Datasets:

Khaledc83
/

german-cities-open-data

slug stringlengths 3 21	name_de stringlengths 3 21	state stringclasses 16 values	ags int64 1M 16.1M	wikidata_qid stringlengths 3 6	lat float64 48 54.3	lon float64 6.08 14.3	coverage stringclasses 2 values	air_uba_no2 float64 64 149 ⌀	air_uba_pm10 float64 4 20 ⌀	air_uba_pm25 float64 5 50 ⌀	base_area_km2 float64 44.9 891 ⌀	base_population float64 98.7k 3.78M ⌀	traffic_roadworks_count float64 61 96 ⌀	weather_condition stringclasses 1 value	weather_humidity float64 27 68	weather_temperature_c float64 22.7 32.9
berlin	Berlin	BE	11,000,000	Q64	52.52	13.405	full	null	null	null	891.12	3,782,202	71	dry	56	28
hamburg	Hamburg	HH	2,000,000	Q1055	53.5511	9.9937	full	null	null	null	755.09	1,910,160	69	dry	67	24.5
muenchen	München	BY	9,162,000	Q1726	48.1374	11.5755	full	null	18	20	310.71	1,510,378	61	dry	45	27.9
koeln	Köln	NW	5,315,000	Q365	50.9375	6.9603	full	null	null	null	405.01	1,087,353	96	dry	48	31.6
frankfurt-am-main	Frankfurt am Main	HE	6,412,000	Q1794	50.1109	8.6821	full	null	null	null	248.31	775,790	null	dry	31	30.6
stuttgart	Stuttgart	BW	8,111,000	Q1022	48.7758	9.1829	full	null	null	16	207.35	633,484	null	dry	36	30.6
duesseldorf	Düsseldorf	NW	5,111,000	Q1718	51.2277	6.7735	full	null	null	null	217.41	631,217	null	dry	49	30
leipzig	Leipzig	SN	14,713,000	Q2079	51.3397	12.3731	full	64	10	21	297.8	619,879	null	dry	42	29.5
dortmund	Dortmund	NW	5,913,000	Q1295	51.5136	7.4653	full	null	null	null	280.71	595,471	null	dry	52	30.3
essen	Essen	NW	5,113,000	Q2066	51.4556	7.0116	full	null	16	16	210.34	586,608	null	dry	55	28.9
bremen	Bremen	HB	4,011,000	Q24879	53.0793	8.8017	full	77	5	6	317.88	577,026	null	dry	52	28
dresden	Dresden	SN	14,612,000	Q1731	51.0504	13.7373	full	null	null	null	328.48	566,222	null	dry	49	27.9
hannover	Hannover	NI	3,241,001	Q1715	52.3759	9.732	full	null	null	null	204.15	548,186	null	dry	58	28.2
nuernberg	Nürnberg	BY	9,564,000	Q2090	49.4521	11.0767	full	null	null	null	186.45	526,091	null	dry	40	29.7
duisburg	Duisburg	NW	5,112,000	Q2100	51.4344	6.7623	full	null	null	null	232.8	503,707	null	dry	52	29.1
bochum	Bochum	NW	5,911,000	Q2103	51.4818	7.2162	full	null	null	null	145.66	366,385	null	dry	49	28.9
wuppertal	Wuppertal	NW	5,124,000	Q2107	51.2562	7.1508	full	null	11	29	168.39	358,938	null	dry	59	27.7
bielefeld	Bielefeld	NW	5,711,000	Q2112	52.0302	8.5325	full	null	null	null	258.82	338,410	null	dry	54	28.9
bonn	Bonn	NW	5,314,000	Q586	50.7374	7.0982	full	null	null	null	141.06	335,789	null	dry	52	29.1
muenster	Münster	NW	5,515,000	Q2742	51.9607	7.6261	full	null	null	null	null	null	null	dry	55	29.2
wiesbaden	Wiesbaden	HE	6,414,000	Q1721	50.0826	8.24	full	null	null	null	203.93	285,522	null	dry	47	27.6
kiel	Kiel	SH	1,002,000	Q1707	54.3233	10.1228	full	null	null	null	118.65	248,873	null	dry	68	23.1
mainz	Mainz	RP	7,315,000	Q1720	49.9929	8.2473	full	null	null	null	97.73	222,889	null	dry	39	31.4
magdeburg	Magdeburg	ST	15,003,000	Q1733	52.1205	11.6276	full	null	13	32	201.01	240,114	null	dry	54	28.4
erfurt	Erfurt	TH	16,051,000	Q1729	50.9787	11.0328	full	78	10	5	269.91	215,199	null	dry	44	28.6
