Switzerland Population in Largest City: as % of Urban Population data was reported at 20.309 % in 2017. This records a decrease from the previous number of 20.328 % for 2016. Switzerland Population in Largest City: as % of Urban Population data is updated yearly, averaging 20.220 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 20.747 % in 2007 and a record low of 19.215 % in 1963. Switzerland Population in Largest City: as % of Urban Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Switzerland – Table CH.World Bank: Population and Urbanization Statistics. Population in largest city is the percentage of a country's urban population living in that country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; Weighted Average;

Actual value and historical data chart for Switzerland Population In Largest City

Switzerland Population in Largest City data was reported at 1,356,037.000 Person in 2017. This records an increase from the previous number of 1,341,453.000 Person for 2016. Switzerland Population in Largest City data is updated yearly, averaging 951,846.500 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 1,356,037.000 Person in 2017 and a record low of 535,471.000 Person in 1960. Switzerland Population in Largest City data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Switzerland – Table CH.World Bank.WDI: Population and Urbanization Statistics. Population in largest city is the urban population living in the country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; ;

About this dataset

Context

This list ranks the 1 cities in the Major County, OK by Swiss population, as estimated by the United States Census Bureau. It also highlights population changes in each city over the past five years.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:

• 2019-2023 American Community Survey 5-Year Estimates
• 2014-2018 American Community Survey 5-Year Estimates
• 2009-2013 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Swiss Population: This column displays the rank of city in the Major County, OK by their Swiss population, using the most recent ACS data available.
• City: The City for which the rank is shown in the previous column.
• Swiss Population: The Swiss population of the city is shown in this column.
• % of Total City Population: This shows what percentage of the total city population identifies as Swiss. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Major County Swiss Population: This tells us how much of the entire Major County, OK Swiss population lives in that city. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: This column displays the rank trend across the last 5 years.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Settlement development of the largest Swiss cities. Map types: Symbols, Choropleths. Spatial extent: Switzerland. Time: before 1850 up to present

About this dataset

Context

This list ranks the 2 cities in the Switzerland County, IN by Some Other Race (SOR) population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:

• 2019-2023 American Community Survey 5-Year Estimates
• 2018-2022 American Community Survey 5-Year Estimates
• 2017-2021 American Community Survey 5-Year Estimates
• 2016-2020 American Community Survey 5-Year Estimates
• 2015-2019 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Other Race Population: This column displays the rank of cities in the Switzerland County, IN by their Some Other Race (SOR) population, using the most recent ACS data available.
• cities: The cities for which the rank is shown in the previous column.
• Other Race Population: The Other Race population of the cities is shown in this column.
• % of Total cities Population: This shows what percentage of the total cities population identifies as Other Race. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Switzerland County Other Race Population: This tells us how much of the entire Switzerland County, IN Other Race population lives in that cities. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: TThis column displays the rank trend across the last 5 years.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

This horizontal bar chart displays population (people) by capital city using the aggregation sum in Switzerland. The data is filtered where the date is 2021. The data is about countries per year.

About this dataset

Context

This list ranks the 2 cities in the Switzerland County, IN by Native Hawaiian and Other Pacific Islander (NHPI) population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:

• 2019-2023 American Community Survey 5-Year Estimates
• 2018-2022 American Community Survey 5-Year Estimates
• 2017-2021 American Community Survey 5-Year Estimates
• 2016-2020 American Community Survey 5-Year Estimates
• 2015-2019 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Pacific Islander Population: This column displays the rank of cities in the Switzerland County, IN by their Native Hawaiian and Other Pacific Islander (NHPI) population, using the most recent ACS data available.
• cities: The cities for which the rank is shown in the previous column.
• Pacific Islander Population: The Pacific Islander population of the cities is shown in this column.
• % of Total cities Population: This shows what percentage of the total cities population identifies as Pacific Islander. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Switzerland County Pacific Islander Population: This tells us how much of the entire Switzerland County, IN Pacific Islander population lives in that cities. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: TThis column displays the rank trend across the last 5 years.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

View yearly updates and historical trends for Switzerland Population in the Largest City. Source: World Bank. Track economic data with YCharts analytics.

