In 2022, there were around 1.39 billion Catholics worldwide, compared to 1.38 billion in 2021. In more than 20 years, the global Catholic population grew by approximately 194 million people. The Catholic population is growing fast in Africa and in the Americas, while it is declining in Europe.

Catholics to Population {title at top of page}Data Developers: Burhans, Molly A., Cheney, David M., Emege, Thomas, Gerlt, R.. . “Catholics to Population {title at top of page}”. Scale not given. Version 1.0. MO and CT, USA: GoodLands Inc., Catholic Hierarchy, Environmental Systems Research Institute, Inc., 2019.Web map developer: Molly Burhans, October 2019Web app developer: Molly Burhans, October 2019GoodLands’ polygon data layers, version 2.0 for global ecclesiastical boundaries of the Roman Catholic Church:Although care has been taken to ensure the accuracy, completeness and reliability of the information provided, due to this being the first developed dataset of global ecclesiastical boundaries curated from many sources it may have a higher margin of error than established geopolitical administrative boundary maps. Boundaries need to be verified with appropriate Ecclesiastical Leadership. The current information is subject to change without notice. No parties involved with the creation of this data are liable for indirect, special or incidental damage resulting from, arising out of or in connection with the use of the information. We referenced 1960 sources to build our global datasets of ecclesiastical jurisdictions. Often, they were isolated images of dioceses, historical documents and information about parishes that were cross checked. These sources can be viewed here:https://docs.google.com/spreadsheets/d/11ANlH1S_aYJOyz4TtG0HHgz0OLxnOvXLHMt4FVOS85Q/edit#gid=0To learn more or contact us please visit: https://good-lands.org/The Catholic Leadership global maps information is derived from the Annuario Pontificio, which is curated and published by the Vatican Statistics Office annually, and digitized by David Cheney at Catholic-Hierarchy.org -- updated are supplemented with diocesan and news announcements. GoodLands maps this into global ecclesiastical boundaries. Admin 3 Ecclesiastical Territories:Burhans, Molly A., Cheney, David M., Gerlt, R.. . “Admin 3 Ecclesiastical Territories For Web”. Scale not given. Version 1.2. MO and CT, USA: GoodLands Inc., Environmental Systems Research Institute, Inc., 2019.Derived from:Global Diocesan Boundaries:Burhans, M., Bell, J., Burhans, D., Carmichael, R., Cheney, D., Deaton, M., Emge, T. Gerlt, B., Grayson, J., Herries, J., Keegan, H., Skinner, A., Smith, M., Sousa, C., Trubetskoy, S. “Diocesean Boundaries of the Catholic Church” [Feature Layer]. Scale not given. Version 1.2. Redlands, CA, USA: GoodLands Inc., Environmental Systems Research Institute, Inc., 2016.Using: ArcGIS. 10.4. Version 10.0. Redlands, CA: Environmental Systems Research Institute, Inc., 2016.Boundary ProvenanceStatistics and Leadership DataCheney, D.M. “Catholic Hierarchy of the World” [Database]. Date Updated: August 2019. Catholic Hierarchy. Using: Paradox. Retrieved from Original Source.Catholic HierarchyAnnuario Pontificio per l’Anno .. Città del Vaticano :Tipografia Poliglotta Vaticana, Multiple Years.The data for these maps was extracted from the gold standard of Church data, the Annuario Pontificio, published yearly by the Vatican. The collection and data development of the Vatican Statistics Office are unknown. GoodLands is not responsible for errors within this data. We encourage people to document and report errant information to us at data@good-lands.org or directly to the Vatican.Additional information about regular changes in bishops and sees comes from a variety of public diocesan and news announcements.

Brazil is the largest Catholic country in the world, with an estimated Catholic population of 140 million, ahead of Mexico and the Philippines, with 101 million and 85 million Catholics, respectively. Nevertheless, Brazil's Catholic population is shrinking. By 2050, today's largest Catholic country could have a majority Protestant population.