potsdam	Potsdam	BB	12,054,000	Q1711	52.3906	13.0645	full	null	null	null	188.26	187,119	null	dry	61	26
saarbruecken	Saarbrücken	SL	10,041,100	Q1724	49.2402	6.9969	full	108	16	5	167.52	183,509	null	dry	36	31.5
schwerin	Schwerin	MV	13,004,000	Q1709	53.6355	11.4012	full	null	null	null	130.52	98,733	null	dry	61	25.4
aachen	Aachen	NW	5,334,002	Q1017	50.7762	6.0838	auto	null	null	null	160.85	252,769	null	dry	55	28.4
augsburg	Augsburg	BY	9,761,000	Q2749	48.3689	10.8978	auto	null	20	31	146.87	303,150	null	dry	47	27.2
bergisch-gladbach	Bergisch Gladbach	NW	5,378,004	Q3117	50.9917	7.1367	auto	null	null	null	83.09	112,660	null	dry	48	28.8
bottrop	Bottrop	NW	5,512,000	Q3069	51.5232	6.9253	auto	null	null	null	100.61	118,705	null	dry	55	28.9
braunschweig	Braunschweig	NI	3,101,000	Q2773	52.2692	10.5211	auto	null	null	null	192.7	252,066	null	dry	57	28.2
bremerhaven	Bremerhaven	HB	4,012,000	Q2706	53.55	8.5833	auto	null	null	null	93.66	114,677	null	dry	66	23.2
chemnitz	Chemnitz	SN	14,511,000	Q2795	50.8333	12.9167	auto	null	null	null	221.05	250,681	null	dry	53	26.4
cottbus	Cottbus	BB	12,052,000	Q3214	51.7608	14.3319	auto	null	null	null	165.63	100,010	null	dry	45	29
darmstadt	Darmstadt	HE	6,411,000	Q2973	49.8667	8.65	auto	null	null	null	122.07	164,792	null	dry	49	28.9
erlangen	Erlangen	BY	9,562,000	Q3126	49.5925	11.005	auto	null	null	null	76.96	117,806	null	dry	41	30.1
freiburg-im-breisgau	Freiburg im Breisgau	BW	8,311,000	Q2833	47.995	7.85	auto	null	null	null	153.04	237,244	null	dry	40	31.2
fuerth	Fürth	BY	9,563,000	Q3075	49.4783	10.9903	auto	null	11	null	63.35	132,032	null	dry	40	29.7
gelsenkirchen	Gelsenkirchen	NW	5,513,000	Q2765	51.5103	7.0942	auto	null	18	50	104.94	265,885	null	dry	49	28.9
goettingen	Göttingen	NI	3,159,016	Q3033	51.5339	9.9356	auto	null	null	null	116.93	120,261	null	dry	61	28.5
guetersloh	Gütersloh	NW	5,754,008	Q3771	51.9	8.3833	auto	null	null	null	112.02	102,464	null	dry	54	28.9
hagen	Hagen	NW	5,914,000	Q2871	51.3594	7.475	auto	null	null	null	160.45	190,490	null	dry	52	28.1
halle-saale	Halle (Saale)	ST	15,002,000	Q2814	51.4828	11.9697	auto	null	null	null	135.03	242,172	null	dry	43	29.5
hamm	Hamm	NW	5,915,000	Q2880	51.6814	7.8192	auto	null	null	null	226.43	180,761	null	dry	50	29.9
hanau	Hanau	HE	6,435,014	Q3802	50.1328	8.9169	auto	149	11	7	76.47	103,184	null	dry	29	32.5
heidelberg	Heidelberg	BW	8,221,000	Q2966	49.4122	8.71	auto	null	null	null	108.89	162,960	null	dry	36	31.7
heilbronn	Heilbronn	BW	8,121,000	Q715	49.1404	9.218	auto	null	null	null	99.89	130,093	null	dry	42	30
herne	Herne	NW	5,916,000	Q2904	51.5426	7.219	auto	null	null	null	51.42	157,896	null	dry	49	28.9
hildesheim	Hildesheim	NI	3,254,021	Q3185	52.15	9.95	auto	null	12	28	92.29	102,325	null	dry	54	28.7
ingolstadt	Ingolstadt	BY	9,161,000	Q3004	48.7631	11.425	auto	null	null	null	133.35	142,308	null	dry	59	25.5
jena	Jena	TH	16,053,000	Q3150	50.9272	11.5864	auto	null	null	null	114.76	109,353	null	dry	44	29
kaiserslautern	Kaiserslautern	RP	7,312,000	Q3758	49.4447	7.7689	auto	99	4	5	139.7	101,486	null	dry	35	31.4
karlsruhe	Karlsruhe	BW	8,212,000	Q1040	49.0167	8.4	auto	null	19	16	173.42	309,964	null	dry	27	32.9
