Population density (people per sq. km of land area) in Turkey was reported at 110 sq. Km in 2022, according to the World Bank collection of development indicators, compiled from officially recognized sources. Turkey - Population density (people per sq. km) - actual values, historical data, forecasts and projections were sourced from the World Bank on October of 2025.

Turkey: Population density, people per square km: The latest value from 2021 is 109 people per square km, an increase from 108 people per square km in 2020. In comparison, the world average is 456 people per square km, based on data from 196 countries. Historically, the average for Turkey from 1961 to 2021 is 72 people per square km. The minimum value, 37 people per square km, was reached in 1961 while the maximum of 109 people per square km was recorded in 2021.

Population Density data was reported at 106.553 Person/sq km in 2018. This records an increase from the previous number of 105.003 Person/sq km for 2017. Population Density data is updated yearly, averaging 98.944 Person/sq km from Dec 2007 (Median) to 2018, with 12 observations. The data reached an all-time high of 106.553 Person/sq km in 2018 and a record low of 91.718 Person/sq km in 2007. Population Density data remains active status in CEIC and is reported by Turkish Statistical Institute. The data is categorized under Global Database’s Turkey – Table TR.G004: Population Density.

Historical dataset showing Turkey population density by year from 1961 to 2022.

Turkey TR: Population Density: People per Square Km data was reported at 104.914 Person/sq km in 2017. This records an increase from the previous number of 103.313 Person/sq km for 2016. Turkey TR: Population Density: People per Square Km data is updated yearly, averaging 68.854 Person/sq km from Dec 1961 (Median) to 2017, with 57 observations. The data reached an all-time high of 104.914 Person/sq km in 2017 and a record low of 36.572 Person/sq km in 1961. Turkey TR: Population Density: People per Square Km data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Turkey – Table TR.World Bank: Population and Urbanization Statistics. Population density is midyear population divided by land area in square kilometers. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship--except for refugees not permanently settled in the country of asylum, who are generally considered part of the population of their country of origin. Land area is a country's total area, excluding area under inland water bodies, national claims to continental shelf, and exclusive economic zones. In most cases the definition of inland water bodies includes major rivers and lakes.; ; Food and Agriculture Organization and World Bank population estimates.; Weighted Average;

View yearly updates and historical trends for Turkey Population Density. Source: World Bank. Track economic data with YCharts analytics.

The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Turkey: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).

110.4 (people per sq. km) in 2022. Population density is midyear population divided by land area in square kilometers.

Turkey TR: Population Density: Inhabitants per sq km data was reported at 110.420 Person in 2022. This records an increase from the previous number of 109.330 Person for 2021. Turkey TR: Population Density: Inhabitants per sq km data is updated yearly, averaging 90.040 Person from Dec 1990 (Median) to 2022, with 33 observations. The data reached an all-time high of 110.420 Person in 2022 and a record low of 71.620 Person in 1990. Turkey TR: Population Density: Inhabitants per sq km data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Turkey – Table TR.OECD.GGI: Social: Demography: OECD Member: Annual.

Comprehensive socio-economic dataset for Turkey including population demographics, economic indicators, geographic data, and social statistics. This dataset covers key metrics such as GDP, population density, area, capital city, and regional classifications.

The portal provides Turkey’s main GIS layers for viewing. Authentication is required. Data: Administrative units, population density, transportation, hydrography, environment, geology, land cover, topography, municipal services.

Linkage disequilibrium (LD) across the genome provides information to identify the genes and variations related to quantitative traits in genome-wide association studies (GWAS) and for the implementation of genomic selection (GS). LD can also be used to evaluate genetic diversity and population structure and reveal genomic regions affected by selection. LD structure and Ne were assessed in a set of 83 water buffaloes, comprising Azeri (AZI), Khuzestani (KHU), and Mazandarani (MAZ) breeds from Iran, Kundi (KUN) and Nili-Ravi (NIL) from Pakistan, Anatolian (ANA) buffalo from Turkey, and buffalo from Egypt (EGY). The values of corrected r2 (defined as the correlation between two loci) of adjacent SNPs for three pooled Iranian breeds (IRI), ANA, EGY, and two pooled Pakistani breeds (PAK) populations were 0.24, 0.28, 0.27, and 0.22, respectively. The corrected r2 between SNPs decreased with increasing physical distance from 100 Kb to 1 Mb. The LD values for IRI, ANA, EGY, and PAK populations were 0.16, 0.23, 0.24, and 0.21 for less than 100Kb, respectively, which reduced rapidly to 0.018, 0.042, 0.059, and 0.024, for a distance of 1 Mb. In all the populations, the decay rate was low for distances greater than 2Mb, up to the longest studied distance (15 Mb). The r2 values for adjacent SNPs in unrelated samples indicated that the Affymetrix Axiom 90 K SNP genomic array was suitable for GWAS and GS in these populations. The persistency of LD phase (PLDP) between populations was assessed, and results showed that PLPD values between the populations were more than 0.9 for distances of less than 100 Kb. The Ne in the recent generations has declined to the extent that breeding plans are urgently required to ensure that these buffalo populations are not at risk of being lost. We found that results are affected by sample size, which could be partially corrected for; however, additional data should be obtained to be confident of the results.

