS ONE 18 (3) : e0271477. https://doi.org/10.1371/journal.pone.0271477\n\nBell, T. W., Allen, J. G., Cavanaugh, K. C. et Siegel, DA (2020). Trois décennies de variabilité dans les forêts de varech géantes de Californie à partir des satellites Landsat. Télédétection de l'environnement, 238, 110811."},"title_translated":{"en":"Time series of quarterly kelp canopy extent from Landsat 5, 7, 8, and 9 since 1985","fr":"Séries chronologiques de l'étendue trimestrielle de la canopée de varech à partir de Landsat 5, 7, 8 et 9 depuis 1985"},"xml_location_url":"https://metadata-generator-proxy.server.hakai.app/metadata/hakai/time_series_of_quarterly_kelp__7cafd.xml","metadata-language":"en","metadata_modified":"2026-09-16T20:33:14.529553","frequency-of-update":"asNeeded","dataset-reference-date":[{"type":"creation","value":"1985-04-01"},{"type":"publication","value":"2026-01-27"}],"cited-responsible-party":[{"role":["author","custodian","pointOfContact"],"individual-name":"Reshitnyk, Luba","organisation-name":"Hakai 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