Auckland

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These Community Mobility Reports aim to provide insights into what has changed in response to policies aimed at combating COVID-19. The reports chart movement trends over time by geography, across different categories of places such as retail and recreation, groceries and pharmacies, parks, transit stations, workplaces, and residential.

Data cited at: Numbeo Methodology: The Index has been calculated twice per year by considering the latest 36 months. A). Beginning of the Year and B). Mid Year Crime Index is an estimation of the overall level of crime in a given city or a country. We consider crime levels lower than 20 as very low, crime levels between 20 and 40 as being low, crime levels between 40 and 60 as being moderate, crime levels between 60 and 80 as being high and finally crime levels higher than 80 as being very high. Safety index is, on the other way, quite the opposite of crime index. If the city has a high safety index, it is considered very safe.

Nestpick studied thousands of cities to hand-pick 100 places considered to be millennial dream destinations. It ranked cities by relevant factors to compile the ultimate Millennial City Ranking. These factors include Employment, Startup, Tourism, Housing, Transport, Health, Food, Internet Speed, Apple Store, Access to Contraception, Gender Equality, Immigration Tolerance, LGBT Friendly, Nightscene, Beer, and Festival

We define our day as midnight-to-midnight, Pacific time. Cities represent usage in greater metropolitan areas and are stably defined during this period. In many countries/regions and cities, relative volume has increased since January 13th, consistent with normal, seasonal usage of Apple Maps. Day of week effects are important to normalize as you use this data. Data that is sent from users’ devices to the Maps service is associated with random, rotating identifiers so Apple doesn’t have a profile of your movements and searches. Apple Maps has no demographic information about our users, so we can’t make any statements about the representativeness of our usage against the overall population. This information will be available for a limited time during the COVID‑19 pandemic.

The Regional database contains annual data from 1995 to the most recent available year (generally 2022 for demographic and labor market data, 2021 for regional accounts, innovation and social statistics). 

The Regional database contains annual data from 1995 to the most recent available year (generally 2018 for demographic and labor market data, 2017 for regional accounts, innovation and social statistics). The data collection is undertaken by the Center for Entrepreneurship, SMEs, Regions and Cities (CFE). Statistics are collected through an annual questionnaire sent to the delegates of the Working Party on Territorial Indicators (WPTI), and via downloads from the web-sites of National Statistical Offices and Eurostat

The Regional Database contains annual data from 1995 to the most recent available year. The data collection is undertaken by the Directorate of Public Governance and Territorial Development, within the Regional Development Policy division (GOV/RDP). Statistics are collected through an annual questionnaire sent to the delegates of the Working Party on Territorial Indicators (WPTI), and through access to the web-sites of National Statistical Offices and Eurostat. The WPTI is responsible for developing regional (subnational) and urban statistics and providing analysis to support policy evaluations. The Regional Database includes statistics on the regional distribution of resources, regional disparities, and how regions contribute to national growth and the well-being of society. Under this framework, the Regional Database is one of the pillars for providing indicators to the publication OECD Regions at a Glance (link).

The Regional Database contains annual data from 1995 to the most recent available year (generally 2016 for demographic, 2015 for labor market data and 2014 for regional accounts, innovation and social statistics).

The Regional Database contains annual data from 1995 to the most recent available year (generally 2014 for demographic and labour market data, 2013 for regional accounts, innovation and social statistics).   In any analytical study conducted at sub-national levels, the choice of the territorial unit is of prime importance. The territorial grids (TL2 and TL3) used in this database are officially established and relatively stable in all member countries, and are used by many as a framework for implementing regional policies. This classification - which, for European countries, is largely consistent with the Eurostat classification - facilitates greater comparability of regions at the same territorial level. The differences with the Eurostat NUTS classification concern Belgium, Greece and the Netherlands where the NUTS 2 level correspond to the OECD TL3 and Germany where the NUTS1 corresponds to the OECD TL2 and the OECD TL3 corresponds to 97 spatial planning regions (Groups of Kreise). For the United Kingdom the Eurostat NUTS1 corresponds to the OECD TL2. Due to limited data availability, labour market indicators in Canada are presented for a different grid (groups of TL3 regions). Since these breakdowns are not part of the OECD official territorial grids, for the sake of simplicity they are labelled as Non Official Grids (NOG).

The Regional well-being dataset presents eleven dimensions central for well-being at local level and for 395 OECD regions, covering material conditions (income, jobs and housing), quality of life (education, health, environment, safety and access to services) and subjective well-being (social network support and life satisfaction). The set of indicators selected to measure these dimensions is a combination of people's individual attributes and their local conditions, and in most cases, are available over two different years (2000 and 2014). Regions can be easily visualised and compared to other regions through the interactive website [www.oecdregionalwellbeing.org]. The dataset, the website and the publications "Regions at a Glance" and "How’s life in your region?" are outputs designed from the framework for regional and local well-being. The Regional income distribution dataset presents comparable data on sub-national differences in income inequality and poverty for OECD countries. The data by region provide information on income distribution within regions (Gini coefficients and income quintiles), and relative income poverty (with poverty thresholds set in respect of the national population) for 2013. These new data complement international assessments of differences across regions in living conditions by documenting how household income is distributed within regions and how many people are poor relatively to the typical citizen of their country. For analytical purposes, the OECD classifies regions as the first administrative tier of sub-national government, so called Territorial Level 2 or TL2 in the OECD classification. This classification is used by National Statistical Offices to collect information and it represents in many countries the framework for implementing regional policies. Well-being indicators are shown for the 395 TL2 OECD regions, equivalent of the NUTS2 for European countries, with the exception for Estonian where well-being data are presented at a smaller (TL3) level and for the Regional Income dataset, where Greece, Hungary and Poland data are presented at a more aggregated (NUTS1) level.

The TomTom Traffic Index is published to provide drivers, industry and policy makers with unbiased information about congestion levels in urban areas. Now in its 6th year, we’re offering even more insight into why our urban centers are congested, putting the issue into context, and offering ideas about how the problem can be alleviated. This year, TomTom is also celebrating those cities that deserve special recognition for their efforts to beat traffic congestion, with the TomTom Traffic Index awards.

Data cited at: The Water Footprint Network https://waterfootprint.org/en/ Topic: Product water footprint statistics Publication: https://waterfootprint.org/en/resources/waterstat/product-water-footprint-statistics/ Reference: Mekonnen, M.M. & Hoekstra, A.Y. (2011) The green, blue and grey water footprint of crops and derived crop products, Hydrology and Earth System Sciences, 15(5): 1577-1600. License: https://creativecommons.org/licenses/by-sa/3.0/    

Data cited at: The Water Footprint Network https://waterfootprint.org/en/ Topic: Product water footprint statistics Publication: https://waterfootprint.org/en/resources/waterstat/product-water-footprint-statistics/ Reference: Mekonnen, M.M. & Hoekstra, A.Y. (2011) The green, blue and grey water footprint of crops and derived crop products, Hydrology and Earth System Sciences, 15(5): 1577-1600. License: https://creativecommons.org/licenses/by-sa/3.0/