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Total settlement fragmentation index

SFI = IFI + UFI =

∑ LoΛ+∑ L * ^∑S

(5)

The index gives the indication about the total fragmentation in the spatial unit due to the
combined effects of the infrastructures and linear urbanisation.

SFI values_____	Environmental fragmentation landscapes
SFI< 0.04 UD<15 mq/ha	Urban settlement very scattered, with some small dense parts, mainly formed by rural and isolated builds within hilly morphological context with extensive agricultural typologies._________________
0.04 < SFI < 0.15 15 <UD <40 mq/ha	Urban settlement very scattered, with some small dense parts, but with uniform density distribution. Country houses and rural builds are the main typologies._____________________________
0.15 < SFI < 0.31 40 <UD < 100 mq/ha____________	Urban settlement scattered again, but with frequent build small aggregations, often located along morphological or infrastructural lines.
0.31 < SFI < 1.90 100 <UD < 300 mq/ha	Urban settlement mainly aggregated, with urban areas of middle dimension and with linear shape, located on flat or low-hilly morphology and large intensive agriculture places._________________
SFI > 1.90 UD > 300 mq/ha	Urban settlement formed by different kinds of builded places, with middle and high density, linear urban concentration along bottom valley and infrastructural belts, with road systems surrounded by factories and residential areas.______________________________

Figure 11 - Sample of the total settlement fragmentation index (SFI) and its relation with Urban density
(UD) for Umbria region

Conclusion

As we said the presented data should represent a profile on urban landscape condition
that have to communicate with eco-biogeographical data implemented on the same
spatial units. This step can permit to obtain relation functions between the settlement
indices and biodiversity indices.

With regards to the cited indices it is necessary to make some considerations: first of all
it is important to define level and dimension of the “minimal analysis units” (MAU) in
which are realized the observation and the interpretation of the phenomena explain from
the different indices.

Normally, in fact, these MAU are very small when are relative to eco-biogeographical
data, and are instead larger when are relative to urban and territorial data. At this aspect
are link the major problems for implementing the correlation functions.

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