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Understanding the evidence base for poverty-environment relationships using remotely sensed satellite data : an example from Assam, India

Watmough, Gary R.; Atkinson, Peter M.; Saikia, Arupjyoti; … - In: World development : the multi-disciplinary … 78 (2016), pp. 188-203

Persistent link: https://www.econbiz.de/10011602510

Estimating local poverty measures using satellite images : a pilot application to Central America

Klemens, Ben; Coppola, Andrea; Shron, Max - 2015

Persistent link: https://www.econbiz.de/10011298550

Poverty from space : using high-resolution satellite imagery for estimating economic well-being

Engstrom, Ryan; Hersh, Jonathan; Newhouse, David Locke - 2017

Persistent link: https://www.econbiz.de/10011794640

Mapping poverty rates in Chile with night lights and fractional multinomial models : introduction

Cecchini, Simone; Savio, Giovanni; Tromben, Varinia - In: Regional science policy and practice : RSPP 14 (2022) 4, pp. 850-876

Persistent link: https://www.econbiz.de/10013401842

Using satellite data to guide urban poverty reduction

Sohnesen, Thomas Pave; Fisker, Peter Simonsen; … - In: Review of income and wealth 68 (2022), pp. S282-S294

Persistent link: https://www.econbiz.de/10013479725

Energy poverty prediction in the United Kingdom : a machine learning approach

Al Kez, Dlzar; Foley, Aoife; Abdul, Zrar Khald; … - In: Energy policy : the international journal of the … 184 (2024), pp. 1-17

Persistent link: https://www.econbiz.de/10014454912

Profiling Poverty with Multivariate Adaptive Regression Splines

Barrios, Erniel B.; Mina, Christian D. - 2009

Using data from the 2003 Family Income and Expenditure Survey and 2005 Community-based Monitoring System for a city, Multivariate Adaptive Regression Splines (MARS) is used in identifying household poverty correlates in the Philippines. Models produced by MARS are more parsimonious yet contain...

Persistent link: https://www.econbiz.de/10011421152