The average for 2013 based on 84 countries was 43.2 percent. The highest value was in Poland: 95.2 percent and the lowest value was in Ethiopia: 0.6 percent. The indicator is available from 1960 to 2013. Below is a chart for all countries where data are available.

In 2022, there were 1.39 billion Catholics worldwide, compared to 1.38 billion in 2021. The largest population growth was recorded in Africa, where there were 7.27 million new Catholics in 2022, ahead of the Americas, where the Catholic population grew by six million people. The population declined only in Europe, where there were 474,000 fewer Catholics compared to 2021.

The USA: Catholic Christians as percent of the total population: The latest value from 2013 is 24 percent, unchanged from 24 percent in 2012. In comparison, the world average is 43.2 percent, based on data from 84 countries. Historically, the average for the USA from 1960 to 2013 is 24 percent. The minimum value, 23.9 percent, was reached in 1960 while the maximum of 24 percent was recorded in 1983.

In 2022, there were around 1.39 billion Catholics worldwide, approximately 17.7 percent of the total global population. Even though the Catholic population has increased in absolute numbers, the share of Catholics has always fluctuated around 17 percent since 2010.

Philippines Population: RA: Roman Catholic data was reported at 80,304,061.000 Person in 2015. This records a decrease from the previous number of 92,097,978.000 Person for 2010. Philippines Population: RA: Roman Catholic data is updated yearly, averaging 80,304,061.000 Person from Dec 2000 (Median) to 2015, with 3 observations. The data reached an all-time high of 92,097,978.000 Person in 2010 and a record low of 61,862,898.000 Person in 2000. Philippines Population: RA: Roman Catholic data remains active status in CEIC and is reported by Philippine Statistics Authority. The data is categorized under Global Database’s Philippines – Table PH.G003: Population: Religious: Affiliation.