Occupied and potential wild turkey habitat in Montana. The species (Merriam's, Eastern, or both) is indicated in occupied habitat polygons.

This dataset is a research outcome of a European Research Council, Starting Grant funded (Grant Number 679097, Industrialisation and Urban Growth from the mid-nineteenth century Ottoman Empire to Contemporary Turkey in a Comparative Perspective, 1850-2000, UrbanOccupationsOETR) project. It contains a mid-nineteenth-century urban Ottoman population micro dataset for the city of Bursa.

In recent decades, a "big microdata revolution" has revolutionized access to transcribed historical census data for social science research. Despite this, the population records of the Ottoman Empire, spanning Southeastern Europe, Western Asia, and Northern Africa, remained absent from the big microdata ecosystem due to their prolonged inaccessibility. In fact, like other modernizing states in the nineteenth century, the Ottoman Empire started to enumerate its population in population registers (nüfus defterleri) in 1830, which recorded only males of all ages for conscription and taxation purposes. These registers were completed and updated in two waves, one in 1830-1838 and the other in the 1839-1865 period. Following this experience, the Empire implemented its first modern census, which included females, in 1881/1882 for more comprehensive statistical and governance reasons to converge with European census-taking practices and account for the increasing participation of females in economic and social spheres.

The pre-census population registers were opened to researchers in 2011. There are around 11.000 registers today. The microdata of the late Ottoman censuses is still not available. Still, unfortunately, the majority of the existing literature using the population registers superficially utilized and failed to tabulate the microdata. Most works using these valuable sources contented with transcribing the microdata from Ottoman to Latin script and presenting their data in raw and unstyled fashion without publishing them in a separate repository.

Our dataset marks the inaugural release of complete population data for an Ottoman urban center, the city of Bursa, derived from the 1839 population registers. It presents originally non-tabulated register data in a tabular format integrated into a relational Microsoft Access database. To ensure that our dataset is more accessible, we are also releasing the dataset in Microsoft Excel format.

The city of Bursa, a major cosmopolitan commercial hub in modern northwestern Turkey, is selected from the larger UrbanOccupationsOETR project database as an exemplary case to represent the volume, value, variety, and veracity of the population data. Furthermore, since urban areas are usually the most densely populated locations that attract the most migration in any country, they are attractive locations for multifold reasons in historical demography. Bursa is not the only urban location in the UrbanOccupationsOETR database. As it focused on urbanization and occupational structural change, it collected the population microdata on major urban centers (chosen as primary locations) and towns (denoted as secondary locations), which pioneered the economic development of post-Ottoman nation-states. What makes the city of Bursa’s data more advantageous than other cities is that it has been cleaned and validated multiple times and used elsewhere for demographic and economic analyses.

The Ottoman population registers of 1830 and 1839 classified the population under the commonly and officially recognized ethnoreligious identities- Muslim, Orthodox Christian, Armenian, Catholic, Jewish, and (Muslim and non-Muslim) Roma. Muslim and non-Muslim populations were counted in separate registers. The registers were organized along spatial and temporal lines. The standard unit of the register was the quarter (mahalle) in urban and village (karye) in rural settings. Within these register units, populated public and non-household spaces such as inns, dervish lodges, monasteries, madrasas, coffeehouses, bakeries, mills, pastures (of nomads), and large private farms (çiftlik) were recorded separately.

