LutherFournierPierceyEtAl2006

Référence

Luther, J.E., Fournier, R.A., Piercey, D.E., Guindon, L. and Hall, R.J. (2006) Biomass mapping using forest type and structure derived from Landsat TM imagery. International Journal of Applied Earth Observation and Geoinformation, 8(3):173-187. (Scopus )

Résumé

A method for mapping forest biomass was developed and tested on a study area in western Newfoundland, Canada. The method, BIOmass from Cluster Labeling Using Structure and Type (BioCLUST), involves: (i) hyperclustering a Landsat TM image, (ii) automatically labeling the clusters with information about forest type and structure, and (iii) applying stand-level equations that estimate biomass as a function of height and crown closure within forest species-type classes. BioCLUST was validated with biomass values measured at geo-referenced field plots and mapped across the study area using an existing forest management photo-inventory. Root mean square error (RMSE) values ranged from 43 to 79 tonnes/ha, and were lowest for intermediate height classes when validated with field plots. Overall bias was negative at 10 tonnes/ha compared with a negative bias of 3 tonnes/ha estimated for the photo-inventory. Validation of the biomass map gave RMSE values of 37-47 tonnes/ha and overall landscape biomass estimates within 0.4% of biomass mapped by the photo-inventory. BioCLUST offers an alternative to other biomass mapping methods when scene-specific plot data are limited and a photo-inventory is available for a representative portion of a Landsat scene. © 2005 Elsevier B.V. All rights reserved.

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@ARTICLE { LutherFournierPierceyEtAl2006,
    AUTHOR = { Luther, J.E. and Fournier, R.A. and Piercey, D.E. and Guindon, L. and Hall, R.J. },
    TITLE = { Biomass mapping using forest type and structure derived from Landsat TM imagery },
    JOURNAL = { International Journal of Applied Earth Observation and Geoinformation },
    YEAR = { 2006 },
    VOLUME = { 8 },
    PAGES = { 173-187 },
    NUMBER = { 3 },
    ABSTRACT = { A method for mapping forest biomass was developed and tested on a study area in western Newfoundland, Canada. The method, BIOmass from Cluster Labeling Using Structure and Type (BioCLUST), involves: (i) hyperclustering a Landsat TM image, (ii) automatically labeling the clusters with information about forest type and structure, and (iii) applying stand-level equations that estimate biomass as a function of height and crown closure within forest species-type classes. BioCLUST was validated with biomass values measured at geo-referenced field plots and mapped across the study area using an existing forest management photo-inventory. Root mean square error (RMSE) values ranged from 43 to 79 tonnes/ha, and were lowest for intermediate height classes when validated with field plots. Overall bias was negative at 10 tonnes/ha compared with a negative bias of 3 tonnes/ha estimated for the photo-inventory. Validation of the biomass map gave RMSE values of 37-47 tonnes/ha and overall landscape biomass estimates within 0.4% of biomass mapped by the photo-inventory. BioCLUST offers an alternative to other biomass mapping methods when scene-specific plot data are limited and a photo-inventory is available for a representative portion of a Landsat scene. © 2005 Elsevier B.V. All rights reserved. },
    COMMENT = { Cited By (since 1996): 8 Export Date: 10 February 2010 Source: Scopus doi: 10.1016/j.jag.2005.09.002 },
    ISSN = { 15698432 (ISSN) },
    KEYWORDS = { Boreal environment, Classification, Forest biomass, Forest inventory, Geographical information systems, Landsat TM, biomass, forest inventory, forest management, GIS, Landsat thematic mapper, satellite imagery, vegetation mapping, Canada, Newfoundland, Newfoundland and Labrador, North America },
    OWNER = { Luc },
    TIMESTAMP = { 2010.02.10 },
    URL = { http://www.scopus.com/inward/record.url?eid=2-s2.0-33746334730&partnerID=40&md5=ff8ea98373626601d3faee454d9ab793 },
}

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