The data collected on members of the local elites of the three largest city-regions (Basel, Geneva and Zurich) are integrated in the more general OBELIS database on Swiss Elites. Currently, the OBELIS database includes elites from four sectors at the national level: Economic, Political, Administrative and Academic (+ national sociability associations) and covers nine dates: 1890, 1910, 1937, 1957, 1980, 2000, 2010, 2015 and 2020. The elite status of individuals is defined by the position/function held in these four spheres at the date mentioned. A description of all the different samples of the Swiss elites can be consulted on the website. The data allows researchers to understand the elites through a relational analysis (network analysis) to highlight the interrelations between these elites. The data is also suitable to conduct prosopographical analysis. As for national elites, the identification of local elites of the three largest Swiss city-regions also follows a positional approach by selecting all individuals occupying leading positions in the major local economic, political, cultural and academic institutions for the 7 benchmark years: 1890, 1910, 1937, 1957, 1980, 2000 and 2020. For the economic sphere we collected information on all the committee members of the regional chambers of commerce as well as directors of the most important companies of the three cities’ leading economic sectors. This includes the major banks and insurance companies for the financial sector; for Basel, all the major textile (until 1937) and chemical-pharmaceutical companies; for Geneva, the major watch-making companies, as well as a few other industrial companies; and for Zurich, all the major companies from the machine industry. The total number of companies varies from 49 in 1890 to 35 in 2020. The smaller sample for the recent period is due to the strong concentration process in all economic sectors, involving mergers and acquisitions as well as bankruptcies. For these companies, all CEOs/general directors and directors’ board members were taken into account. For the political sphere, we included all members of the cantonal (regional) and local (city) parliaments and governments for Geneva and Zurich, whereas in Basel, where the city’s territory fully coincides with the canton, only the members of the cantonal parliament and government were considered. For the academic sphere we include all full and extraordinary (associate) professors of the three cities’ universities until 1957, and, for the more recent dates, a selection of professors according to the occupation of institutional positions or according to their scientific reputation. Finally, the committee members of the three cities’ fine art societies are included as urban elites from the cultural sphere.

About this dataset

Context

This list ranks the 2 cities in the Switzerland County, IN by Black or African American population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:

• 2019-2023 American Community Survey 5-Year Estimates
• 2018-2022 American Community Survey 5-Year Estimates
• 2017-2021 American Community Survey 5-Year Estimates
• 2016-2020 American Community Survey 5-Year Estimates
• 2015-2019 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Black Population: This column displays the rank of cities in the Switzerland County, IN by their Black or African American population, using the most recent ACS data available.
• cities: The cities for which the rank is shown in the previous column.
• Black Population: The Black population of the cities is shown in this column.
• % of Total cities Population: This shows what percentage of the total cities population identifies as Black. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Switzerland County Black Population: This tells us how much of the entire Switzerland County, IN Black population lives in that cities. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: TThis column displays the rank trend across the last 5 years.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

About this dataset

Context

This list ranks the 2 cities in the Big Stone County, MN by Swiss population, as estimated by the United States Census Bureau. It also highlights population changes in each city over the past five years.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:

• 2019-2023 American Community Survey 5-Year Estimates
• 2014-2018 American Community Survey 5-Year Estimates
• 2009-2013 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Swiss Population: This column displays the rank of city in the Big Stone County, MN by their Swiss population, using the most recent ACS data available.
• City: The City for which the rank is shown in the previous column.
• Swiss Population: The Swiss population of the city is shown in this column.
• % of Total City Population: This shows what percentage of the total city population identifies as Swiss. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Big Stone County Swiss Population: This tells us how much of the entire Big Stone County, MN Swiss population lives in that city. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: This column displays the rank trend across the last 5 years.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Techsalerator’s Location Sentiment Data for Switzerland

Techsalerator’s Location Sentiment Data for Switzerland provides valuable insights into public sentiment, environmental mood, and acoustic trends across various Swiss locations. This dataset is essential for businesses, researchers, policymakers, and technology developers looking to understand the evolving sentiments and soundscapes in the Swiss context.

For access to the full dataset, contact us at info@techsalerator.com or visit Techsalerator Contact Us.