The household (menzil/hane) was the unit of entry, which sometimes took different forms depending on the context, such as the room for inns and the tent for nomads. Each household recorded its members on a horizontal line. The variables of male individuals inhabiting them were self-reported biographical information (names, titles/family names, ages, and occupations), physical description (height and facial hair), relationships with other household members (kinship, tenancy, and employment ties), infirmities, and military and poll tax status, including the reasons for exemption, military post, and poll tax category (high-ala, medium-evsat, and small-edna). Households with no inhabitants were differentiated. At the same time, if a resident was known to be absent during registration due to reasons such as military service or migration, he was recorded in his household with a note stating that reason. If he was missing and appeared later, he was added to the household during updates with a note like “not recorded previously” (e.g., hin-i tahrirde taşrada olub) or “newly recorded” (tahrir-mande).

In addition to the permanent residents of a given location, migrant/temporary non-local (yabancı) residents such as laborers, inn-stayers, and unskilled bachelors (bî-kâr) were recorded along with their place of origin and for how long they had been in the migrated place. Non-Muslim migrants were registered with information regarding the last location where they got their poll tax certificate and if they would make their next poll tax payment in the migrated location.

Updates were made mainly to births, deaths, migrations, and military and poll tax status. No other variables, such as age, were renewed except for occupations in a limited number of cases. Updates are easily identifiable since they were written in siyakat, a special Ottoman chancery shorthand script, and occasionally in red ink. Births were specified with newborns’ names added next to the father’s entry. Deaths were updated by crossing out the deceased person’s record. Migrations were added with a description of the migrated place (including the military branch if the person was conscripted). Military and poll tax status was updated by crossing out the old category and adding the new one next to it. Updates were usually expressed in hijri years, sometimes in month-year, and rarely in day-month-year fashion. It is important to note that since updates were made once every few months, these dates may reflect their registration date rather than giving the exact time of the events. Equally crucial is that many events, especially births, were not reported, so their quality is limited.

Modeled after the way information was contained in the population registers, this relational database has two tables, “tblHouse” and “tblIndividual.” Each table categorizes and standardizes the register variables. To make the data easier to use, the dataset also includes a query “Query_InnerJoin” that combines all the variables from each table in a separate sheet.

Given Bursa’s important place in Ottoman history, our dataset serves as a large and crucial resource for comprehending historical societal, economic, and demographic trends within the Empire in the early stages of globalization. The dataset has 8391 household entries (HouseID) and 19,186 individual (IndivID) entries. This data includes the population registered in all of Bursa’s quarters and other location categories in 1839 and the updates until and including 1843 (Figure 2). The ethno-religious breakdown of the total population is 12462 Muslims (65%), 3315 Armenians (17%), 2466 Orthodox Christians (13%), 749 Jews (4%), and 194 Catholics (1%).

To broaden access and use of our data and bring it more in line with findability, accessibility, interoperability, and reusability (FAIR) data guidelines, the variables of “tblHouse” and “tblIndividual” are sorted into general categories and described in detail in the following tables. As the variables indicate, the dataset and population registers, in general, could serve to formulate unprecedented, hitherto impossible research questions related to major demographic dynamics, i.e., household size and composition, ethnoreligious differences, population density, occupational structure, intergenerational mobility and status transfer, mortality, fertility, migration, age-heaping/human capital, conscription, settlement patterns within and across urban locations, onomastics, toponymy, etc.

Table 1: Categories and descriptions of the variables of tblHouse

The demography of, and factors that influence these metrics, are largely unknown for most vultures in the Americas. Survivorship of Turkey Vultures (Cathartes aura) may be influenced by landscape heterogeneity and human disturbance. We quantified the effects of landscape composition (Shannon's diversity index) and configuration (contagion, edge density, and largest patch index), and human disturbance (road density) on the annual and seasonal survival probabilities of the 3 North American breeding populations (western, central, and eastern) of Turkey Vultures that spend the nonbreeding season in the southeastern portion of the Nearctic and the northern Neotropics during a 17-yr period. We used Cox's proportional hazards models with time-varying covariates to estimate spatial and temporal changes in survival rates of adult Turkey Vultures. Road density, but not landscape composition or configuration, influenced survival rates in space and time. Overall annual survival averaged 0.87 (95% CI: 0.74–0.98). Mortality risk was low in western and central populations (hazard ratio < 1) but was 3.7 times greater for vultures in the eastern population. Survival during the breeding (0.97, 95% CI: 0.96–0.98) and outbound migration (1.0, 95% CI: 1–1) seasons was significantly higher than the other seasons. Average survival tended to be higher for nonbreeding (0.81, 95% CI: 0.71–0.88) compared to return migration (0.69, 95% CI: 0.56–0.81) seasons. Risk of mortality for all vulture populations increased with road density, and this was greater during the nonbreeding and return migration seasons. The spatial variation in road density across the Americas may generate a network of ecological traps for Turkey Vultures induced to stop in areas of greater road-kill abundance. Road-killed animals acting as an attractant for vultures can increase the occurrence of vulture-vehicle collisions and potentially aggravate human-wildlife conflicts. Further analyses are needed to address survivorship and mortality factors for young birds. Our results may help the implementation of specific mitigation efforts to reduce human–vulture conflicts and vulture mortality. For instance, concentrating efforts to remove road-killed animals in areas where road density is highest can likely reduce vulture–vehicle collisions and associated mortalities of these birds.

