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Examples of how such data can be combined for analysing specific landscape characteristics such as the percentage of rivers running through forested areas or the distribution of forest categories according to relief characteristics are given for the whole of Italy as well as for three selected catchments.
The mapping is applied within five forest categories (open, sparse, deciduous, mixed, and conifer).
Natural forest categories include moist deciduous, evergreen to semi evergreen, scrub/grass and dry deciduous forest types.
In fact, abundance in a plot, mortality rate and diameter growth in the two forest categories were in most species not related to each other (see Table 2).
Nevertheless, there is great potential in terms of the spatial expansion of forest areas and the shift of suitable forest categories [10].
The areas and proportions of different forest categories from NFI1 to NFI8 in China are listed in Table 5 (Lei 2005; SFA 2009, 2014b).
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Forest cover in the primary humid tropical forest category for 2000 was used for this analysis, as this class correlates best with moist tropical forest as defined by IPCC, while other FACET forest types mix secondary and dry forest [67].
These Landsat data were differentiated into 21 class types, but four classes (Deciduous Forest, Evergreen Forest, Mixed Forest, and Palustrine Forested Wetland) were collapsed into one "Forest" category.
Data for woodland and orchard were combined as forest category.
Land type and forest category are two of the most important plot attributes.
Most of this sink (≈ 380 Mt CO2/year) occurs in the "forest remaining forest" category, with the remainder in the "land converted to forest" (including afforestation or reforestation) category.
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