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Population distribution mapping using EO data is very useful, particular=
ly for fast-growing or developing countries, where urbanisation creates rap=
id significant changes in the geographical distribution of population. Popu=
lation distribution and density are based on the spatial disaggregation of =
census data using EO-derived lnd cover information. When collected at vario=
us administrative levels, census data is often too coarse for direct analys=
is, but additional information inside each administrative division can be o=
btained by studying the spatial distribution of land cover types inside eac=
h division. Knowing the type of urban fabric (residential or nonresidential=
) allows for more accurate spatial distribution of information and provides=
population estimates, for example, at night-time (home) periods, and, prov=
ided additional information is available, also for daytime (work) periods. =
Other EO contributions to population mapping consist in the estimation of t=
he population in informal settlements (e.g. refugee camps) by measuring the=
ir spatial extent in very highresolution imagery.
The spatial resolution, frequency and availability of the final products a=
re directly linked to that of the input satellite products. Disaggregation =
using land cover information can be performed at various scales, from mediu=
m- to very highresolution.
= p>
Mapping of settlements requires very high-resolution data in the o= rder of 1=E2=80=935 m. For the disaggregation technique using land cover, t= he accuracies and constraints discussed in the Urban Mapping section apply,= and are naturally influenced by the accuracy of the input census data. The= presence of high-rise buildings needs careful consideration, as the vertic= al component biases the outcome of the spatial disaggregation technique. Po= pulation mapping using very high-resolution imagery still suffer from accur= acy issues and a lot of detail is required in order to recognise and differ= entiate man-made structures and their extensions. No global solutions exist= , many of the existing solutions apply only regionally and in an ad-hoc man= ner.
Nevertheless, presently it is often possible to achieve better res=
ults than with existing GIS datasets, which are usually derived from much c=
oarser or more aggregated sources. Information about population distributio=
n is important for planning purposes and geomarketing.
Cens=
us data are often only available for large administrative units with arbitr=
ary boundaries that convey a wrong impression of homogeneous population den=
sity leading to analytical and cartographic problems. EO data =
can contribute to refine census information to better reflect reality in te=
rms of spatial distribution of population. The largest potential of the pro=
ducts is in regions and countries where limited information on=
population distribution is available.
References:
ESA 2013, Earth Observation for Gr= een Growth: An overview of European and Canadian Industrial Capability
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