This boundary dataset complements 13 other datasets as part of a study that compared ancient settlement patterns with modern environmental conditions in the Jazira region of Syria. This study examined settlement distribution and density patterns over the past five millennia using archaeological survey reports and French 1930s 1:200,000 scale maps to locate and map archaeological sites. An archaeological site dataset was created and compared to and modelled with soil, geology, terrain (contour), surface and subsurface hydrology and normal and dry year precipitation pattern datasets; there are also three spreadsheet datasets providing 1963 precipitation and temperature readings collected at three locations in the region. The environmental datasets were created to account for ancient and modern population subsistence activities, which comprise barley and wheat farming and livestock grazing. These environmental datasets were subsequently modelled with the archaeological site dataset, as well as, land use and population density datasets for the Jazira region. Ancient trade routes were also mapped and factored into the model, and a comparison was made to ascertain if there was a correlation between ancient and modern settlement patterns and environmental conditions; the latter influencing subsistence activities. This boundary dataset was generated to define the extent of the study area, which comprises the border between Syria and Turkey, Syria and Iraq, the River Tigris and the River Euphrates. All related data collected was confined within this boundary dataset with the exception of the archaeological dataset. Archaeological sites were identified and mapped along both banks of the River Euphrates. Also, the town of Dayr az-Zawr, where the 1963 precipitation and temperature monthly values were collected for one of the datasets, falls outside the Jazira Region. Derived from 1:200,000 French Levant Map Series (Further Information element in this metadata record provides list of sheets).The boundary line dataset was captured from 11 map sheets, which were based on the French Levant surveys conducted in Syria during the 1930s and mapped at a scale of 1:200,000. The size of each map measures 69 x 59 cm. The boundary line on each sheet was traced to mylar. Subsequently, each mylar sheet was photocopied and reduced in size to an 11 x 17 inch sheet. These sheets were merged to form the contiguous area comprising the full extent of the boundary for the study area. This was then traced again to another mylar sheet and subsequently scanned and cleaned for further processing and use in a GIS as a polygon coverage. Thesis M 2001 MATH, Ohio University Mathys, Antone J 'A GIS comparative analysis of bronze age settlement patterns and the contemporary physical landscape in the Jazira Region of Syria'., French Levant Map Series (1:200,000) for Syrie (Syria). Projected to Lambert grid. These are colour maps measuring to 69 x 59 cm in size. The dataset was created from the following sheet numbers and titles: 1) NI-37 XVII, Abou Kemal 2) NI-37 XVIII, Ana 3) NI-37 XXI, Ressafe 4) NI-37 XXII, Raqqa 5) NI-37 XXIII, Deir ez Zoir 6) NI-37 XXIV, Bouara 7) NI-37-III, Djerablous 8) NJ-37 IV, Toual Aaba 9) NJ-37 V, Hassetche 10) NJ-37 VI, Qamishliye-Sinjar 11) (No sheet number), Qaratchok-Darh Dressepar la Service Geographique des F.F.L. en 1945 Reimprime par l'Institut Geographique National en 1950 (Originally produced by this Geographic Service of the F.F.L. (Forces Francaises Libres) in 1945 and reprinted by the National Geographic Institute in 1950). Paris: France. Institut Geographique National, 1945-1950. Original map series might be traced to Beirut: Bureau Topographique des Troupes francaises du Levant, 1933-1938. GIS vector data. This dataset was first accessioned in the EDINA ShareGeo Open repository on 2010-06-09 and migrated to Edinburgh DataShare on 2017-02-21.

