Information about the municipality Blankenberg:

View the information on over 100 topics about the municipality Blankenberg! With charts, links to more information & an overview of all figures in 1 table.
View the information on over 100 topics about the municipality Blankenberg! With charts, links to more information & an overview of all figures in 1 table.
Population numbers per year
The number of inhabitants in the municipality Blankenberg

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Population numbers in the municipality Blankenberg for the years 2009 thru 2019.

The number of inhabitants is the number of persons as registered in the population register on January 1st.

Population at the map of Blankenberg
Map of Rural district Saale-Orla-Kreis with the population per municipality.Municipality Blankenberg is highlighted with a red edge.. This page shows a lot of information about residents (such as the distribution by age groups, family composition, gender, native or German with an immigration background, ...), homes (numbers, types, price development, use, type of property, ...) and more (car ownership, energy consumption, ...) based on open data from the German Federal Agency for Cartography, the Federal Statistical Office (DESTATIS), the Regional Statistical Offices and various other sources!

Map of Rural district Saale-Orla-Kreis with the population per municipality.Municipality Blankenberg is highlighted with a red edge. The numbers at the map represent the following municipalities: 1: municipality Stanau, 2: municipality Geroda, 3: municipality Rosendorf, 4: municipality city Triptis, 5: municipality Mittelpöllnitz ...Show more... Map of Rural district Saale-Orla-Kreis with the population per municipality.Municipality Blankenberg is highlighted with a red edge. The numbers at the map represent the following municipalities: 1: municipality Stanau, 2: municipality Geroda, 3: municipality Rosendorf, 4: municipality city Triptis, 5: municipality Mittelpöllnitz, 6: municipality Dreitzsch, 7: municipality city Neustadt an der Orla, 8: municipality Miesitz, 9: municipality Langenorla, 10: municipality Lausnitz b. Neustadt an der Orla, 11: municipality Oppurg, 12: municipality Schmieritz, 13: municipality Lemnitz, 14: municipality Kospoda, 15: municipality Tömmelsdorf, 16: municipality city Pößneck, 17: municipality Krölpa, 18: municipality Weira, 19: municipality Nimritz, 20: municipality Döbritz, 21: municipality Oberoppurg, 22: municipality Solkwitz, 23: municipality Linda b. Neustadt an der Orla, 24: municipality Bodelwitz, 25: municipality Quaschwitz, 26: municipality Gertewitz, 27: municipality Moßbach, 28: municipality Grobengereuth, 29: municipality Wernburg, 30: municipality city Ranis, 31: municipality Dreba, 32: municipality Peuschen, 33: municipality Dittersdorf, 34: municipality Tegau, 35: municipality Knau, 36: municipality Seisla, 37: municipality Moxa, 38: municipality Schmorda, 39: municipality Keila, 40: municipality Plothen, 41: municipality Bucha, 42: municipality Göschitz, 43: municipality Wilhelmsdorf, 44: municipality Pörmitz, 45: municipality Gössitz, 46: municipality Schöndorf, 47: municipality Paska, 48: municipality Volkmannsdorf, 49: municipality Löhma, 50: municipality city Ziegenrück, 51: municipality Neundorf (bei Schleiz), 52: municipality Kirschkau, 53: municipality Oettersdorf, 54: municipality Eßbach, 55: municipality Crispendorf, 56: municipality Görkwitz, 57: municipality city Schleiz, 58: municipality Burgk, 59: municipality Remptendorf, 60: municipality city Saalburg-Ebersdorf, 61: municipality city Tanna, 62: municipality city Bad Lobenstein, 63: municipality city Wurzbach, 64: municipality city Gefell, 65: municipality Birkenhügel, 66: municipality Neundorf (bei Lobenstein), 67: municipality city Hirschberg, 68: municipality Pottiga, 69: municipality Harra, 70: municipality Blankenberg, 71: municipality Schlegel, 72: municipality Blankenstein ...Show less...

Population per age group
The percentage of inhabitants per age group in the municipality Blankenberg

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Municipality Blankenberg, 2019, age groups.

Population, age groups: percentage of inhabitants per age category.

The number of rooms per house (dwelling)
The number of rooms of the houses in the municipality Blankenberg

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Municipality Blankenberg, 2019, number of rooms per house.

The percentage shows the relative share of houses per category based on the numer of rooms: 1 to 2 rooms, 3 to 4 rooms or 5 rooms or more. This is based on the total number of rooms as identified for all dwellings in the municipality Blankenberg.

Data about more than 100 topics!

The table below shows data for more than 100 topics as most recently available for the municipality Blankenberg. Select a category to display the related topics:

