X
feed icon rss

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Online Resource
    Online Resource
    Estimating Small Area Population Density Using Survey Data and Satellite Imagery : An Application to Sri Lanka (2019)
    Washington, D.C. :The World Bank,
    Details
    UID:
    almafu_9959045270302883
    Format: 1 online resource (43 pages)
    Series Statement: Policy research working papers.
    Content: Country-level census data are typically collected once every 10 years. However, conflict, migration, urbanization, and natural disasters can cause rapid shifts in local population patterns. This study uses Sri Lankan data to demonstrate the feasibility of a bottom-up method that combines household survey data with contemporaneous satellite imagery to track frequent changes in local population density. A Poisson regression model based on indicators derived from satellite data, selected using the least absolute shrinkage and selection operator, accurately predicts village-level population density. The model is estimated in villages sampled in the 2012/13 Household Income and Expenditure Survey to obtain out-of-sample density predictions in the nonsurveyed villages. The predictions approximate the 2012 census density well and are more accurate than other bottom-up studies based on lower-resolution satellite data. The predictions are also more accurate than most publicly available population products, which rely on areal interpolation of census data to redistribute population at the local level. The accuracies are similar when estimated using a random forest model, and when density estimates are expressed in terms of population counts. The collective evidence suggests that combining surveys with satellite data is a cost-effective method to track local population changes at more frequent intervals.
    Language: English
    DOI: 10.1596/1813-9450-8776
    URL: Volltext  (kostenfrei)
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    Fulltext
    FU Berlin
    EUV Frankfurt
    HTW Berlin
    Charité
  • 2
    Online Resource
    Online Resource
    Estimating small area population density using survey data and satellite imagery : an application to Sri Lanka (2019)
    Washington, DC, USA : World Bank Group, Poverty and Equity Global Practice
    Details
    UID:
    gbv_1666275328
    Format: 1 Online-Ressource (circa 43 Seiten) , Illustrationen
    Series Statement: Policy research working paper 8776
    Content: Country-level census data are typically collected once every 10 years. However, conflict, migration, urbanization, and natural disasters can cause rapid shifts in local population patterns. This study uses Sri Lankan data to demonstrate the feasibility of a bottom-up method that combines household survey data with contemporaneous satellite imagery to track frequent changes in local population density. A Poisson regression model based on indicators derived from satellite data, selected using the least absolute shrinkage and selection operator, accurately predicts village-level population density. The model is estimated in villages sampled in the 2012/13 Household Income and Expenditure Survey to obtain out-of-sample density predictions in the nonsurveyed villages. The predictions approximate the 2012 census density well and are more accurate than other bottom-up studies based on lower-resolution satellite data. The predictions are also more accurate than most publicly available population products, which rely on areal interpolation of census data to redistribute population at the local level. The accuracies are similar when estimated using a random forest model, and when density estimates are expressed in terms of population counts. The collective evidence suggests that combining surveys with satellite data is a cost-effective method to track local population changes at more frequent intervals
    Additional Edition: Erscheint auch als Druck-Ausgabe Engstrom, Ryan Estimating Small Area Population Density Using Survey Data and Satellite Imagery: An Application to Sri Lanka Washington, D.C : The World Bank, 2019
    Language: English
    Keywords: Graue Literatur
    DOI: 10.1596/1813-9450-8776
    URL: Volltext  (lizenzpflichtig)
    URL: Deutschlandweit zugänglich
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    Online Access
    Open Access Request
    UB Potsdam
    MPI Bildungsforschung
  • 3
    Book
    Book
    Patterns of inequality in the Indian labour market, 1983-2012 (2016)
    New Delhi : Academic Foundation | New Delhi : Institute for Human Development
    Details
    UID:
    b3kat_BV044443638
    Format: 136 Seiten , Diagramme , 24 cm
    ISBN: 9789332703575
    Note: Includes bibliographical references (pages 135-136)
    Language: English
    URL: Inhaltsverzeichnis
    Author information: Rodgers, Gerry 1946-
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Book
    F.-Ebert-Stiftung get availability status
  • 4
    Online Resource
    Online Resource
    Estimating Small Area Population Density Using Survey Data and Satellite Imagery : An Application to Sri Lanka (2019)
    Washington, D.C. :The World Bank,
    Details
    UID:
    edoccha_9959045270302883
    Format: 1 online resource (43 pages)
    Series Statement: Policy research working papers.
    Content: Country-level census data are typically collected once every 10 years. However, conflict, migration, urbanization, and natural disasters can cause rapid shifts in local population patterns. This study uses Sri Lankan data to demonstrate the feasibility of a bottom-up method that combines household survey data with contemporaneous satellite imagery to track frequent changes in local population density. A Poisson regression model based on indicators derived from satellite data, selected using the least absolute shrinkage and selection operator, accurately predicts village-level population density. The model is estimated in villages sampled in the 2012/13 Household Income and Expenditure Survey to obtain out-of-sample density predictions in the nonsurveyed villages. The predictions approximate the 2012 census density well and are more accurate than other bottom-up studies based on lower-resolution satellite data. The predictions are also more accurate than most publicly available population products, which rely on areal interpolation of census data to redistribute population at the local level. The accuracies are similar when estimated using a random forest model, and when density estimates are expressed in terms of population counts. The collective evidence suggests that combining surveys with satellite data is a cost-effective method to track local population changes at more frequent intervals.
