2785c103-9c2d-429b-9f3d-89f5cd9ea94d eng; CAN utf8; utf8 dataset; jeuDonnées Dr. Michael A. Wulder Government of Canada; Natural Resources Canada; Service canadien des forêts Gouvernement du Canada; Ressources naturelles Canada Research Scientist Chercheur 250-298-2401 250-298-2401 250-363-0775 506 W. Burnside Road 506 rue Burnside Ouest Victoria British Columbia Colombie-Britannique V8Z1M5 Canada Canada mike.wulder@canada.ca mike.wulder@canada.ca https://cfs.nrcan.gc.ca/employes/vue/mwulder http email only please courriel seulemente svp principalInvestigator; chercheurPrincipal 2026-02-17T09:22:45 North American Profile of ISO 19115:2003 - Geographic information - Metadata Profil nord-américain de la norme ISO 19115:2003 - Information géographique - Métadonnées CAN/CGSB-171.100-2009 French; Français Canada; Canada utf8; utf8 EPSG:3978 http://www.epsg-registry.org 1.0 Annual High-resolution forest land cover for Canada (1984-2022) Couverture forestière annuelle à haute résolution pour le Canada (1984-2022) 2025-12-16 publication; publication 2025-12-16 creation; création Dr. Michael A. Wulder Government of Canada; Natural Resources Canada; Service canadien des forêts Gouvernement du Canada; Ressources naturelles Canada Research Scientist Chercheur 250-298-2401 250-298-2401 250-363-0775 506 W. Burnside Road 506 rue Burnside Ouest Victoria British Columbia Colombie-Britannique V8Z1M5 Canada Canada mike.wulder@canada.ca mike.wulder@canada.ca https://cfs.nrcan.gc.ca/employes/vue/mwulder http email only please courriel seulemente svp principalInvestigator; chercheurPrincipal High-resolution annual forest land cover maps for Canada's forested ecosystems (1984-2022). It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). The annual time series of forest land cover maps are national in scope (entire 650 million hectare forested ecosystem) and represent a wall-to-wall land cover characterization yearly from 1984 to 2022. These time-series land cover maps were produced from annual time-series of Landsat image composites, forest change information, and ancillary topographic and hydrologic data following the framework described in Hermosilla et al. (2022), which builds upon the approach introduced in Hermosilla et al. (2018). The methodological innovations included (i) a refined training pool derived from existing land cover products using airborne and spaceborne measures of forest structure; (ii) selection of training samples proportionally to the land cover distribution using a distance-weighted approach; and (iii) generation of regional classification models using a 150x150 km tiling system. Maps are post-processed using disturbance information to ensure logical class transitions over time using a Hidden Markov Model. Hidden Markov Models assess individual year class likelihoods to reduce variability and possible noise in year-on-year class assignments (for instances when class likelihoods are similar). Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., 2022. Land cover classification in an era of big and open data: Optimizing localized implementation and training data selection to improve mapping outcomes. Remote Sensing of Environment. Vol. 268, No. 112780. https://doi.org/10.1016/j.rse.2021.112780. (Hermosilla et al. 2022) Hermosilla, T., M.A. Wulder, J.C. White, N.C. Coops, G. W. Hobart, (2018). Disturbance-Informed Annual Land Cover Classification Maps of Canada's Forested Ecosystems for a 29-Year Landsat Time Series. Canadian Journal of Remote Sensing. 