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about Piemonte Atlas

Coordinate Reference System

The supported SRS is WGS84 / UTM zone 32N, as formally identified by the EPSG standard SRID 32632.
This CRS is one of the planar / projected type, i.e. it's based on X and Ycartesian coordinates measured in metres.

Spatial Resolution (Nominal Scale)

The supported nominal scale for each dataset is one well fit for medium scale / regional representations. It typically is about 15 m.

Supported vector datasets

The following datasets (aka layers) of the vector type are included on the Piemonte Atlas:

• Towns: about 1.700 populated places are represented.
  The original source for this dataset is GeoNames (released under the CC-BY license terms).
• Any other dataset was taken from Regione Piemonte (released under the CC-BY license terms).
  Region and Counties Coat-of-Arms are taken from Wikipedia (and usually are in the Public Domain).
  • AdminAreas: about 1.200 administrative boudaries (Counties and Local Councils)
  • CulturalHeritage: about 70 POIs
  • Lakes: about 200
  • Rivers: about 4,100
  • NaturalReserves: about 110
  • Highways: about 23.000 road arcs
  • Railways: about 190 railway arcs
  • RailwayStations: about 400 POIs
  • TownAreas: about 1.000 footprints

Supported raster datasets

The following datasets (aka layers) of the raster type are included on the Piemonte Atlas:

• Satellite imagery: this actually corresponding to Landsat panchromatic band (relased on the Public Domain)
  .i.e. it's a mosaic of selected orbital scenes taken from Lansat-7 NASA/USGS satellite. Supported resolution is 15m/pixel.
• Relief imagery: this actually corresponding to SRTM Digital Elevation Model. (Public Domain).
  The original measured elevations were produced by the NASA/USGS Space Shuttle Radar Topography Mission.
  This dataset has a spatial resolution of 90m/pixel.Actual imagery was then obtained by the Author itself by applying false colours and shaded relief rendering techniques.
  Cordinates reprojection from 4326 WGS84 to 32632 WGS84 / UTM zone 32N was applied using the gdalwarp open source tool.

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Visual Examples
dataset	Full Coverage	Detail
Political map (vector layers)
Satellite map (Landsat-7 panchromatic band)
Relief map (SRTM)

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