Techsalerator’s Location Sentiment Data for Switzerland

Techsalerator’s Location Sentiment Data for Switzerland delivers a comprehensive analysis of emotional sentiment and environmental sounds across urban, rural, and scenic locations. This data is crucial for urban development, environmental monitoring, social studies, and AI-based sentiment analysis applications.

Top 5 Key Data Fields

• Location of Data Capture – Identifies the geographic region where the sentiment and sound data was collected, aiding in regional sentiment analysis.
• Sentiment Score – Provides an aggregated sentiment score (positive, negative, or neutral) for each recorded location based on local interactions and public opinions.
• Audio Frequency Spectrum – Analyzes sound frequencies present in various environments, supporting studies on urban noise, nature sounds, and public health.
• Decibel Levels (dB) – Measures sound intensity in different locations, helping in noise pollution studies and assessing the impact of sound on the Swiss population.
• Time of Capture – Captures the exact time and date of data collection, allowing for analysis of sentiment and soundscape variations between day and night.

Top 5 Location Sentiment Trends in Switzerland

• Urban Sentiment Shifts – Increased urbanization and tourism in cities like Zurich and Geneva are contributing to shifts in public sentiment, impacting local business and social dynamics.
• Tourism and Regional Sentiment – The tourist influx in locations such as Interlaken and Lucerne has influenced sentiment patterns, especially in terms of local hospitality and cultural identity.
• Mountain Soundscapes – In alpine areas, there is a growing interest in environmental acoustics, including the study of wildlife and natural sound environments in the Swiss Alps.
• Swiss Political Sentiment – Political movements and national elections have an observable impact on sentiment in major cities, helping analysts understand voter behavior and public opinion trends.
• Climate Change Awareness – Sentiment around climate change is rising, with increasing attention on environmental concerns in areas like Geneva and the Swiss Jura.

Top 5 Applications of Location Sentiment Data in Switzerland

• Urban Planning and Smart Cities – Understanding sentiment and noise levels helps urban planners create more harmonious and people-centered cities.
• Tourism and Hospitality Industry – Analyzing regional sentiment helps businesses tailor services to meet customer expectations and improve local experiences.
• Environmental and Climate Research – Sentiment and acoustic data aid in understanding public awareness and concerns regarding climate change and conservation efforts.
• Public Policy and Government – Local sentiment data provides valuable input for policymakers in creating programs that align with the concerns of Swiss citizens.
• AI and Social Media Analysis – Enhancing sentiment analysis tools with localized data for better understanding of public moods and behaviors on digital platforms.

Accessing Techsalerator’s Location Sentiment Data

To obtain Techsalerator’s Location Sentiment Data for Switzerland, contact info@techsalerator.com with your specific requirements. Techsalerator offers customized datasets based on requested fields, with delivery available within 24 hours. Ongoing access options can also be discussed.

Included Data Fields

• Location of Data Capture
• Sentiment Score (Positive, Negative, Neutral)
• Audio Frequency Spectrum
• Decibel Levels (dB)
• Time of Capture
• Sentiment Analysis (Mood Patterns)
• Noise Pollution Analysis
• Cultural Sentiment
• Tourism Impact
• Climate Sentiment

Techsalerator’s Location Sentiment Data for Switzerland offers a comprehensive view of public sentiment and sound data, providing critical insights for businesses, environmental researchers, urban developers, and policymakers across the country.

This horizontal bar chart displays health expenditure (% of GDP) by capital city using the aggregation average, weighted by gdp in Switzerland. The data is filtered where the date is 2021. The data is about countries per year.

This horizontal bar chart displays renewable energy consumption (% of total final energy consumption) by capital city using the aggregation average in Switzerland. The data is filtered where the date is 2021. The data is about countries per year.

In 2023, the average rent for apartments and houses in Switzerland peaked at ** Swiss francs per square meter. That was an increase from ***** Swiss francs per square meter in 2022 and the largest rise since 2017. In 2023, Zurich and Geneva were the Swiss cities with the highest rents.

