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    Interannual Variability and Decadal Trend of Global Fractional Vegetation Cover from 1982 to 2000

    Source: Journal of Applied Meteorology:;2003:;volume( 042 ):;issue: 010::page 1525
    Author:
    Zeng, Xubin
    ,
    Rao, Praveen
    ,
    DeFries, Ruth S.
    ,
    Hansen, Matthew C.
    DOI: 10.1175/1520-0450(2003)042<1525:IVADTO>2.0.CO;2
    Publisher: American Meteorological Society
    Abstract: Fractional vegetation cover (FVC) is one of the most important variables in land surface modeling and also provides a continuous field to complement discrete land cover classification. A global 8-km FVC dataset for 1982?2000 is derived using the NOAA?NASA land Pathfinder normalized difference vegetation index data. The confidence in the dataset is provided by the insensitivity of the algorithm to the data resolution (between 1 and 8 km), the good agreement of the results with the field survey data over Germany, the consistency of the results with previous observational studies over the savannas in North Africa and the forests in Bolivia, and the robustness of the algorithm, as demonstrated by the small interannual variability of FVC over areas where anthropogenic land cover change is expected to be small, based on the 30-m Landsat data analysis. Significant interannual variability is found over shrubland, savanna, and grassland; both positive and negative trends exist over different areas of the same region in many parts of the world. In particular, the trend analysis pinpoints areas with statistically significant trends (i.e., ?hotspots?) for further study using higher-resolution satellite data and field-survey data.
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      Interannual Variability and Decadal Trend of Global Fractional Vegetation Cover from 1982 to 2000

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4148739
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    contributor authorZeng, Xubin
    contributor authorRao, Praveen
    contributor authorDeFries, Ruth S.
    contributor authorHansen, Matthew C.
    date accessioned2017-06-09T14:08:57Z
    date available2017-06-09T14:08:57Z
    date copyright2003/10/01
    date issued2003
    identifier issn0894-8763
    identifier otherams-13303.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4148739
    description abstractFractional vegetation cover (FVC) is one of the most important variables in land surface modeling and also provides a continuous field to complement discrete land cover classification. A global 8-km FVC dataset for 1982?2000 is derived using the NOAA?NASA land Pathfinder normalized difference vegetation index data. The confidence in the dataset is provided by the insensitivity of the algorithm to the data resolution (between 1 and 8 km), the good agreement of the results with the field survey data over Germany, the consistency of the results with previous observational studies over the savannas in North Africa and the forests in Bolivia, and the robustness of the algorithm, as demonstrated by the small interannual variability of FVC over areas where anthropogenic land cover change is expected to be small, based on the 30-m Landsat data analysis. Significant interannual variability is found over shrubland, savanna, and grassland; both positive and negative trends exist over different areas of the same region in many parts of the world. In particular, the trend analysis pinpoints areas with statistically significant trends (i.e., ?hotspots?) for further study using higher-resolution satellite data and field-survey data.
    publisherAmerican Meteorological Society
    titleInterannual Variability and Decadal Trend of Global Fractional Vegetation Cover from 1982 to 2000
    typeJournal Paper
    journal volume42
    journal issue10
    journal titleJournal of Applied Meteorology
    identifier doi10.1175/1520-0450(2003)042<1525:IVADTO>2.0.CO;2
    journal fristpage1525
    journal lastpage1530
    treeJournal of Applied Meteorology:;2003:;volume( 042 ):;issue: 010
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
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