A global poverty map derived from satellite data

被引：416

作者：

Elvidge, Christopher D. ^{[1
]}

Sutton, Paul C. ^{[2
]}

Ghosh, Tilottama ^{[2
,3
]}

Tuttle, Benjamin T. ^{[2
,3
]}

Baugh, Kimberly E. ^{[3
]}

Bhaduri, Budhendra ^{[4
]}

Bright, Edward ^{[4
]}

机构：

[1] NOAA, Natl Geophys Data Ctr, US Dept Commerce, Boulder, CO 80205 USA

[2] Univ Denver, Dept Geog, Denver, CO 80208 USA

[3] Univ Colorado, Cooperat Inst Res Environm Sci, Boulder, CO 80309 USA

[4] Oak Ridge Natl Lab, US Dept Energy, Oak Ridge, TN 37831 USA

来源：

COMPUTERS & GEOSCIENCES | 2009年 / 35卷 / 08期

关键词：

Poverty; DMSP; Nighttime lights; World development indicators; POPULATION; EMISSIONS;

D O I：

10.1016/j.cageo.2009.01.009

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

A global poverty map has been produced at 30 arcsec resolution using a poverty index calculated by dividing population count (LandScan 2004) by the brightness of satellite observed lighting (DMSP nighttime lights). Inputs to the LandScan product include satellite-derived land cover and topography, plus human settlement outlines derived from high-resolution imagery. The poverty estimates have been calibrated using national level poverty data from the World Development Indicators (WDI) 2006 edition. The total estimate of the numbers of individuals living in poverty is 2.2 billion, slightly under the WDI estimate of 2.6 billion. We have demonstrated a new class of poverty map that should improve over time through the inclusion of new reference data for calibration of poverty estimates and as improvements are made in the satellite observation of human activities related to economic activity and technology access. Published by Elsevier Ltd.

引用

页码：1652 / 1660

页数：9

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