Predicting Poverty Using Geospatial Data in Thailand

Predicting Poverty Using Geospatial Data in Thailand

Poverty statistics are conventionally compiled using data from socioeconomic surveys. This study examines an alternative approach to estimating poverty by investigating whether readily available geospatial data can accurately predict the spatial distribution of poverty in Thailand. In particular, th...

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Bibliographic Details
Main Authors: Nattapong Puttanapong, Arturo Martinez, Joseph Albert Nino Bulan, Mildred Addawe, Ron Lester Durante, Marymell Martillan
Format: Article
Language:English
Published: MDPI AG 2022-04-01
Series:ISPRS International Journal of Geo-Information
Subjects:
poverty
Thailand
geospatial
machine learning
Online Access:https://www.mdpi.com/2220-9964/11/5/293

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