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A new global 1‐km dataset of percentage tree cover derived from remote sensing
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| Zeitschriftentitel: | Global Change Biology |
|---|---|
| Personen und Körperschaften: | , , , , |
| In: | Global Change Biology, 6, 2000, 2, S. 247-254 |
| Format: | E-Article |
| Sprache: | Englisch |
| veröffentlicht: |
Wiley
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| Schlagwörter: |
| author_facet |
Defries, R. S. Hansen, M. C. Townshend, J. R. G. Janetos, A. C. Loveland, T. R. Defries, R. S. Hansen, M. C. Townshend, J. R. G. Janetos, A. C. Loveland, T. R. |
|---|---|
| author |
Defries, R. S. Hansen, M. C. Townshend, J. R. G. Janetos, A. C. Loveland, T. R. |
| spellingShingle |
Defries, R. S. Hansen, M. C. Townshend, J. R. G. Janetos, A. C. Loveland, T. R. Global Change Biology A new global 1‐km dataset of percentage tree cover derived from remote sensing General Environmental Science Ecology Environmental Chemistry Global and Planetary Change |
| author_sort |
defries, r. s. |
| spelling |
Defries, R. S. Hansen, M. C. Townshend, J. R. G. Janetos, A. C. Loveland, T. R. 1354-1013 1365-2486 Wiley General Environmental Science Ecology Environmental Chemistry Global and Planetary Change http://dx.doi.org/10.1046/j.1365-2486.2000.00296.x <jats:title>Summary</jats:title><jats:p>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 <jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="http://glcf.umiacs.umd.edu">http://glcf.umiacs.umd.edu</jats:ext-link>.</jats:p> A new global 1‐km dataset of percentage tree cover derived from remote sensing Global Change Biology |
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A new global 1‐km dataset of percentage tree cover derived from remote sensing |
| title_unstemmed |
A new global 1‐km dataset of percentage tree cover derived from remote sensing |
| title_full |
A new global 1‐km dataset of percentage tree cover derived from remote sensing |
| title_fullStr |
A new global 1‐km dataset of percentage tree cover derived from remote sensing |
| title_full_unstemmed |
A new global 1‐km dataset of percentage tree cover derived from remote sensing |
| title_short |
A new global 1‐km dataset of percentage tree cover derived from remote sensing |
| title_sort |
a new global 1‐km dataset of percentage tree cover derived from remote sensing |
| topic |
General Environmental Science Ecology Environmental Chemistry Global and Planetary Change |
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http://dx.doi.org/10.1046/j.1365-2486.2000.00296.x |
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2000 |
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247-254 |
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<jats:title>Summary</jats:title><jats:p>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 <jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="http://glcf.umiacs.umd.edu">http://glcf.umiacs.umd.edu</jats:ext-link>.</jats:p> |
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| author | Defries, R. S., Hansen, M. C., Townshend, J. R. G., Janetos, A. C., Loveland, T. R. |
| author_facet | Defries, R. S., Hansen, M. C., Townshend, J. R. G., Janetos, A. C., Loveland, T. R., Defries, R. S., Hansen, M. C., Townshend, J. R. G., Janetos, A. C., Loveland, T. R. |
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| description | <jats:title>Summary</jats:title><jats:p>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 <jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="http://glcf.umiacs.umd.edu">http://glcf.umiacs.umd.edu</jats:ext-link>.</jats:p> |
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| spelling | Defries, R. S. Hansen, M. C. Townshend, J. R. G. Janetos, A. C. Loveland, T. R. 1354-1013 1365-2486 Wiley General Environmental Science Ecology Environmental Chemistry Global and Planetary Change http://dx.doi.org/10.1046/j.1365-2486.2000.00296.x <jats:title>Summary</jats:title><jats:p>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 <jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="http://glcf.umiacs.umd.edu">http://glcf.umiacs.umd.edu</jats:ext-link>.</jats:p> A new global 1‐km dataset of percentage tree cover derived from remote sensing Global Change Biology |
| spellingShingle | Defries, R. S., Hansen, M. C., Townshend, J. R. G., Janetos, A. C., Loveland, T. R., Global Change Biology, A new global 1‐km dataset of percentage tree cover derived from remote sensing, General Environmental Science, Ecology, Environmental Chemistry, Global and Planetary Change |
| title | A new global 1‐km dataset of percentage tree cover derived from remote sensing |
| title_full | A new global 1‐km dataset of percentage tree cover derived from remote sensing |
| title_fullStr | A new global 1‐km dataset of percentage tree cover derived from remote sensing |
| title_full_unstemmed | A new global 1‐km dataset of percentage tree cover derived from remote sensing |
| title_short | A new global 1‐km dataset of percentage tree cover derived from remote sensing |
| title_sort | a new global 1‐km dataset of percentage tree cover derived from remote sensing |
| title_unstemmed | A new global 1‐km dataset of percentage tree cover derived from remote sensing |
| topic | General Environmental Science, Ecology, Environmental Chemistry, Global and Planetary Change |
| url | http://dx.doi.org/10.1046/j.1365-2486.2000.00296.x |