Top 10 Dioceses with Highest Carbon FootprintBurhans, Molly A., Cheney, David M., Gerlt, Robert, Thompson, Helen. “PerCapita_CO2_Footprint_InDioceses_FULL”. Scale not given. Version 1.0. MO and CT, USA: GoodLands Inc., Environmental Systems Research Institute, Inc., 2019.MethodologyThis is the first global Carbon footprint of the Catholic population. We will continue to improve and develop these data with our research partners over the coming years. While it is helpful, it should also be viewed and used as a "beta" prototype that we and our research partners will build from and improve. The years of carbon data are (2010) and (2015 - SHOWN). The year of Catholic data is 2018. The year of population data is 2016. Care should be taken during future developments to harmonize the years used for catholic, population, and CO2 data.1. Zonal Statistics: Esri Population Data and Dioceses --> Population per dioceses, non Vatican based numbers2. Zonal Statistics: FFDAS and Dioceses and Population dataset --> Mean CO2 per Diocese3. Field Calculation: Population per Diocese and Mean CO2 per diocese --> CO2 per Capita4. Field Calculation: CO2 per Capita * Catholic Population --> Catholic Carbon FootprintAssumption: PerCapita CO2Deriving per-capita CO2 from mean CO2 in a geography assumes that people's footprint accounts for their personal lifestyle and involvement in local business and industries that are contribute CO2. Catholic CO2Assumes that Catholics and non-Catholic have similar CO2 footprints from their lifestyles.Derived from:A multiyear, global gridded fossil fuel CO2 emission data product: Evaluation and analysis of resultshttp://ffdas.rc.nau.edu/About.htmlRayner et al., JGR, 2010 - The is the first FFDAS paper describing the version 1.0 methods and results published in the Journal of Geophysical Research.Asefi et al., 2014 - This is the paper describing the methods and results of the FFDAS version 2.0 published in the Journal of Geophysical Research.Readme version 2.2 - A simple readme file to assist in using the 10 km x 10 km, hourly gridded Vulcan version 2.2 results.Liu et al., 2017 - A paper exploring the carbon cycle response to the 2015-2016 El Nino through the use of carbon cycle data assimilation with FFDAS as the boundary condition for FFCO2."S. Asefi‐Najafabady P. J. Rayner K. R. Gurney A. McRobert Y. Song K. Coltin J. Huang C. Elvidge K. BaughFirst published: 10 September 2014 https://doi.org/10.1002/2013JD021296 Cited by: 30Link to FFDAS data retrieval and visualization: http://hpcg.purdue.edu/FFDAS/index.phpAbstractHigh‐resolution, global quantification of fossil fuel CO2 emissions is emerging as a critical need in carbon cycle science and climate policy. We build upon a previously developed fossil fuel data assimilation system (FFDAS) for estimating global high‐resolution fossil fuel CO2 emissions. We have improved the underlying observationally based data sources, expanded the approach through treatment of separate emitting sectors including a new pointwise database of global power plants, and extended the results to cover a 1997 to 2010 time series at a spatial resolution of 0.1°. Long‐term trend analysis of the resulting global emissions shows subnational spatial structure in large active economies such as the United States, China, and India. These three countries, in particular, show different long‐term trends and exploration of the trends in nighttime lights, and population reveal a decoupling of population and emissions at the subnational level. Analysis of shorter‐term variations reveals the impact of the 2008–2009 global financial crisis with widespread negative emission anomalies across the U.S. and Europe. We have used a center of mass (CM) calculation as a compact metric to express the time evolution of spatial patterns in fossil fuel CO2 emissions. The global emission CM has moved toward the east and somewhat south between 1997 and 2010, driven by the increase in emissions in China and South Asia over this time period. Analysis at the level of individual countries reveals per capita CO2 emission migration in both Russia and India. The per capita emission CM holds potential as a way to succinctly analyze subnational shifts in carbon intensity over time. Uncertainties are generally lower than the previous version of FFDAS due mainly to an improved nightlight data set."Global Diocesan Boundaries:Burhans, M., Bell, J., Burhans, D., Carmichael, R., Cheney, D., Deaton, M., Emge, T. Gerlt, B., Grayson, J., Herries, J., Keegan, H., Skinner, A., Smith, M., Sousa, C., Trubetskoy, S. “Diocesean Boundaries of the Catholic Church” [Feature Layer]. Scale not given. Version 1.2. Redlands, CA, USA: GoodLands Inc., Environmental Systems Research Institute, Inc., 2016.Using: ArcGIS. 