LeboeufFournier2015

Référence

Leboeuf, A., Fournier, R.A. (2015) A Multisensor Multiresolution Method for Mapping Vegetation Status, Surficial Deposits, and Historical Fires over Very Large Areas in Northern Boreal Forests of Quebec, Canada. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8(11):5199-5211. (Scopus )

Résumé

Boreal forests have a significant impact on the Earth's climate and on global warming. In this context, a mapping method was developed and was capable of dealing with very large areas with a lack of support datasets, which could characterize the current forest, surficial deposits, and forest disturbance history. The method based on remote sensing data, images processing techniques, and images interpretation was applied over a very large area (680\,000\;\text{km}2) in Québec, QC, Canada that was dominated by black spruce (Picea mariana [Miller] BSP). It involved five steps: 1) mapping the vegetation based on unsupervised classification, imputation, and segmentation methods; 2) mapping the history of fires that occurred over the mapping area based on archives Landsat images; 3) determining the dominant species characterizing forest stands; 4) mapping surficial deposits; and 5) accuracy assessment of map attributes based on video dataset. Kappa values ranged from 72.5% to 96.3%, indicating substantial agreement when compared with validation dataset. The results demonstrated that our method is a convenient and inexpensive way of mapping forest ecosystems over large areas of northern boreal forest. © 2008-2012 IEEE.

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@ARTICLE { LeboeufFournier2015,
    AUTHOR = { Leboeuf, A. and Fournier, R.A. },
    TITLE = { A Multisensor Multiresolution Method for Mapping Vegetation Status, Surficial Deposits, and Historical Fires over Very Large Areas in Northern Boreal Forests of Quebec, Canada },
    JOURNAL = { IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing },
    YEAR = { 2015 },
    VOLUME = { 8 },
    NUMBER = { 11 },
    PAGES = { 5199-5211 },
    NOTE = { cited By 0 },
    ABSTRACT = { Boreal forests have a significant impact on the Earth's climate and on global warming. In this context, a mapping method was developed and was capable of dealing with very large areas with a lack of support datasets, which could characterize the current forest, surficial deposits, and forest disturbance history. The method based on remote sensing data, images processing techniques, and images interpretation was applied over a very large area (680\,000\;\text{km}2) in Québec, QC, Canada that was dominated by black spruce (Picea mariana [Miller] BSP). It involved five steps: 1) mapping the vegetation based on unsupervised classification, imputation, and segmentation methods; 2) mapping the history of fires that occurred over the mapping area based on archives Landsat images; 3) determining the dominant species characterizing forest stands; 4) mapping surficial deposits; and 5) accuracy assessment of map attributes based on video dataset. Kappa values ranged from 72.5% to 96.3%, indicating substantial agreement when compared with validation dataset. The results demonstrated that our method is a convenient and inexpensive way of mapping forest ecosystems over large areas of northern boreal forest. © 2008-2012 IEEE. },
    ART_NUMBER = { 7293616 },
    AUTHOR_KEYWORDS = { Boreal; fire history; forest attributes; Landsat; RapidEye; surficial deposits },
    DOCUMENT_TYPE = { Article },
    DOI = { 10.1109/JSTARS.2015.2477780 },
    KEYWORDS = { Classification (of information); Data handling; Deposits; Earth (planet); Ecosystems; Forestry; Global warming; Image segmentation; Remote sensing; Vegetation, Accuracy assessment; Forest disturbances; Images interpretation; Mapping vegetations; Multiresolution methods; Remote sensing data; Segmentation methods; Unsupervised classification, Mapping, boreal forest; fire history; forest ecosystem; forest fire; image processing; Landsat; mapping; RapidEye; surficial sediment; vegetation dynamics, Canada; Quebec [Canada] },
    SOURCE = { Scopus },
    URL = { https://www.scopus.com/inward/record.uri?eid=2-s2.0-84943374817&partnerID=40&md5=edda1a5e728ea9fc4f867b5e9fb1ced2 },
}

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