TR：人口密度：每平方公里人口在12-01-2017达104.914Person/sq km，相较于12-01-2016的103.313Person/sq km有所增长。TR：人口密度：每平方公里人口数据按年更新，12-01-1961至12-01-2017期间平均值为68.854Person/sq km，共57份观测结果。该数据的历史最高值出现于12-01-2017，达104.914Person/sq km，而历史最低值则出现于12-01-1961，为36.572Person/sq km。CEIC提供的TR：人口密度：每平方公里人口数据处于定期更新的状态，数据来源于World Bank，数据归类于Global Database的土耳其 – 表 TR.世界银行：人口和城市化进程统计。

The Turkish residential real estate market, valued at $99.05 million in 2025, exhibits robust growth potential, projected to expand at a Compound Annual Growth Rate (CAGR) of 11.16% from 2025 to 2033. This growth is driven by several factors. Increasing urbanization and a burgeoning young population fuel demand for housing, particularly in key cities like Istanbul, Antalya, and Bodrum, known for their tourism and economic activity. Government initiatives aimed at stimulating the construction sector and infrastructure development also contribute positively. Furthermore, Turkey's strategic geographic location and relatively affordable property prices compared to Western European nations attract both domestic and international investors. However, economic volatility and fluctuating exchange rates represent significant challenges. Inflationary pressures and potential interest rate hikes can impact affordability and deter buyers. Furthermore, the market's dependence on tourism in some regions makes it vulnerable to external shocks like global pandemics or geopolitical instability. The segmentation of the market, encompassing apartments/condominiums, villas, and landed houses, caters to diverse buyer preferences and contributes to the overall market dynamism. Leading developers such as Sinpas Group, Agaoglu Group, and others play a vital role in shaping the market's trajectory. The segment of apartments and condominiums dominates the market, driven by affordability and high population density in urban centers. Villas and landed houses cater to a more affluent segment, with significant demand in coastal areas and regions with scenic landscapes. While the Turkish domestic market forms the core of demand, international buyers, especially from the Middle East and Europe, contribute significantly, especially to the high-end segments. The analysis of past performance (2019-2024) reveals significant variations linked to economic cycles and international events. Projecting forward, a cautious optimism is warranted, with growth contingent on macro-economic stability and sustained investor confidence. Detailed regional breakdowns within Turkey and global comparisons will provide further granular insights into market dynamics. This insightful report provides a deep dive into the Turkish residential real estate market, offering a comprehensive analysis of its current state, future trends, and key players. With a focus on the period from 2019 to 2033, including a base year of 2025 and a forecast period spanning 2025-2033, this report is an essential resource for investors, developers, and industry professionals seeking to understand and capitalize on opportunities within this dynamic sector. The report leverages data from the historical period (2019-2024) to provide accurate and reliable projections. Keywords: Turkish real estate market, Istanbul property market, Antalya real estate, Bodrum property, Turkish residential market analysis, real estate investment Turkey, Turkish construction industry, Turkish housing market forecast. Key drivers for this market are: Increasing Investment in Infrastructure Projects, The rising popularity of sustainable architecture. Potential restraints include: Volatility in Raw material prices. Notable trends are: Increasing FDI Flow in the Residential Real Estate Market in Turkey.

Coronavirus disease 2019 (COVID-19), one of the most serious public health crises in over a century, has led to an unprecedented surge of publications across all areas of knowledge. This study assessed the early research productivity on COVID-19 in terms of vaccination, diagnosis, treatment, symptoms, risk factors, nutrition, and economy. The Scopus database was searched between January 1, 2020 and December 31, 2020 to initially examine the research productivity on COVID-19, as measured by total publications by the 20 highest-ranked countries according to gross domestic product. The literature search was then refined, and research productivity was assessed across seven major research domains related to COVID-19: vaccination, diagnosis, treatment, symptoms, risk factors, nutrition, and economy. The initial literature search yielded 53,348 publications. Among these, 27,801 publications involved authorship from a single country and 22,119 publications involved authorship from multiple countries. Overall, the United States was the most productive country (n = 13,491), with one and a half times or more publications than any other country, on COVID-19 and the selected domains related to it. However, following adjustment for population size, gross domestic product, and expenditure for research and development, countries of emerging economies such as India along countries of lower population density such as Switzerland, Indonesia, and Turkey exhibited higher research productivity. The surge of COVID-19 publications in such a short period of time underlines the capacity of the scientific community to respond against a global health emergency; however where future research priorities and resource distribution should be placed on the respective thematic fields at an international level, warrants further investigation.

Biscayne National Park sediment porewater sampling site names and GPS locations.