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1 Production of grid statistics Methods for producing and harmonise statistics on grid course on Geographic Information Systems (GIS): of GIS for making statistics in a production environment istics Norway, Oslo, 26th to 30th of March 2012 Attribution (by) Licensees may copy, distribute, display and perform the work and make derivative works based on it only if they give the author or licensor the credits in the manner specified by these. http://creativecommons.org/licenses/by/3.0/ Mr Vilni Verner Holst Bloch MSc Resourcs Geography and Landscape Ecology Statistics Norway 460 Construction and service statistics Oterveien 23 N-2225 Kongsvinger NORWAY [email protected] Tel: +47 6288 5097 Mob. +47 9482 2532

Production of grid statistics Methods for producing and harmonise statistics on grid

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Production of grid statistics Methods for producing and harmonise statistics on grid. Mr Vilni Verner Holst Bloch MSc Resourcs Geography and Landscape Ecology Statistics Norway 460 Construction and service statistics Oterveien 23 N-2225 Kongsvinger NORWAY [email protected] Tel: +47 6288 5097 - PowerPoint PPT Presentation

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Page 1: Production of grid statistics Methods for producing and harmonise statistics on grid

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Production of grid statistics

Methods for producing and harmonise statistics on grid

ESTP course on Geographic Information Systems (GIS): Use of GIS for making statistics in a production environmentStatistics Norway, Oslo, 26th to 30th of March 2012

Attribution (by) Licensees may copy, distribute, display and perform the work and make derivative works based on it only if they give the author or licensor the credits in the manner specified by these. http://creativecommons.org/licenses/by/3.0/

Mr Vilni Verner Holst BlochMSc Resourcs Geography and Landscape EcologyStatistics Norway460 Construction and service statisticsOterveien 23 N-2225 Kongsvinger [email protected]: +47 6288 5097Mob. +47 9482 2532

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Content

• Recommendations from Geostat 1A

• Xx

• Task on QA of grid statistics

• Task on producing grid statistics

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The grid

• Recommendation 1: Grid data for the European GEOSTAT dataset should be referenced to the European Grid Grid_ETRS89-LAEA_1K.

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Grid cell size

• Recommendation 2: The GEOSTAT grid dataset should have a grid cell size of 1km².

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Grid coding

• Recommendation 3: For unambiguous referencing and identification of a grid cell, the cell code should be composed of the size of the cell (1 and the coordinates of the lower left cell corner in ETRS89-LAEA should be used). The cell size should be denoted in kilometres (‘km’) for cell size 1km. Values for northing and easting should be divided by 1000. The cell code ‘1kmN2599E4695’ identifies the 1km grid cell with coordinates of the lower left corner: Y=2599000 m, X=4695000 m.

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Disclosure

• Recommendation 4: For the European GEOSTAT dataset at 1km² the total population should be disclosed without restrictions for any grid cell. The GEOSTAT project recommends that data protection measures should depend on the sensitive nature of the variables. Absolute counts of the statistical units (such as number of inhabitants, households, buildings, workplaces) should be disseminated without any restrictions, even for the smallest grid sizes.

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Availability

• Recommendation 5: The GEOSTAT dataset may be downloaded free of charge and without access restrictions in a package of a .csv file with the statistical data, a grid net shape file and an INSPIRE metadata file in ISO19139 encoding. The dataset may be downloaded from the EFGS or Eurostat websites.

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Reference year

• Recommendation 6: The GEOSTAT dataset version 1 should have the reference year 2006. The next version of the European GEOSTAT dataset should have the reference year 2011.

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Data quality

• Recommendation 7: The data quality of the GEOSTAT dataset version 1 should be in the form of INSPIRE metadata encoded in ISO19139 .xml files. The production process should be documented per grid data source and country.

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Cross border cells

Handling of border cells. The picture shows the situation on the border (black line) between two countries. The same grid cell is provided by SE (top left) with 2 inhabitants and Norway (top right) with 4 inhabitants. In the final GEOSTAT data set the grid cell contains 6 inhabitants) and the DATA_SCR attribute is filled accordingly with SE;NO.

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The following population classes are recommended for general mapping purposes:

1.Not inhabited, Population 0, Colour scheme CMYK (white)

2.1 – 4 Inhabitants, CMYK M5, Y40 (light yellow)

3.5 – 19 Inhabitants, CMYK M20, Y60 (yellow)

4.20 – 199 Inhabitants, CMYK M50, Y80 (light orange)

5.200 – 499 Inhabitants, CMYK M70, Y80 (orange)

6.500 – 5000 Inhabitants, CMYK M100, Y50 (red)

7.>5000 Inhabitants, CMYK C55, M90, Y50 (lilac)

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Aggregation method

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Disaggregation method

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Hands-on exercise 1/2:

Assessing data quality and coverage

Hands-on exercise 2/2:

Methods for producing and harmonise statistics on grid

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Import data 1/3 - normalize

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Import data 2/3 – join tables

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Import data 3/3 - display

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Excercises 1/2

• Download grid statistics from http://www.efgs.info/data/norway

• Join tables for dwellings (DWE), buildings (BUI) and population (POP)to grid

• Do you find grid cells with dwellings but no buildings?

• Do you find grid cells with population but no dwellings?

• How many grid cells are populated?

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Excercises 2/2

• Use OSM data (EPSG:4326), points.shp, population field, to aggregate to Geostat grid

• Use OSM and NUTS (ETRS89) data to disaggregate population data to Geostat grid