44(1) 67-87.DOI: 10.1080/07038992.2018.1437719 (Hermosilla et al. 2018). Cartes à haute résolution de la couverture terrestre forestière annuelle pour les écosystèmes forestiers du Canada (1984-2022). Il a été développé dans le cadre du Système national de surveillance des écosystèmes terrestres (NTEMS) du Canada. La série chronologique annuelle de cartes de la couverture terrestre forestière a une portée nationale (elle comprend les 650 millions d'hectares d'écosystèmes forestiers du Canada) et est le résultat de la caractérisation de la totalité de la couverture terrestre canadienne effectuée chaque année de 1984 à 2022. Les cartes de couverture terrestre de cette série chronologique ont été produites à partir d'une série chronologique annuelle d'images composites Landsat, de données sur les changements du couvert forestier et de données topographiques et hydrologiques auxiliaires, conformément au cadre décrit dans Hermosilla et al. (2022) et fondé sur l'approche présentée dans Hermosilla et al. (2018). Les innovations méthodologiques apportées comprennent (i) un ensemble de données d'entraînement précises obtenu à partir de produits de couverture terrestre existants à l'aide de mesures aériennes et spatiales de la structure forestière; (ii) une sélection des échantillons d'entraînement effectuée proportionnellement à la répartition de la couverture terrestre au moyen d'une approche pondérée en fonction de la distance; et (iii) la génération de modèles de classification régionale au moyen d'un système de pavés de 150 × 150 km. Les cartes sont post traitées à l'aide de données sur les perturbations afin de s'assurer que les transitions de classe dans le temps sont logiques, grâce à un modèle de Markov caché. Les modèles de Markov cachés évaluent les probabilités de classe pour chaque année afin de réduire la variabilité et le bruit possible dans les attributions de classe d'une année à l'autre (p. ex., lorsque les probabilités de classe sont du même ordre). Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., 2022. Land cover classification in an era of big and open data: Optimizing localized implementation and training data selection to improve mapping outcomes. Remote Sensing of Environment. 268, 112780. https://doi.org/10.1016/j.rse.2021.112780. ( Hermosilla et al. 2022) Hermosilla, T., M.A. Wulder, J.C. White, N.C. Coops, G. W. Hobart, (2018). Disturbance-Informed Annual Land Cover Classification Maps of Canada's Forested Ecosystems for a 29-Year Landsat Time Series. 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Characterizing long-term tree species dynamics in Canada's forested ecosystems using annual time series remote sensing data. Supporting Document;PDF;eng Document de soutien;PDF;eng https://www.sciencedirect.com/science/article/pii/S0034425717301360?via%3Dihub HTTPS A nationwide annual characterization of 25 years of forest disturbance and recovery for Canada using Landsat time series A nationwide annual characterization of 25 years of forest disturbance and recovery for Canada using Landsat time series Supporting Document;PDF;eng Document de soutien;PDF;eng https://www.tandfonline.com/doi/full/10.1080/17538947.2016.1187673 HTTPS Mass data processing of time series Landsat imagery: pixels to data products for forest monitoring Mass data processing of time series Landsat imagery: pixels to data products for forest monitoring Supporting Document;PDF;eng Document de soutien;PDF;eng https://www.sciencedirect.com/science/article/pii/S0303243417301599?via%3Dihub HTTPS Updating Landsat time series of surface-reflectance composites and forest change products with new observations Updating Landsat time series of surface-reflectance composites and forest change products with new observations Supporting Document;PDF;eng Document de soutien;PDF;eng https://www.tandfonline.com/doi/full/10.1080/07038992.2018.1437719 HTTPS Disturbance-Informed Annual Land Cover Classification Maps of Canada's Forested Ecosystems for a 29-Year Landsat Time Series Disturbance-Informed Annual Land Cover Classification Maps of Canada's Forested Ecosystems for a 29-Year Landsat Time Series Supporting Document;PDF;eng Document de soutien;PDF;eng https://opendata.nfis.org/mapserver/nfis-change_eng.html HTTPS Satellite Forest Information for Canada Information sur les forêts du Canada provenant d'images satellitaires Application;HTML;eng Application;HTML;eng https://opendata.nfis.org/mapserver/nfis-change_fra.html HTTPS Satellite Forest Information for Canada Information sur les forêts du Canada provenant d'images satellitaires Application;HTML;fra Application;HTML;fra