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Cities in Europe and Central Asia Database 1992 - 2012

Albania, Bulgaria, Germany...and 13 more, 2015 - 2016
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Reference ID
ECA_2015_CECA_v01_M
Producer(s)
Paula Restrepo Cadavid, Grace Cineas, Sofia Zhukova
Metadata
Documentation in PDF DDI/XML JSON
Created on
Nov 30, 2017
Last modified
Jun 13, 2022
Page views
36285
Downloads
160123
  • Study Description
  • Data Description
  • Documentation
  • Get Microdata
  • Identification
  • Version
  • Scope
  • Coverage
  • Producers and sponsors
  • Data collection
  • Depositor information
  • Data Access
  • Disclaimer and copyrights
  • Contacts
  • Metadata production
  • Identification

    Survey ID number

    ECA_2015_CECA_v01_M

    Title

    Cities in Europe and Central Asia Database 1992 - 2012

    Country/Economy
    Name Country code
    Albania ALB
    Bulgaria BGR
    Germany DEU
    United Kingdom GBR
    Georgia GEO
    Kazakhstan KAZ
    Kyrgyz Republic KGZ
    Moldova MDA
    Poland POL
    Romania ROU
    Russian Federation RUS
    Serbia SRB
    Tajikistan TJK
    Turkiye TUR
    Ukraine UKR
    Uzbekistan UZB
    Abstract
    This research, designed by the World Bank, and supported by the Department for International Development (DFID), aims to highlight the unprecedented transformation of the urban systems in the ECA region in the last decades, and to look at this shifts from the demographic, economic, and spatial prospectives.

    Cities in ECA database comprises data from 5,549 cities in 15 countries of the Eastern Europe and Central Asia region, as defined by the World Bank Group, and from the United Kingdom and Germany. Database information for each city is in three dimensions: demographic, spatial, and economic.

    The starting point to construct the Cities in ECA database was to obtain from each of the countries the list of official cities and these cities' population data. Population data collected for cities falls on or around three years: 1989, 1999, and 2010 (or the latest year available). The official list of "cities" was geo-referenced and overlaid with globally-available spatial data to produce city-level indicators capturing spatial characteristics (e.g., urban footprint) and proxies for economic activity. City-level spatial characteristics, including urban footprints (or extents) for the years 1996, 2000, and 2010 and their temporal evolution, were obtained from the Global Nighttime Lights (NTL) dataset. City-level proxies for economic activity were also estimated based on the NTL dataset. Nighttime Lights (NLS) data is produced by the Defense Meteorological Satellite Program (DMSP) - Optical Line Scanner (OLS) database and maintained by the National Oceanic and Atmospheric Administration (NOAA).
    Kind of Data

    Process-produced data [pro]

    Unit of Analysis
    • a city

    Version

    Version Description

    v01, edited dataset for public distribution

    The Cities in ECA database also includes several variables which result from the intersection of other globally-available spatial data and the location of cities, or which further qualify cities' characteristics - based on their institutional or economic structure-using official data. Below is a description of some of these variables:

    • Location fundamentals refer to a series of spatially-concentrated characteristics, which can support the concentration of population and economic activities. These could include natural advantages supporting the development of agricultural activities or spatial characteristics supporting the development of commercial activities-such as having access to navigable waterways. The database includes seven location fundamentals variables: land vegetation, average January temperature, total annual precipitation, percentage forest cover, distance to nearest coast, distance to nearest international border, and distance to closest border.
    • Market potential intends to measure the proximity of a city to nearby (national) markets as a city's market potential is determined by the network of cities to which it has access.
    • Monotowns are cities whose economies are dominated by one or a few tightly inter-connected industries. The Cities in ECA database includes a dummy variable identifying 224 monotowns in Russia, the only country for which this information was readily available.
    • Multi-city agglomeration or agglomerations correspond to cities whose urban footprint extends beyond a single administrative entity. Agglomerations are identified by intersecting the cities' data with the urban footprints produced by the NTL dataset. There are a total of 352 agglomerations composed of 2,358 cities in the 17 countries studied.
    Version Date

    2017

    Scope

    Notes

    The scope of the study includes:

    • City population, area
    • Light convergence
    • Urbanization
    • Economic density
    • Monotowns (cities which economic performance and employment is highly dependent on one or few industries)
    • Population growth
    • Migration

    Coverage

    Geographic Coverage

    Albania, Belarus, Bulgaria, Georgia, Germany, Kazakhstan, Kyrgyz Republic, Moldova, Poland, Romania, Russian Federation, Serbia, Tajikistan, Turkey, Ukraine, United Kingdom, Uzbekistan

    Producers and sponsors

    Primary investigators
    Name Affiliation
    Paula Restrepo Cadavid World Bank
    Grace Cineas World Bank
    Sofia Zhukova World Bank
    Producers
    Name Affiliation
    Benjamin Stewart World Bank
    Katie McWilliams World Bank
    Luis E. Quintero World Bank
    Funding Agency/Sponsor
    Name
    Department for International Development, United Kingdom

    Data collection

    Dates of Data Collection
    Start End
    2015-04-01 2016-09-01
    Data Collection Notes

    Data collection was done through work with the World Bank economists and statistical offices in each of the countries (for the demographic data), and the Geospatial Operations Support Team (GOST) of the World Bank (for the spatial data, nighttime lights).

    Global Nighttime Lights (NTL) data was recorded by the Defense Meteorological Satellite Program (DMSP), in the National Geophysical Data Center (NGDC), NOAA. The data was collected using polar orbiting satellites that provide full cover of the globe twice a day. The satellites have an Operation Linescan system which allows them to detect low levels of visible-near infrared radiance at night. With this data, it is possible to detect clouds illuminated by moonlight, lights from cities and towns, industrial sites, gas flares, fires, lightning, and aurora.

    Depositor information

    Depositor
    Name Affiliation
    Sofia Zhukova World Bank
    Paula Restrepo Cadavid World Bank

    Data Access

    Citation requirements

    The use of the datasets must be acknowledged using a citation which would include:

    • the identification of the Primary Investigator (including country name);
    • the full title of the survey and its acronym (when available), and the year(s) of implementation;
    • the survey reference number;
    • the source and date of download (for datasets disseminated online).

    Example:

    Paula Restrepo Cadavid, Grace Cineas, Sofia Zhukova, World Bank. Cities in Europe and Central Asia Database 1992 - 2012 (CECA 1992-2012), Ref. ECA_2015_CECA_v01_M. Dataset downloaded from [URL] on [date].

    Disclaimer and copyrights

    Disclaimer

    The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.

    Contacts

    Contacts
    Name Affiliation Email
    Paula Restrepo Cadavid World Bank prestrepocadavid@worldbank.org
    Sofia Zhukova World Bank szhukova@worldbank.org

    Metadata production

    DDI Document ID

    DDI_ECA_2015_CECA_v02_M_WB

    Producers
    Name Affiliation Role
    GSU09 - Urban, DRM ECA World Bank Sharing of metadata, the dataset and documents
    Development Data Group World Bank Preparing and publishing of the DDI
    Date of Metadata Production

    2017-11-16

    Metadata version

    DDI Document version

    DDI Document - Version 02 - (04/27/21)
    This version is identical to DDI_ECA_2015_CECA_v01_M_WB but country field has been updated to capture all the countries covered by survey.

    v01 (November 2017)

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