kassel	Kassel	HE	6,611,000	Q2865	51.3158	9.4979	auto	null	16	40	106.78	204,687	null	dry	52	27.3
koblenz	Koblenz	RP	7,111,000	Q3104	50.3597	7.5978	auto	null	null	null	105.25	115,298	null	dry	34	32.1
krefeld	Krefeld	NW	5,114,000	Q2805	51.3333	6.5667	auto	null	null	null	137.77	228,550	null	dry	52	30.6
leverkusen	Leverkusen	NW	5,316,000	Q2938	51.0333	6.9833	auto	99	10	6	78.87	175,300	null	dry	48	27.7
ludwigshafen-am-rhein	Ludwigshafen am Rhein	RP	7,314,000	Q2910	49.4811	8.4353	auto	null	null	null	77.43	176,110	null	dry	36	31.7
luebeck	Lübeck	SH	1,003,000	Q2843	53.8697	10.6864	auto	null	null	null	214.21	219,044	null	dry	62	25.1
mannheim	Mannheim	BW	8,222,000	Q2119	49.4878	8.4661	auto	null	16	27	144.97	316,877	null	dry	36	31.7
moenchengladbach	Mönchengladbach	NW	5,116,000	Q2758	51.2	6.4333	auto	null	null	null	170.47	268,943	null	dry	67	29
moers	Moers	NW	5,170,024	Q3132	51.4592	6.6197	auto	null	null	null	67.68	105,606	null	dry	52	29.1
muelheim-an-der-ruhr	Mülheim an der Ruhr	NW	5,117,000	Q2899	51.4275	6.8825	auto	null	null	null	91.28	173,255	null	dry	55	28.9
neuss	Neuss	NW	5,162,024	Q2948	51.2003	6.6939	auto	null	null	null	null	null	null	dry	49	30
oberhausen	Oberhausen	NW	5,119,000	Q2838	51.4699	6.8514	auto	null	16	41	77.09	211,099	null	dry	55	28.9
offenbach-am-main	Offenbach am Main	HE	6,413,000	Q3042	50.1	8.7667	auto	null	null	null	44.88	135,490	null	dry	35	30.4
oldenburg	Oldenburg	NI	3,403,000	Q2936	53.1439	8.2139	auto	null	12	29	103.09	174,629	null	dry	64	26.6
osnabrueck	Osnabrück	NI	3,404,000	Q2916	52.2789	8.0431	auto	null	null	null	119.8	166,960	null	dry	59	26.6
paderborn	Paderborn	NW	5,774,032	Q2971	51.7167	8.7667	auto	null	null	null	179.59	155,749	null	dry	56	28.9
pforzheim	Pforzheim	BW	8,231,000	Q3046	48.8909	8.703	auto	null	null	null	98.07	128,992	null	dry	49	28.8
recklinghausen	Recklinghausen	NW	5,562,032	Q3050	51.6167	7.2	auto	null	null	null	66.5	111,693	null	dry	49	28.9
regensburg	Regensburg	BY	9,362,000	Q2978	49.0167	12.0833	auto	null	15	27	80.85	159,465	null	dry	43	28.5
remscheid	Remscheid	NW	5,120,000	Q3097	51.1799	7.1944	auto	null	null	null	74.52	112,970	null	dry	59	27.7
reutlingen	Reutlingen	BW	8,415,061	Q3085	48.4833	9.2167	auto	null	15	40	87.04	118,528	null	dry	40	30.6
rostock	Rostock	MV	13,003,000	Q2861	54.0833	12.1333	auto	null	null	null	181.36	210,795	null	dry	62	22.7
salzgitter	Salzgitter	NI	3,102,000	Q3200	52.1503	10.3593	auto	null	null	null	224.49	105,039	null	dry	57	28.2
siegen	Siegen	NW	5,970,040	Q3167	50.8756	8.0167	auto	null	null	null	114.69	102,114	null	dry	52	25.9
solingen	Solingen	NW	5,122,000	Q2942	51.1719	7.0847	auto	null	null	null	89.54	161,545	null	dry	59	27.7
trier	Trier	RP	7,211,000	Q3138	49.7557	6.6394	auto	null	15	14	117.07	112,737	null	dry	37	30.3
ulm	Ulm	BW	8,421,000	Q3012	48.3986	9.9911	auto	null	null	null	118.68	129,942	null	dry	43	27.7
wolfsburg	Wolfsburg	NI	3,103,000	Q3014	52.4231	10.7872	auto	null	null	null	204.61	127,256	null	dry	58	28.4
wuerzburg	Würzburg	BY	9,663,000	Q2999	49.7944	9.9294	auto	null	null	null	87.66	132,215	null	dry	35	30.5