10.4. Version 10.0. Redlands, CA: Environmental Systems Research Institute, Inc., 2016.Boundary ProvenanceStatistics and Leadership DataCheney, D.M. “Catholic Hierarchy of the World” [Database]. Date Updated: August 2019. Catholic Hierarchy. Using: Paradox. Retrieved from Original Source.Catholic HierarchyAnnuario Pontificio per l’Anno .. Città del Vaticano :Tipografia Poliglotta Vaticana, Multiple Years.The data for these maps was extracted from the gold standard of Church data, the Annuario Pontificio, published yearly by the Vatican. The collection and data development of the Vatican Statistics Office are unknown. GoodLands is not responsible for errors within this data. We encourage people to document and report errant information to us at data@good-lands.org or directly to the Vatican.Additional information about regular changes in bishops and sees comes from a variety of public diocesan and news announcements.GoodLands’ polygon data layers, version 2.0 for global ecclesiastical boundaries of the Roman Catholic Church:Although care has been taken to ensure the accuracy, completeness and reliability of the information provided, due to this being the first developed dataset of global ecclesiastical boundaries curated from many sources it may have a higher margin of error than established geopolitical administrative boundary maps. Boundaries need to be verified with appropriate Ecclesiastical Leadership. The current information is subject to change without notice. No parties involved with the creation of this data are liable for indirect, special or incidental damage resulting from, arising out of or in connection with the use of the information. We referenced 1960 sources to build our global datasets of ecclesiastical jurisdictions. Often, they were isolated images of dioceses, historical documents and information about parishes that were cross checked. These sources can be viewed here:https://docs.google.com/spreadsheets/d/11ANlH1S_aYJOyz4TtG0HHgz0OLxnOvXLHMt4FVOS85Q/edit#gid=0To learn more or contact us please visit: https://good-lands.org/Esri Gridded Population Data 2016DescriptionThis layer is a global estimate of human population for 2016. Esri created this estimate by modeling a footprint of where people live as a dasymetric settlement likelihood surface, and then assigned 2016 population estimates stored on polygons of the finest level of geography available onto the settlement surface. Where people live means where their homes are, as in where people sleep most of the time, and this is opposed to where they work. Another way to think of this estimate is a night-time estimate, as opposed to a day-time estimate.Knowledge of population distribution helps us understand how humans affect the natural world and how natural events such as storms and earthquakes, and other phenomena affect humans. This layer represents the footprint of where people live, and how many people live there.Dataset SummaryEach cell in this layer has an integer value with the estimated number of people likely to live in the geographic region represented by that cell. Esri additionally produced several additional layers World Population Estimate Confidence 2016: the confidence level (1-5) per cell for the probability of people being located and estimated correctly. World Population Density Estimate 2016: this layer is represented as population density in units of persons per square kilometer.World Settlement Score 2016: the dasymetric likelihood surface used to create this layer by apportioning population from census polygons to the settlement score raster.To use this layer in analysis, there are several properties or geoprocessing environment settings that should be used:Coordinate system: WGS_1984. This service and its underlying data are WGS_1984. We do this because projecting population count data actually will change the populations due to resampling and either collapsing or splitting cells to fit into another coordinate system. Cell Size: 0.0013474728 degrees (approximately 150-meters) at the equator. No Data: -1Bit Depth: 32-bit signedThis layer has query, identify, pixel, and export image functions enabled, and is restricted to a maximum analysis size of 30,000 x 30,000 pixels - an area about the size of Africa.Frye, C. et al., (2018). Using Classified and Unclassified Land Cover Data to Estimate the Footprint of Human Settlement. Data Science Journal. 17, p.20. DOI: http://doi.org/10.5334/dsj-2018-020.What can you do with this layer?This layer is unsuitable for mapping or cartographic use, and thus it does not include a convenient legend. Instead, this layer is useful for analysis, particularly for estimating counts of people living within watersheds, coastal areas, and other areas that do not have standard boundaries. Esri recommends using the Zonal Statistics tool or the Zonal Statistics to Table tool where you provide input zones as either polygons, or raster data, and the tool will summarize the count of population within those zones. https://www.esri.com/arcgis-blog/products/arcgis-living-atlas/data-management/2016-world-population-estimate-services-are-now-available/

