comparing the geostat population grid 2006 data with ...€¦ · rege/gbl/ 40/84 mbl 370 baublöcke...
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Comparing the
GEOSTAT population grid 2006 data
with
municipal data in Germanymunicipal data in Germany
Dr. Udo Maack
KOSIS-Verbund, Germany
1
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GISCO Meeting March 2009:
Grid-Data Project
2
a Geostat 1 Backgroundpaper
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7. “ESS_grid”1. We have a well functioning statistical system of statistics
aggregated to administrative areas designed and built
serve “accounting” purposes.
2. For building a global infrastructure of spatial information
these traditional statistical systems represents an
obstacle. Their data are not suitable for the
3
obstacle. Their data are not suitable for the
“engineering” purposes required.
3. The current global challenge will a statistical systems that
allows for integrated spatial analysis that involves
qualified statistics from any available source. This calls for
a shared of statistics that covers the whole earth, is
liberated from administrative areas, and that allows for
hierarchical analysis of datasets on all scale ranges from
global to local.
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Project Investigations:
A. Population by Pan European Population Grid and
Population registered
KOSIS-Grid-Data Project
Population registered
B. Relation between Grids and Small Area Classifications
(SAC’s) used in German municipalities
C. Tools and use cases
D. Conclusions and Advises
B. Relation between Grids and Small Area Classifications
(SAC’s) used in German municipalities
C. Tools and use cases
D. Conclusions and Advises4
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Roadmap (revised)
Grid-Data Project
5
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Cities
participating
Grid-Data Project
6
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Spatial Data Base per City (Subcity-Classification)
Spatial Units DD F FR GE HB L M MA
Nbg /
Fü S WOB
1kmRaster 394 365 204 139 393 362 371 185 311 257 253
100mRaster 33.662 25.682 15.893 10.844 32.695 30.524 31.786 14.924 25.252 21.321 21.036
EuroPopGrid 345 263 149 135 308 302 357 150 285 230 154
City 1 1 1 1 1 1 1 1 2 1 1
Grid-Data Project (A)
City 1 1 1 1 1 1 1 1 2 1 1
Stadtbezirke 121 42 5 10 27 17 105 23
Stadtbereiche 6 18
Stadtbezirksteile 108
Distrikte 387
Stadt-/Ortsteile 64 29 90 63 152 42
Stadtviertel 319
Stat. Bezirke 388 161 310
Rege/GBL/ 40/84
MBL 370
Baublöcke 11.622 5.943 1.636 1.768 5.957 4.013 10.348 2.803 4.693 6.048 1.998
Baublockseiten 17.504
Urban Atlas X X X --- X X X --- X X ---7
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Summary-Values
on Data-Level
Principles of Disaggregation
Grid-Data Project (A)
Filter-Level
Grid-Level 8
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Disaggregated Data of
the Pan European
Population Grid
Grid-Data Project (A)
Impact of Grids
truncated
by the
City Borderline
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City
Grids
within City
boundaries
Grids
popu-
lated
Population
in Grids
Grids
truncated
Pop within
City Limits
registered
Population
Relation
POP-EU /
POP-
Register
How to produce comparable Data?
Grid-Data Project (A)
Register
DD 394 345 529.613 114 496.288 487.199 1,019
F 365 263 724.738 97 660.502 627.826 1,052
FR 204 149 229.039 70 215.189 194.137 1,108
GE 139 135 344.740 64 269.015 256.990 1,047
HB 393 308 578.833 113 537.378 558.018 0,963
L 362 302 524.477 85 499.762 489.099 1,022
M 371 357 1.313.226 113 1.243.148 1.283.855 0,968
MA 185 150 332.436 50 306.038 295.876 1,034
NF 311 285 634.230 163 598.040 608.346 0,983
S 257 230 628.963 74 586.096 556.710 1,053
WOB 253 154 124.950 41 120.706 120.709 1,00010
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Grid-
Data-Level
Principles of spatial
Aggregation
Grid-Data Project (A)
Starting-
Data-Level
(Point Cloud based on Addresses)
Data-Level
11
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Grid-Data Project (A)
disaggregated Population12
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Grid-Data Project (A)
disaggregated Population
aggregated Population
13
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Grid-Data Project (A)
disaggregated Population
Population distribution
in 100x100m Grids
Population not
represented by
Disaggregation
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Blockareas
overlaying
disaggregated
Grid-Data Project (A)
disaggregated
populated
Grids(only blocks
with buildings)
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Differences
between
aggregated and
disaggregated
values
Grid-Data Project (A)
values
overestimation
underestimation16
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Error estimation:
R s = Ṗ s - P s
Difference per Grid:
City relErrorTAE
DD 37%
F 33%
FR 31%
GE 22%
HB 33%
Acc
ep
tab
le ?