InfraNode German Cities Open-Data Snapshot

Ein reproduzierbarer, offen lizenzierter Querschnitt von Infrastruktur- und Umweltdaten für 84+ deutsche Städte, erzeugt aus der öffentlichen InfraNode-API. Eine Zeile je Stadt.

Inhalt

Bereich	Felder	Quelle
Stammdaten	`slug`, `name_de`, `state`, `ags`, `wikidata_qid`, `lat`, `lon`, `base_population`, `base_area_km2`	Wikidata (CC0)
Wetter	`weather_temperature_c`, `weather_humidity`, `weather_condition`	DWD (GeoNutzV)
Luftqualität	`air_uba_pm10`, `air_uba_pm25`, `air_uba_no2`, `air_uba_o3`	Umweltbundesamt (dl-de/by-2.0)
Verkehr	`traffic_roadworks_count`	Autobahn GmbH / BASt (dl-de/by-2.0)

Es wurden ausschließlich Quellen mit offener Lizenz übernommen. Quellen mit unklarer Lizenz (OpenAQ) oder Share-Alike (OpenStreetMap/ODbL) sind bewusst ausgeschlossen.

Lizenz und Namensnennung

Mischung offener Lizenzen, je Spalte dokumentiert. Pflicht-Namensnennung:

Wikidata (CC0)
Deutscher Wetterdienst, DWD (GeoNutzV)
Umweltbundesamt, UBA (dl-de/by-2.0)
Bundesanstalt für Straßenwesen / Autobahn GmbH (dl-de/by-2.0)

Reproduktion und Code

Code, Sammel-Skript und eine täglich wachsende Zeitreihe: https://github.com/street1983nk/infranode-dataset

Zitation

Cherif, K. (2026). InfraNode German Cities Open-Data Snapshot. Zenodo. https://doi.org/10.5281/zenodo.20752355

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