BusinessValueUnitYear
Businessesno dataNumber2015
Active personsno dataNumber2015
Gross wagesno dataEuro2015
DwellingsValueUnitYear
Houses 1 room1Number2019
Houses 2 rooms12Number2019
Houses 3 rooms89Number2019
Houses 4 rooms138Number2019
Houses 5 rooms127Number2019
Houses 6 rooms83Number2019
Houses 7+ rooms 72Number2019
Houses 1-2 rooms13Number2019
Houses 3-4 rooms227Number2019
Houses 5+ rooms282Number2019
1-2 rooms2%Percentage2019
3-4 rooms43%Percentage2019
5+ rooms54%Percentage2019
ElectionsValueUnitYear
Voters Bundestag812,00Number2017
Voter turnout Bundestag68Number2017
Votes valid Bundestag545Number2017
Votes Bundestag CDU/CSU174Number2017
Votes Bundestag SPD100Number2017
Votes Bundestag GRÜNE15Number2017
Votes Bundestag FDP20Number2017
Votes Bundestag DIE LINKE82Number2017
Votes Bundestag AfD128Number2017
Votes Bundestag other parties26Number2017
Votes Bundestag total545Number2017
% Votes Bundestag CDU/CSU21%Percentage2017
% Votes Bundestag SPD12%Percentage2017
% Votes Bundestag GRÜNE2%Percentage2017
% Votes Bundestag FDP2%Percentage2017
% Votes Bundestag DIE LINKE10%Percentage2017
% Votes Bundestag AfD16%Percentage2017
% Votes Bundestag other parties3%Percentage2017
EmploymentValueUnitYear
Employeesno dataNumber2018
Employees maleno dataNumber2018
Employees femaleno dataNumber2018
Employees foreignerno dataNumber2018
Employees male foreignerno dataNumber2018
Employees female foreignerno dataNumber2018
Unemployed17Number2018
Unemployed foreigners2Number2018
Unemployed severely disabled2Number2018
Unemployed 15-200Number2018
Unemployed 15-250Number2018
Unemployed 55-658Number2018
Unemployed long-term5Number2018
% Unemployed2%Percentage2018
% Unemployed foreigners0%Percentage of the population2018
% Unemployed severely disabled0%Percentage of the population2018
% Unemployed 15-200%Percentage of the population2018
% Unemployed 15-250%Percentage of the population2018
% Unemployed 55-651%Percentage of the population2018
% Unemployed long-term1%Percentage of the population2018
IncomeValueUnitYear
Income receivers397Number2015
Income total€12.618Euro2015
Income tax€1.529Euro2015
PopulationValueUnitYear
Population886Number2019
Men450Number2019
Women436Number2019
% Men51%Percentage2019
% Women49%Percentage2019
0-1893Number2019
18-3064Number2019
30-45127Number2019
45-60247Number2019
18-60438Number2019
60-75202Number2019
60+355Number2019
Average age52Average number2019
Average age male52Average number2019
Average age female53Average number2019
Births3Number2018
Births male1Number2018
Births female2Number2018
1K Births3Number per 1000 inhabitants2018
Deaths14Number2018
Deaths male4Number2018
Deaths female10Number2018
1K Deaths16Number2018
0-317Number2019
Girls 0-35Number2019
Boys 0-312Number2019
3-611Number2019
Girls 3-68Number2019
Boys 3-63Number2019
6-1022Number2019
10-1523Number2019
15-1820Number2019
18-2016Number2019
20-2522Number2019
25-3026Number2019
30-3531Number2019
35-4044Number2019
40-4552Number2019
45-5072Number2019
50-5575Number2019
55-60100Number2019
60-6586Number2019
65-75116Number2019
Women 65-7056Number2019
Men 65-7060Number2019
75+153Number2019
Women 75+89Number2019
Men 75+64Number2019
% 0-106%Percentage2019
% 10-185%Percentage2019
% 18-307%Percentage2019
% 30-4514%Percentage2019
% 45-6028%Percentage2019
% 60+40%Percentage2019
Real estateValueUnitYear
Property tax A revenueno dataEurono data
Property tax B revenueno dataEurono data
Trade tax actual revenueno dataEurono data
Property tax A basic amountno dataEurono data
Property tax B basic amountno dataEurono data
Trade tax basic amountno dataEurono data
Property tax A rateno dataEurono data
Property tax B rateno dataEurono data
Trade tax rateno dataEurono data
Real tax raising forceno dataEurono data
Trade tax levyno dataEurono data
Trade tax netno dataEurono data
Community share in income taxno dataEurono data
Community share in sales taxno dataEurono data
Tax revenueno dataEurono data
RegionalValueUnitYear
Region code160755008003Code2019
Region code 8 digits16075003Code16075003
Sorting code160755008003Code160755008003
Sorting code 8 digits16075003Code16075003
Region nameBlankenbergName2019
Regional level6Categorical type2019
Region typeMunicipalityCategorical type2019
Region type detailmunicipalityCategorical type2019
Region name with typemunicipality BlankenbergName2019
Region name in GermanGemeinde BlankenbergName2019
Direct subregionsno dataNumber2019
NUTS codeDEG0KCode2019
Area4Area in km²2019
ReligionValueUnitYear
Roman Catholic church12Number2011
Protestant church383Number2011
Other or none600Number2011
% Roman Catholic church1%Percentage2011
% Protestant church38%Percentage2011
% Other or none60%Percentage2011
Roman Catholic church German12Number2011
Protestant church German383Number2011
Other or none German600Number2011
% Roman Catholic church German1%Percentage2011
% Protestant church German38%Percentage2011
% Other or none German Foreign60%Percentage2011
Roman Catholic church Foreign0Number2011
Protestant church Foreign0Number2011
Other or none Foreign0Number2011
% Roman Catholic church Foreignno dataPercentageno data
% Protestant church Foreignno dataPercentageno data
% Other or none Foreignno dataPercentageno data
Open data sources used

Data is used from multiple German open data providers. See this description of the sources with the definitions of all regional topics.

Sources & definitions
Under development
Work is in progress to add more information to this page

This page will be further expanded with more topics in clear graphs. This will be done in several iterations in the coming weeks.