Towards a typology of urban centers and subcenters – evidence from German city regions

Figures & data

Figure 1. Summary of the empirical procedure (Source: Own elaboration based on the data described above).

Table 1. Characterizing the study regions.

	Frankfurt region	Cologne region	Munich region	Stuttgart region
Area in km^2	4,843	2,812	3,277	2,842
Number of core cities	4	2	1	1
Employees in million	1.06	0.80	0.79	0.77
Employees in service sectors in million	0.35	0.24	0.28	0.19
Residents in million	3.53	2.78	2.42	2.37
Average distance to … in km
(main) CBD	32.80	26.44	26.76	25.78
Next highway entrance ramp	7.78	5.73	7.97	11.94
Next main station	15.69	15.18	21.50	14.81
Next international airport	31.88	27.01	39.20	30.67
Built-up volume in million m^3	1,028.53	1,158.90	942.26	658.96
Built area in 1970 in km^2	570.95	449.50	351.73	338.21
Built area in 2010 in km^2	655.95	488.78	395.44	405.23
Employees per number of residents	0.30	0.29	0.33	0.32
Service sector employees per number of residents	0.10	0.09	0.12	0.08
Change in built area 1970–2010 in %	14.89	8.74	12.43	19.82

(Source: Own calculations based on the data described above)

Table 2. List of variables considered for the macro layer.

Data content	Measurement unit	Data source
Employees	count	georeferenced IEB
Employees in service sectors	count	georeferenced IEB
Firms	count	georeferenced IEB
Firms (in service sectors)	count	georeferenced IEB
Residents	count	EUROSTAT
Built-up volume	cubic meters	see Wurm et al., 2014
Floor area	square meters	see Wurm et al., 2014
Built area in 1970	square meters	Landsat-MSS, processed by Michael Wurm
Land consumption 1970–1980	square meters	Landsat-TM, processed by Michael Wurm
Land consumption 1980–1990	square meters	Landsat-TM, processed by Michael Wurm
Land consumption 1990–2000	square meters	Landsat-TM, processed by Michael Wurm
Land consumption 2000–2010	square meters	Landsat-TM, processed by Michael Wurm
Average firm size	number of employees	georeferenced IEB, own calculation
Average service sector firm size	number of employees	georeferenced IEB, own calculation
Employees per number of residents	ratio	georeferenced IEB and EUROSTAT, own calculation
Service sector employees per number of residents	ratio	georeferenced IEB and EUROSTAT, own calculation
Distance to the next CBD	kilometers	NAVTEQ street map
Distance to the next international airport	kilometers	NAVTEQ street map
Distance to the next main station	kilometers	NAVTEQ street map
Distance to the next highway entrance ramp	kilometers	NAVTEQ street map

(Source: own compilation)

Figure 2. Macro layer based on the mapping of the 3-cluster solution (Source: Own elaboration based on the data described above).

Table 3. Shares of region-wide totals captured by the clusters.

Shares of	Frankfurt region	Cologne region	Munich region	Stuttgart region	Joint analysis
	Cluster No. 1
Employees in million	0.23	0.15	0.26	0.09	0.15
Employees in service sectors in million	0.19	0.11	0.21	0.07	0.11
Residents in million	0.24	0.16	0.28	0.11	0.16
Built-up volumes in million m^3	0.36	0.15	0.39	0.21	0.23
Built area in 1970 in km^2	0.33	0.15	0.40	0.14	0.21
Built area in 2010 in km^2	0.36	0.17	0.44	0.16	0.24
Area covered in km^2	0.58	0.65	0.73	0.52	0.61
	Cluster No. 2
Employees in million	0.45	0.72	0.38	0.46	0.76
Employees in service sectors in million	0.44	0.72	0.38	0.43	0.77
Residents in million	0.45	0.72	0.39	0.45	0.76
Built-up volumes in million m^3	0.35	0.73	0.29	0.45	0.70
Built area in 1970 in km^2	0.45	0.80	0.42	0.50	0.76
Built area in 2010 in km^2	0.45	0.78	0.39	0.51	0.73
Area covered in km^2	0.13	0.32	0.07	0.22	0.22
	Cluster No. 3
Employees in million	0.32	0.13	0.36	0.45	0.09
Employees in service sectors in million	0.37	0.17	0.41	0.50	0.12
Residents in million	0.31	0.12	0.33	0.44	0.08
Built-up volumes in million m^3	0.29	0.12	0.32	0.34	0.07
Built area in 1970 in km^2	0.22	0.05	0.18	0.36	0.03
Built area in 2010 in km^2	0.19	0.05	0.17	0.33	0.03
Area covered in km^2	0.04	0.01	0.03	0.07	< 0.01

Note: Shares of area covered do not sum to one because not every part of each region’s area is captured by the clusters. Some grid cells do not host any type of activity and thus have been omitted.

Figure 3. Micro layer (source: Own elaboration based on the data described above).

Table 4. Thresholds and descriptions of the micro layer’s types.

	Indicators (based on z-scores)
Subcenter type	Job density	Service sector job density	Population density	Built-up volume	Land consumption 1970–2010
(1) High density core area	> 4	> 4	n.s.	> 2	n.s.
(2) Extended core & mid-sized centers	> 2/n.s.	n.s./> 2	> 2	> 1	n.s.
(3) (Sub-) urban edge densification	> 1.5/n.s.	n.s./> 1.5	n.s.	> 0	n.s.
(4) Commercial area with service sector orientation	< 0	> 0	n.s.	n.s.	> 0
(5) Other suburban commercial area	> 0	< 0	n.s.	n.s.	> 0

Note: n.s. = not specified || If two sets of thresholds are provided for a type, either of them has to apply (Source: Own elaboration)

Table 5. Region-wide averages for each micro type.

