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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.
At the home range scale, however, the sloths did not show preference for any forest category, though, again, avoided open areas.
The percentage of forested perimeter was calculated by dividing the length of the wetland edge by the total distance of wetland edge that came into direct contact with the "Forest" category described above.
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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.
Nevertheless, there is great potential in terms of the spatial expansion of forest areas and the shift of suitable forest categories [10].
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).
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