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
Created on
Nov 30, 2017
Last modified
Jun 13, 2022
Page views
20043
Downloads
159401
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).
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.
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
- 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 | Abbreviation |
|---|---|
| Department for International Development, United Kingdom | DFID |
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2015-04-01 | 2016-09-01 |
Data Collection Mode
Other [oth]
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.
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.
Access policy
Contacts
| Name | Affiliation | |
|---|---|---|
| Paula Restrepo Cadavid | World Bank | prestrepocadavid@worldbank.org |
| Sofia Zhukova | World Bank | szhukova@worldbank.org |
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].
- 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.
Metadata production
DDI Document ID
DDI_ECA_2015_CECA_v02_M_WB
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| GSU09 - Urban, DRM ECA | GSU09 | World Bank | Sharing of metadata, the dataset and documents |
| Development Data Group | DECDG | World Bank | Preparing and publishing of the DDI |
Date of Metadata Production
2017-11-16
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)
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)