Average values	Frankfurt region	Cologne region	Munich region	Stuttgart region
	Type 1: High density core area
Observations (n, km^2)	8	8	3	5
Employment density (employees/km^2)	5,478	4,467	7,624	4,912
Service sectors employment density (employees/km^2)	2,428	1,808	3,553	1,807
Residential density (residents/km^2)	16,200	13,437	20,546	13,802
Built-up volume density (million m^3/km^2)	4.14	4.98	6.20	3.13
Land consumption 1970–2010 (m^2/km^2)	5,423	2,011	2,783	7,526
	Type 2: Extended core & mid-sized centers
Observations (n, km^2)	15	28	10	13
Employment density (employees/km^2)	3,028	2,873	5,822	2,554
Service sectors employment density (employees/km^2)	1,352	1,031	2,524	823
Residential density (residents/km^2)	9,767	9,567	15,620	7,860
Built-up volume density (million m^3/km^2)	2.76	3.32	5.74	2.25
Land consumption 1970–2010 (m^2/km^2)	2,312	1,421	4,807	18,121
	Type 3: (Sub-) urban edge densification
Observations (n, km^2)	24	36	11	43
Employment density (employees/km^2)	2,189	1,997	4,455	2,044
Service sectors employment density (employees/km^2)	913	671	1,750	567
Residential density (residents/km^2)	7,375	6,577	11,840	6,211
Built-up volume density (million m^3/km^2)	2.04	2.45	3.47	1.17
Land consumption 1970–2010 (m^2/km^2)	5,360	14,502	2,070	64,808
	Type 4: Commercial area with service sector orientation
Observations (n, km^2)	7	3	2	6
Employment density (employees/km^2)	936	681	1,644	731
Service sectors employment density (employees/km^2)	388	238	752	251
Residential density (residents/km^2)	2,859	2,415	4,313	2,311
Built-up volume density (million m^3/km^2)	0.87	0.72	0.91	0.43
Land consumption 1970–2010 (m^2/km^2)	129,502	88,207	81,232	101,603
	Type 5: Other suburban commercial area
Observations (n, km^2)	12	12	7	20
Employment density (employees/km^2)	1,182	814	2,059	947
Service sectors employment density (employees/km^2)	312	208	574	185
Residential density (residents/km^2)	3,605	2,680	5,614	2,859
Built-up volume density (million m^3/km^2)	0.73	0.93	1.35	0.60
Land consumption 1970–2010 (m^2/km^2)	179,500	107,436	112,913	129,802
	Residual
Observations (n, km^2)	729	843	296	766
Employment density (employees/km^2)	902	578	1,484	694
Service sectors employment density (employees/km^2)	296	168	536	173
Residential density (residents/km^2)	2,997	2,010	4,536	2,095
Built-up volume density (million m^3/km^2)	0.72	0.89	1.52	0.53
Land consumption 1970–2010 (m^2/km^2)	51,989	27,875	32,350	55,390

(Source: Own calculations based on the data described above)

Table

	Cologne region	Frankfurt region	Munich region	Stuttgart region^a	Entire sample of regions
Component 1: Socioeconomic importance	employees firms residents employee density	employees firms residents employee density area 1970	employees firms residents employee density area 1970 built area	employees firms residents employee density area 1970 number of buildings	employees firms residents employee density area 1970
Expl. total variance	0.37	0.36	0.40	0.40	0.36
Component 2: Functional balance and grain	employees per residents^b average firm size number of buildings	employees per residents^b average firm size number of buildings	employees per residents^b average firm size number of buildings	employees per residents^b average firm size newly built area 2000-10	employees per residents^b average firm size number of buildings newly built area 2000-10
Expl. total variance	0.15	0.14	0.15	0.13	0.14
Component 3: Accessibility	linear distance to CBD next highway entrance ramp next airport next main station distance to main city’s center^c	linear distance to CBD next highway entrance ramp next airport distance to main city’s center^c	linear distance to CBD next highway entrance ramp next main station distance to main city’s center^c	linear distance to CBD next highway entrance ramp next airport distance to main city’s center^c	linear distance to CBD next highway entrance ramp next airport next main station distance to main city’s center^c
Expl. total variance	0.15	0.13	0.14	0.15	0.13
Component 4: Built environment	area 1970 building area built-up volumes floor space average building size newly built area 1980-90	building area built-up volumes floor space average building size	built-up volumes floor space average building size newly built area 1970-80 newly built area 1980-90 newly built area 2000-10	building area built-up volumes average building size	building area built-up volumes floor space average building size newly built area 1980-90 newly built area 2000-10
Expl. total variance	0.11	0.11	0.07	0.08	0.09
Component 5: Residual	x	newly built area 1980-90 newly built area 1990-00 newly built area 2000-10 next main station	x	newly built area 1990-00 next main station	x
Expl. total variance	x	0.05	x	0.05	x
Expl. total variance	0.78	0.79	0.76	0.81	0.72

^aComponent 2 is accessibility and component 3 is functional balance and grain, which the shares of explained total variance also reflect. However, this order has been reversed here for ease of reading || b Just all employees are considered. The subgroup of employees in service sectors is not considered separately|| c Largest city in the case of multiple core cities (Source: Own elaboration)

Figure B. Mapping of the 3-cluster solution after a joint analysis of all study regions (Source: Own elaboration based on the data described above).

Wurm, Michael, d’Angelo, Pablo, Reinartz, Peter, & Taubenböck, Hannes (2014). Investigating the applicability of Cartosat-1 DEMs and topographic maps to localize large-area urban mass concentration. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (J-STARS), 7(10), 4138–4152.

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