Understanding the evidence base for poverty-environment relationships using remotely sensed satellite data: An example from Assam, India
Understanding the evidence base for poverty-environment relationships using remotely sensed satellite data: An example from Assam, India
This article presents results from an investigation of the relationships between welfare and geographic metrics from over 14,000 villages in Assam, India. Geographic metrics accounted for 61% of the variation in the lowest welfare quintile and 57% in the highest welfare quintile. Travel time to market towns, percentage of a village covered with woodland, and percentage of a village covered with winter crop were significantly related to welfare. These results support findings in the literature across a range of different developing countries. Model accuracy is unprecedented considering that the majority of geographic metrics were derived from remotely sensed data.
Environment, India, Livelihoods, Poverty, Remote sensing
188-203
Watmough, Gary R.
6ed84a4f-0106-4665-b810-4fa71baefb8c
Atkinson, Peter M.
96e96579-56fe-424d-a21c-17b6eed13b0b
Saikia, Arupjyoti
dd99e2d6-e334-499a-ac4f-68baa9758b0a
Hutton, Craig W.
9102617b-caf7-4538-9414-c29e72f5fe2e
1 February 2016
Watmough, Gary R.
6ed84a4f-0106-4665-b810-4fa71baefb8c
Atkinson, Peter M.
96e96579-56fe-424d-a21c-17b6eed13b0b
Saikia, Arupjyoti
dd99e2d6-e334-499a-ac4f-68baa9758b0a
Hutton, Craig W.
9102617b-caf7-4538-9414-c29e72f5fe2e
Watmough, Gary R., Atkinson, Peter M., Saikia, Arupjyoti and Hutton, Craig W.
(2016)
Understanding the evidence base for poverty-environment relationships using remotely sensed satellite data: An example from Assam, India.
World Development, 78, .
(doi:10.1016/j.worlddev.2015.10.031).
Abstract
This article presents results from an investigation of the relationships between welfare and geographic metrics from over 14,000 villages in Assam, India. Geographic metrics accounted for 61% of the variation in the lowest welfare quintile and 57% in the highest welfare quintile. Travel time to market towns, percentage of a village covered with woodland, and percentage of a village covered with winter crop were significantly related to welfare. These results support findings in the literature across a range of different developing countries. Model accuracy is unprecedented considering that the majority of geographic metrics were derived from remotely sensed data.
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Accepted/In Press date: 3 October 2015
e-pub ahead of print date: 28 October 2015
Published date: 1 February 2016
Keywords:
Environment, India, Livelihoods, Poverty, Remote sensing
Identifiers
Local EPrints ID: 413626
URI: http://eprints.soton.ac.uk/id/eprint/413626
ISSN: 0305-750X
PURE UUID: 5c7b7921-35ad-476d-950a-5c7bb94816bb
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Date deposited: 30 Aug 2017 16:31
Last modified: 16 Mar 2024 03:18
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Author:
Gary R. Watmough
Author:
Peter M. Atkinson
Author:
Arupjyoti Saikia
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