About this dataset

Context

This list ranks the 1 cities in the Big Horn County, MT by Swiss population, as estimated by the United States Census Bureau. It also highlights population changes in each city over the past five years.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:

• 2019-2023 American Community Survey 5-Year Estimates
• 2014-2018 American Community Survey 5-Year Estimates
• 2009-2013 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Swiss Population: This column displays the rank of city in the Big Horn County, MT by their Swiss population, using the most recent ACS data available.
• City: The City for which the rank is shown in the previous column.
• Swiss Population: The Swiss population of the city is shown in this column.
• % of Total City Population: This shows what percentage of the total city population identifies as Swiss. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Big Horn County Swiss Population: This tells us how much of the entire Big Horn County, MT Swiss population lives in that city. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: This column displays the rank trend across the last 5 years.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

In this paper we explore how policy discourses on urban sustainability impact the governing of urban food gardening in favoring community gardens. Our main hypothesis is that community gardens better accommodate the tensions created by the discourses of the compact and green city compared to other types of food gardening, especially allotment gardens. In the context of the Swiss cities of Lausanne and Zurich, analysis of policy documents confirms this hypothesis by identifying four frames that orient policies toward favoring community gardening: (i) Adapting green space planning to densification favors community gardening with their modest, flexible and multifunctional design, (ii) Revaluating the role of urban food gardening in urban sustainability represents community gardening as a new multifunctional benchmark, (iii) Reorganizing urban food gardening fosters diversity in gardening opportunities which in turn supports a variety of forms of community gardening, (iv) Justifying urban food gardening through public values and needs supports community gardening with their cost-efficient green space management, lower land management and more active citizen participation. In this vein, urban policymakers continually turn to community gardens as a strategic urban planning tool that gives urban green space greater legitimacy in the wake of the densifying city. Overall, urban food gardens continue to be negotiated between space-related marginalization and socio-political significance serving different needs to urban citizens. This results in the need of a more sophisticated planning approach considering different types of urban gardens related to their location in the built city, associated functions, and user groups.

Switzerland Self Storage Market size was valued to be USD 10 Billion in the year 2024 and it is expected to reach USD 13.48 Billion in 2032, at a CAGR of 3.8% over the forecast period of 2026 to 2032.

Key Market Drivers: Urban Demographic Transformation: Switzerland is experiencing a profound urban demographic shift, which has a direct impact on the self-storage market. Urban populations are rapidly expanding, with projections indicating that 87% of Swiss residents live in cities by 2030. This urban concentration results in significant living space constraints, especially in major metropolitan areas such as Zurich, Geneva, and Basel. E-commerce and Business Storage Requirements: Self-storage facilities offer businesses cost-effective alternatives to traditional warehousing. The Swiss e-commerce market has grown dramatically, with a projected 22% increase in 2022. Small and medium-sized businesses now face new storage requirements due to the digital marketplace transformation.

We established our study sites in the cities of Basel, Lugano and Zurich. We characterised urban tree cover of each city using a rectangular grid with squares of 100x100 m. Within each square, we measured the area covered by urban trees using the European Union's Copernicus Land Monitoring Service information, Urban Atlas Street Tree Layer 2018 https://doi.org/10.2909/205691b3-7ae9-41dd-abf1-1fbf60d72c8c. Then we assigned each square to three categories of urban tree cover that roughly represented the main types of urban uses: 1) low cover, industrial/commercial areas, 0-20% tree cover; 2) intermediate cover, residential areas, 20-40% tree cover; 3) high cover, urban parks and cemeteries, 40-60% tree cover. -br/--br/- We measured bird predation rate on the non-native insect larvae of the horse chestnut leaf miner (HCLM) Cameraria ohridella, an invasive moth that lays eggs and completes its larval and pupal development stages within the leaves of the horse chestnut Aesculus hippocastanus. The larvae feed on leaf fluids and tissue while creating mines within the leaf, which ultimately results in early leaf browning and loss of photosynthetic activity. We collected roughly ten twigs from each tree, including five twigs from the inner and five from the outer crown. Each twig carried 2-4 leaves, for a total of 3408 leaflets. Leaves were stored for ~10 weeks in a refrigerated room at 4 degrees C. We checked all HCLM mines using a stereo microscope and distinguished among open and close mines. Open mines were further divided based on the opening hole, whether it was a small round exit hole of the larva or the parasitoid, or an irregularly shaped, large bird predation hole.