Although traditionally a Catholic country, Spain saw a decline in the number of believers over the past years. Compared to 2011, when the share of believers accounted for slightly over 70 percent of the Spanish population, the Catholic community lost approximately 15 percentage points of their faithful by June 2025 with a share of 56.1 percent of the surveyed population. Believers of a religion other than Catholicism accounted for approximately 3.6 percent of the Spanish population in 2025 according to the most recent data. A Catholic majority, a practicing minority Going to mass is no longer a thing in Spain, or so it would seem when looking at the latest statistics about the matter: over 47 percent of those who consider themselves Catholics almost never attend any religious service in June 2025. The not so Catholic Spain Around 37 percent of the surveyed population stated to be either non-believers or full atheists in 2025. Non-believers or people that do not have a religious faith fluctuated over the past years with the latest figures showing a 21 percent of people that categorize themselves as so. The share of Spanish atheists is on the rise according to the most recent surveys, taking up 13.3 percent of respondents in June 2025.

Spain: Catholic Christians as percent of the total population: The latest value from 2013 is 88.3 percent, a decline from 88.8 percent in 2012. In comparison, the world average is 43.2 percent, based on data from 84 countries. Historically, the average for Spain from 1960 to 2013 is 95.5 percent. The minimum value, 88.3 percent, was reached in 2013 while the maximum of 98.5 percent was recorded in 1969.

The overall aim was to conduct a wide-ranging survey of Catholic adults living in Britain, which asked about many aspects of their lives, including their socio-demographic circumstances, the nature and extent of their religious engagement (belonging, behaviour and beliefs), their views of the Catholic Church’s leadership, institutions and teachings, and their social and political attitudes. The survey was conducted online by Savanta ComRes, in October-November 2019. This is a cross-sectional dataset, based on interviews with 1,823 self-identifying Catholics adults in Britain (aged 18 and over).

In recent decades, the religious profile of British society has changed significantly, with a marked increase in 'religious nones', declining proportions identifying as Anglican or with a particular Non-Conformist tradition, an increase in non-denominational Christians, and the spread of non-Christian faiths. Within this wider context, Roman Catholics have remained broadly stable as a proportion of the adult population and represent the second largest Christian denomination in Britain, after Anglicans. However, there have been significant internal and external developments which have affected the institutional church and wider Roman Catholic community in Britain, and which could have shaped how Catholics' think about and engage with their faith and how it impacts their daily lives. Recent years have seen demographic change through significant inflows of Catholic migrants coming from Eastern Europe, the papal visit of Pope Benedict XVI to Britain in autumn 2010 (the first since 1982), Pope Francis's pontificate from 2013 onwards, Catholic leaders' political interventions against 'aggressive secularism' and in other policy debates, and internal crises and debates impacting on the perceived authority of the Catholic Church. The last major academic investigation of the Catholic community (and only in England and Wales) was undertaken in the late 1970s (Hornsby-Smith and Lee 1979; Hornsby-Smith 1987, 1991). It found that the 'distinctive subculture' of the Catholic community in the post-war period was evolving and dissolving in complex ways due to processes of social change and developments within the wider faith, such as the Second Vatican Council (Hornsby-Smith 1987, 1991). It also demonstrated growing internal heterogeneity in Catholics' religious beliefs, practices and social attitudes (Hornsby-Smith 1987, 1991). However, while there has been some recent scholarship on particular topics relating to Catholics and Catholicism in Britain, using both general social surveys and limited one-off denomination-specific opinion polls (Clements 2014a, 2014b; 2016; Bullivant 2016a, 2016b), there has been no systematic academic inquiry into the Roman Catholic population in Britain. In comparison, an academic-led survey series has profiled the Catholic population in the United States on five occasions between 1987 and 2011, with other large-scale surveys carried out in recent years by organisations such as the Pew Research Center. Most existing research into the waning of religious belief, practice, and affiliation in Britain has focused either on the very large, macro level or on the very small, micro level. While both are important and necessary, largely missing has been sustained sociological attention on how secularising trends have affected - and are being mediated within - individual religious communities. This project would undertake such a task for Roman Catholics in Britain, by conducting a large-scale, thematically wide-ranging and nationally representative survey. It would provide a detailed study of personal faith, social attitudes and political engagement within a significant religious minority with distinctive historical roots and in which 'tribal' feelings of belonging have been strong. The core topics would consist of personal faith, religiosity and associational involvement in parish life; attitudes towards leadership and governance within the institutional church; attitudes on social and moral issues; and political attitudes and engagement. It would be thematically wide-ranging and analytically rich, providing a detailed portrait of contemporary social, religious and attitudinal heterogeneity amongst Catholics. By undertaking this large-scale and wide-ranging survey, an important and distinctive contribution would be made to the sociology of religion in Britain in general and to the study of its Catholic population in particular.

aCatholic populations by country from http://www.catholic-hierarchy.org/country/sc1.html[4].bOnly the top 31 Catholic countries with more than 5 million Catholics and countries in which at least 50% of the population is Catholic are included (as well as Canada and Uganda, each with more than 40% Catholic population), which excludes India, Indonesia, Kenya, Nigeria, and Vietnam.cFrom [6], [7].dFrom [8], [9].eFrom [10], [11].fChagas disease is found in every South American and Central American country listed [5].gFrom [31].

