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Figure 8 shows the top view of the artificial chimney C0016B with its surroundings and Fig. 9 shows the population density maps of S. crosnieri.
In this paper we describe an approach for developing historical population density maps by downdating a recent high-resolution population density raster, using a time series of sealed surface data and historical census data as an input.
From this data the population density maps for the area around the natural and the three artificial hydrothermal vents were generated using a 2D Gaussian window with a standard deviation of 15 cm. Figure 6 shows the 3D map of chimney C0014G with the S. crosnieri population density overlaid.
They end up just basically being population density maps.
LS produced the maps of infected herds and JF produced the population density maps.
The population density maps on which we base some of the estimates were constructed by the interpolation of sub-district data [ 19].
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Then, students can apply their knowledge by writing a paragraph to describe this population density map of the world.
Population data obtained from the National Institute of Statistic INSS) was used to generate the population density map.
a Population density map, b Drainage system map and c Urban Structure Types.
Fig. 6 Population density map of S. crosnieri at chimney C0014G.
Settlements are identified through remote sensing data and population density mapping using Census data.
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