Predicting poverty using geospatial data in Thailand
Year of publication: |
2020
|
---|---|
Authors: | Puttanapong, Nattapong ; Martinez, Arturo M. ; Addawe, Mildred ; Bulan, Joseph ; Durante, Ron Lester ; Martillan, Marymell |
Publisher: |
Manila : Asian Development Bank (ADB) |
Subject: | big data | computer vision | data for development | machine learning algorithm | multidimensional poverty | official statistics | poverty | SDG | Thailand |
Series: | |
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Type of publication: | Book / Working Paper |
Type of publication (narrower categories): | Working Paper |
Language: | English |
Other identifiers: | 10.22617/WPS200434-2 [DOI] 1744291748 [GVK] hdl:10419/246707 [Handle] RePEc:ris:adbewp:0630 [RePEc] |
Classification: | C19 - Econometric and Statistical Methods: General. Other ; D31 - Personal Income, Wealth and Their Distributions ; I32 - Measurement and Analysis of Poverty ; O15 - Human Resources; Income Distribution; Migration |
Source: |
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Predicting poverty using geospatial data in Thailand
Puttanapong, Nattapong, (2020)
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Applying artificial intelligence on satellite imagery to compile granular poverty statistics
Hofer, Martin, (2020)
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Applying artificial intelligence on satellite imagery to compile granular poverty statistics
Hofer, Martin, (2020)
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Predicting poverty using geospatial data in Thailand
Puttanapong, Nattapong, (2020)
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Predicting Poverty Using Geospatial Data in Thailand
Puttanapong, Nattapong, (2021)
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Compiling granular population data using geospatial information
Mitterling, Thomas, (2021)
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