Italy: Catholic Christians as percent of the total population: The latest value from 2013 is 84 percent, a decline from 84.7 percent in 2012. In comparison, the world average is 43.2 percent, based on data from 84 countries. Historically, the average for Italy from 1960 to 2013 is 94.5 percent. The minimum value, 84 percent, was reached in 2013 while the maximum of 99.1 percent was recorded in 1960.

PerCapita_CO2_Footprint_InDioceses_FULLBurhans, Molly A., Cheney, David M., Gerlt, R.. . “PerCapita_CO2_Footprint_InDioceses_FULL”. Scale not given. Version 1.0. MO and CT, USA: GoodLands Inc., Environmental Systems Research Institute, Inc., 2019.MethodologyThis is the first global Carbon footprint of the Catholic population. We will continue to improve and develop these data with our research partners over the coming years. While it is helpful, it should also be viewed and used as a "beta" prototype that we and our research partners will build from and improve. The years of carbon data are (2010) and (2015 - SHOWN). The year of Catholic data is 2018. The year of population data is 2016. Care should be taken during future developments to harmonize the years used for catholic, population, and CO2 data.1. Zonal Statistics: Esri Population Data and Dioceses --> Population per dioceses, non Vatican based numbers2. Zonal Statistics: FFDAS and Dioceses and Population dataset --> Mean CO2 per Diocese3. Field Calculation: Population per Diocese and Mean CO2 per diocese --> CO2 per Capita4. Field Calculation: CO2 per Capita * Catholic Population --> Catholic Carbon FootprintAssumption: PerCapita CO2Deriving per-capita CO2 from mean CO2 in a geography assumes that people's footprint accounts for their personal lifestyle and involvement in local business and industries that are contribute CO2. Catholic CO2Assumes that Catholics and non-Catholic have similar CO2 footprints from their lifestyles.Derived from:A multiyear, global gridded fossil fuel CO2 emission data product: Evaluation and analysis of resultshttp://ffdas.rc.nau.edu/About.htmlRayner et al., JGR, 2010 - The is the first FFDAS paper describing the version 1.0 methods and results published in the Journal of Geophysical Research.Asefi et al., 2014 - This is the paper describing the methods and results of the FFDAS version 2.0 published in the Journal of Geophysical Research.Readme version 2.2 - A simple readme file to assist in using the 10 km x 10 km, hourly gridded Vulcan version 2.2 results.Liu et al., 2017 - A paper exploring the carbon cycle response to the 2015-2016 El Nino through the use of carbon cycle data assimilation with FFDAS as the boundary condition for FFCO2."S. Asefi‐Najafabady P. J. Rayner K. R. Gurney A. McRobert Y. Song K. Coltin J. Huang C. Elvidge K. BaughFirst published: 10 September 2014 https://doi.org/10.1002/2013JD021296 Cited by: 30Link to FFDAS data retrieval and visualization: http://hpcg.purdue.edu/FFDAS/index.phpAbstractHigh‐resolution, global quantification of fossil fuel CO2 emissions is emerging as a critical need in carbon cycle science and climate policy. We build upon a previously developed fossil fuel data assimilation system (FFDAS) for estimating global high‐resolution fossil fuel CO2 emissions. We have improved the underlying observationally based data sources, expanded the approach through treatment of separate emitting sectors including a new pointwise database of global power plants, and extended the results to cover a 1997 to 2010 time series at a spatial resolution of 0.1°. Long‐term trend analysis of the resulting global emissions shows subnational spatial structure in large active economies such as the United States, China, and India. These three countries, in particular, show different long‐term trends and exploration of the trends in nighttime lights, and population reveal a decoupling of population and emissions at the subnational level. Analysis of shorter‐term variations reveals the impact of the 2008–2009 global financial crisis with widespread negative emission anomalies across the U.S. and Europe. We have used a center of mass (CM) calculation as a compact metric to express the time evolution of spatial patterns in fossil fuel CO2 emissions. The global emission CM has moved toward the east and somewhat south between 1997 and 2010, driven by the increase in emissions in China and South Asia over this time period. Analysis at the level of individual countries reveals per capita CO2 emission migration in both Russia and India. The per capita emission CM holds potential as a way to succinctly analyze subnational shifts in carbon intensity over time. Uncertainties are generally lower than the previous version of FFDAS due mainly to an improved nightlight data set."Global Diocesan Boundaries:Burhans, M., Bell, J., Burhans, D., Carmichael, R., Cheney, D., Deaton, M., Emge, T. Gerlt, B., Grayson, J., Herries, J., Keegan, H., Skinner, A., Smith, M., Sousa, C., Trubetskoy, S. “Diocesean Boundaries of the Catholic Church” [Feature Layer]. Scale not given. Version 1.2. Redlands, CA, USA: GoodLands Inc., Environmental Systems Research Institute, Inc., 2016.Using: ArcGIS. 