Search Results - (Author, Cooperation:T. R. Loveland)

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  1. 1
    M. C. Hansen ; P. V. Potapov ; R. Moore ; M. Hancher ; S. A. Turubanova ; A. Tyukavina ; D. Thau ; S. V. Stehman ; S. J. Goetz ; T. R. Loveland ; A. Kommareddy ; A. Egorov ; L. Chini ; C. O. Justice ; J. R. Townshend
    American Association for the Advancement of Science (AAAS)
    Published 2013
    Staff View
    Publication Date:
    2013-11-16
    Publisher:
    American Association for the Advancement of Science (AAAS)
    Print ISSN:
    0036-8075
    Electronic ISSN:
    1095-9203
    Topics:
    Biology
    Chemistry and Pharmacology
    Computer Science
    Medicine
    Natural Sciences in General
    Physics
    Keywords:
    Brazil ; *Conservation of Natural Resources ; *Geographic Mapping ; Indonesia ; *Maps as Topic ; *Trees
    Published by:
    Latest Papers from Table of Contents or Articles in Press
  2. 2
    Defries, R. S. ; Hansen, M. C. ; Townshend, J. R. G. ; Janetos, A. C. ; Loveland, T. R.

    Oxford, UK : Blackwell Publishing Ltd
    Published 2000
    Staff View
    ISSN:
    1365-2486
    Source:
    Blackwell Publishing Journal Backfiles 1879-2005
    Topics:
    Biology
    Energy, Environment Protection, Nuclear Power Engineering
    Geography
    Notes:
    Accurate assessment of the spatial extent of forest cover is a crucial requirement for quantifying the sources and sinks of carbon from the terrestrial biosphere. In the more immediate context of the United Nations Framework Convention on Climate Change, implementation of the Kyoto Protocol calls for estimates of carbon stocks for a baseline year as well as for subsequent years. Data sources from country level statistics and other ground-based information are based on varying definitions of ‘forest’ and are consequently problematic for obtaining spatially and temporally consistent carbon stock estimates. By combining two datasets previously derived from the Advanced Very High Resolution Radiometer (AVHRR) at 1 km spatial resolution, we have generated a prototype global map depicting percentage tree cover and associated proportions of trees with different leaf longevity (evergreen and deciduous) and leaf type (broadleaf and needleleaf). The product is intended for use in terrestrial carbon cycle models, in conjunction with other spatial datasets such as climate and soil type, to obtain more consistent and reliable estimates of carbon stocks. The percentage tree cover dataset is available through the Global Land Cover Facility at the University of Maryland at .
    Type of Medium:
    Electronic Resource
    URL:
    Articles: DFG German National Licenses