    Language: English
    DOI: 10.1596/1813-9450-8776
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    Open Access Request
    Charité
  • 5
    Online Resource
    Online Resource
    Estimating Small Area Population Density Using Survey Data and Satellite Imagery : An Application to Sri Lanka (2019)
    Washington, D.C. :The World Bank,
    Details
    UID:
    edocfu_9959045270302883
    Format: 1 online resource (43 pages)
    Series Statement: Policy research working papers.
    Content: Country-level census data are typically collected once every 10 years. However, conflict, migration, urbanization, and natural disasters can cause rapid shifts in local population patterns. This study uses Sri Lankan data to demonstrate the feasibility of a bottom-up method that combines household survey data with contemporaneous satellite imagery to track frequent changes in local population density. A Poisson regression model based on indicators derived from satellite data, selected using the least absolute shrinkage and selection operator, accurately predicts village-level population density. The model is estimated in villages sampled in the 2012/13 Household Income and Expenditure Survey to obtain out-of-sample density predictions in the nonsurveyed villages. The predictions approximate the 2012 census density well and are more accurate than other bottom-up studies based on lower-resolution satellite data. The predictions are also more accurate than most publicly available population products, which rely on areal interpolation of census data to redistribute population at the local level. The accuracies are similar when estimated using a random forest model, and when density estimates are expressed in terms of population counts. The collective evidence suggests that combining surveys with satellite data is a cost-effective method to track local population changes at more frequent intervals.
    Language: English
    DOI: 10.1596/1813-9450-8776
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    Open Access Request
    FU Berlin
  • 6
    Online Resource
    Online Resource
    Estimating Small Area Population Density Using Survey Data and Satellite Imagery : An Application to Sri Lanka (2019)
    World Bank, Washington, DC
    Details
    UID:
    gbv_1759629405
    Format: 1 Online-Ressource
    Series Statement: Policy Research Working Paper No. 8776
    Content: Country-level census data are typically collected once every 10 years. However, conflict, migration, urbanization, and natural disasters can cause rapid shifts in local population patterns. This study uses Sri Lankan data to demonstrate the feasibility of a bottom-up method that combines household survey data with contemporaneous satellite imagery to track frequent changes in local population density. A Poisson regression model based on indicators derived from satellite data, selected using the least absolute shrinkage and selection operator, accurately predicts village-level population density. The model is estimated in villages sampled in the 2012/13 Household Income and Expenditure Survey to obtain out-of-sample density predictions in the nonsurveyed villages. The predictions approximate the 2012 census density well and are more accurate than other bottom-up studies based on lower-resolution satellite data. The predictions are also more accurate than most publicly available population products, which rely on areal interpolation of census data to redistribute population at the local level. The accuracies are similar when estimated using a random forest model, and when density estimates are expressed in terms of population counts. The collective evidence suggests that combining surveys with satellite data is a cost-effective method to track local population changes at more frequent intervals
    Note: South Asia , Sri Lanka , English
    Language: English
    URL: kostenfrei
    URL: kostenfrei
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    Stabi Berlin
  • 7
    Book
    Book
    Growth and inequality : the contrasting trajectories of India and Brazil (2017)
    Cambridge : Cambridge University Press
    Details
    UID:
    gbv_894935119
    Format: xxvi, 349 Seiten , Illustrationen
    ISBN: 9781108416191
    Content: "Discusses the patterns of growth in both India and Brazil and their consequences for inequality, along with an analysis of labour market structures, wages and employment."
    Content: Brazil and India : a mirror image of each other? -- Approach and method -- Brazil and India in the decades before 1980 -- India and Brazil from 1980 until 2014 -- Key divides and cleavages ruptures, continuities, or adaptation? -- Index
    Note: Literaturverzeichnis: Seite 317-341, Literaturhinweise
    Additional Edition: Erscheint auch als Online-Ausgabe Barbosa, Alexandre de Freitas Growth and Inequality Cambridge : Cambridge University Press, 2017 ISBN 9781108588874
    Additional Edition: Erscheint auch als Online-Ausgabe Barbosa, Alexandre de Freitas Growth and inequality Cambridge : Cambridge University Press, 2017 ISBN 9781108236027
    Additional Edition: ISBN 9781108416191
    Language: English
    Subjects: Economics
    RVK:
    QG 020
    Keywords: Indien ; Brasilien ; Wirtschaftsentwicklung ; Gesellschaft ; Ungleichheit
    URL: Cover
    URL: Inhaltsverzeichnis
    Author information: Rodgers, Gerry 1946-
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Book
    Ibero-Amerik. Institut get availability status
Nothing or not found what you are looking for? Please check your search query or use the Interlibrary Loan Search.
Close ⊗
This website uses cookies and the analysis tool Matomo. Further information can be found on the KOBV privacy pages