10.4. Version 10.0. Redlands, CA: Environmental Systems Research Institute, Inc., 2016.Boundary ProvenanceStatistics and Leadership DataCheney, D.M. “Catholic Hierarchy of the World” [Database]. Date Updated: August 2019. Catholic Hierarchy. Using: Paradox. Retrieved from Original Source.Catholic HierarchyAnnuario Pontificio per l’Anno .. Città del Vaticano :Tipografia Poliglotta Vaticana, Multiple Years.The data for these maps was extracted from the gold standard of Church data, the Annuario Pontificio, published yearly by the Vatican. The collection and data development of the Vatican Statistics Office are unknown. GoodLands is not responsible for errors within this data. We encourage people to document and report errant information to us at data@good-lands.org or directly to the Vatican.Additional information about regular changes in bishops and sees comes from a variety of public diocesan and news announcements.GoodLands’ polygon data layers, version 2.0 for global ecclesiastical boundaries of the Roman Catholic Church:Although care has been taken to ensure the accuracy, completeness and reliability of the information provided, due to this being the first developed dataset of global ecclesiastical boundaries curated from many sources it may have a higher margin of error than established geopolitical administrative boundary maps. Boundaries need to be verified with appropriate Ecclesiastical Leadership. The current information is subject to change without notice. No parties involved with the creation of this data are liable for indirect, special or incidental damage resulting from, arising out of or in connection with the use of the information. We referenced 1960 sources to build our global datasets of ecclesiastical jurisdictions. Often, they were isolated images of dioceses, historical documents and information about parishes that were cross checked. These sources can be viewed here:https://docs.google.com/spreadsheets/d/11ANlH1S_aYJOyz4TtG0HHgz0OLxnOvXLHMt4FVOS85Q/edit#gid=0To learn more or contact us please visit: https://good-lands.org/Esri Gridded Population Data 2016DescriptionThis layer is a global estimate of human population for 2016. Esri created this estimate by modeling a footprint of where people live as a dasymetric settlement likelihood surface, and then assigned 2016 population estimates stored on polygons of the finest level of geography available onto the settlement surface. Where people live means where their homes are, as in where people sleep most of the time, and this is opposed to where they work. Another way to think of this estimate is a night-time estimate, as opposed to a day-time estimate.Knowledge of population distribution helps us understand how humans affect the natural world and how natural events such as storms and earthquakes, and other phenomena affect humans. This layer represents the footprint of where people live, and how many people live there.Dataset SummaryEach cell in this layer has an integer value with the estimated number of people likely to live in the geographic region represented by that cell. Esri additionally produced several additional layers World Population Estimate Confidence 2016: the confidence level (1-5) per cell for the probability of people being located and estimated correctly. World Population Density Estimate 2016: this layer is represented as population density in units of persons per square kilometer.World Settlement Score 2016: the dasymetric likelihood surface used to create this layer by apportioning population from census polygons to the settlement score raster.To use this layer in analysis, there are several properties or geoprocessing environment settings that should be used:Coordinate system: WGS_1984. This service and its underlying data are WGS_1984. We do this because projecting population count data actually will change the populations due to resampling and either collapsing or splitting cells to fit into another coordinate system. Cell Size: 0.0013474728 degrees (approximately 150-meters) at the equator. No Data: -1Bit Depth: 32-bit signedThis layer has query, identify, pixel, and export image functions enabled, and is restricted to a maximum analysis size of 30,000 x 30,000 pixels - an area about the size of Africa.Frye, C. et al., (2018). Using Classified and Unclassified Land Cover Data to Estimate the Footprint of Human Settlement. Data Science Journal. 17, p.20. DOI: http://doi.org/10.5334/dsj-2018-020.What can you do with this layer?This layer is unsuitable for mapping or cartographic use, and thus it does not include a convenient legend. Instead, this layer is useful for analysis, particularly for estimating counts of people living within watersheds, coastal areas, and other areas that do not have standard boundaries. Esri recommends using the Zonal Statistics tool or the Zonal Statistics to Table tool where you provide input zones as either polygons, or raster data, and the tool will summarize the count of population within those zones. https://www.esri.com/arcgis-blog/products/arcgis-living-atlas/data-management/2016-world-population-estimate-services-are-now-available/