Grid-Data Project (A)
n
TAE = ∑ | R s |s=1
Total Absolute Error:
TAE
RelError TAE = ―――
∑ Ṗ
Relative Error:
HB 33%
L 45%
MA 39%
M 40%
NF 39%
S 29%
WOB 37%
Acc
ep
tab
le ?
17
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From Geostat 1A Report:
A quality assessment of the disaggregated population
grid carried out by AIT showed that the relative error at
national level
Grid-Data Project (A)
national level
for those countries where reference register data are
available is in the order of 30%
but can exceed 50% for sparsely populated countries
such as NO, SE and FI.
How was this performed?18
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Grid-Data Project (A)
Data handling of border grids
Pan European Population Grid Data:
19
INSPIRE conform - Grid Data:
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Municipal Situation:
Grid-Data Project (A)
10 Stadtbezirke / Hektarraster
2.616 von 30.524 - 27.908 freie Raster
4.013 Baublöcke / Hektarraster
16.427 von 30.524 - 14.097 freie Raster20
9 % Bordergrids 54 % Bordergrids
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Grid-Data Project (A)
First-Conclusion (for Block A)
• Grids are useful for an easy harmonization of
reference areas
• Grids are useful for a certain class of applications
21
• Grids are useful for a certain class of applications
• Grids not able to provide statistical data on user
territorial classifications without loosing quality
• Grids can not replace the vector representation of
statistical / planning / administrative units at least
on municipal level
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City
Grids
1 km Relation?
SAC- Units
Stadtbezirke
Grid-Data Project (B)
Two-Pillar-Model of municipal georeferencing
Blockseiten
(geocoded) Addresses
125 m
100 m
200 m
Blöcke
Stadtbezirke
22
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How to characterize the relation between the
two pillars?
• Quantitative – How to measure?
Grid-Data Project (B)
• Quantitative – How to measure?
• Visual – By which rules?
• Advantages and Disadvantages?
23
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Visual comparison
Grid-Data Project (B)
Population
density
on
Baublock-
Level
24
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Grid-Data Project (B)
Visual comparison
Population
density
on
100mx100m
Grids
25
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Population
density
on
Grid-Data Project (B)
Visual comparison
on
Baublock-
Level(only Areas < 13 ha)
and
100mx100m
Grids(contrasted colors)
26
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Mixed referenced Units
Population
density
on
Grid-Data Project (B)
on
Baublock-
Level(only Areas < 13 ha)
and
100mx100m
Grids(same classification)
27
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SAC vs. Grids
Evaluation:
Advantages of Grids
Disadvantages of Grids
Grid-Data Project (B)
Advantages of SAC-Units
Disadvantages of SAC-Units
Results will be published at beginning of 2014
28
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Displaying
Grid-Data Project (C)
Displaying
Single values
per
100mx100m
Grids
© 2013, Hans Menge29
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Displaying
Smoothing with
neighboring grids
Grid-Data Project (C)
© 2013, Hans Menge
1 2 3
1 6 6
2
3 6 6
Weightingfactors:
1,0 / 1,0 / 1,030
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Displaying
Smoothing with
neighboring grids
Grid-Data Project (C)
© 2013, Hans Menge
1 2 3
1 6 6
2
3 6 6
Weightingfactors:
1,0 / 0,5 / 0,231
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Calculation of potentiality
10
12
Populationpotential für ZP1
0
5
0 5 10 15 20
Grid-Mapping (Inh/km²)
Grid-Data Project (C)
12
14
16
18
20
5 10 15
Ho
ch
wert
H
Rechtswert R
10
15
20
© 2013, Hans Menge32
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accessible potential
and barriers
Grid-Data Project (C)
© 2013, Hans Menge33
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European
Forum for
Geo Grid
34
Geo
Statistics
Grid
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?Thank you
?
35