Singapore Population: Religion: Christianity: Catholic data was reported at 220.900 Person th in 2015. This records an increase from the previous number of 219.133 Person th for 2010. Singapore Population: Religion: Christianity: Catholic data is updated yearly, averaging 219.133 Person th from Jun 2000 (Median) to 2015, with 3 observations. The data reached an all-time high of 220.900 Person th in 2015 and a record low of 118.980 Person th in 2000. Singapore Population: Religion: Christianity: Catholic data remains active status in CEIC and is reported by Department of Statistics. The data is categorized under Global Database’s Singapore – Table SG.G002: Population by Religion .

In 2021, around 53.59 percent of the population in East Nusa Tenggara, Indonesia were Catholics. Indonesia has the largest Islamic population in the world and therefore the largest Muslim nation. However, Indonesia is not a Muslim nation by constitution. The archipelago has six official religions – Islam, Protestantism, Catholicism, Buddhism, Hinduism, and Confucianism.

Germany: Catholic Christians as percent of the total population: The latest value from 2013 is 31.7 percent, a decline from 31.9 percent in 2012. In comparison, the world average is 43.2 percent, based on data from 84 countries. Historically, the average for Germany from 1960 to 2013 is 38.2 percent. The minimum value, 31.7 percent, was reached in 2013 while the maximum of 45 percent was recorded in 1960.

Singapore Population: Religion: Female: Christianity: Catholic data was reported at 122.800 Person th in 2015. This records an increase from the previous number of 119.050 Person th for 2010. Singapore Population: Religion: Female: Christianity: Catholic data is updated yearly, averaging 119.050 Person th from Jun 2000 (Median) to 2015, with 3 observations. The data reached an all-time high of 122.800 Person th in 2015 and a record low of 66.079 Person th in 2000. Singapore Population: Religion: Female: Christianity: Catholic data remains active status in CEIC and is reported by Department of Statistics. The data is categorized under Global Database’s Singapore – Table SG.G002: Population by Religion .

Poland: Catholic Christians as percent of the total population: The latest value from 2013 is 95.2 percent, an increase from 95.1 percent in 2012. In comparison, the world average is 43.2 percent, based on data from 84 countries. Historically, the average for Poland from 1960 to 2013 is 92 percent. The minimum value, 87.7 percent, was reached in 1960 while the maximum of 95.2 percent was recorded in 2013.