Exploring the links between census and environment using remotely sensed satellite sensor imagery
Exploring the links between census and environment using remotely sensed satellite sensor imagery
Relationships are often found between socio-economic variables and environmental factors for relatively small study regions. This research forms an exploratory data analysis using logistic regression to explore the (non-causal) relationships between socio-economic variables from a national census (female literacy and involvement in economic alternatives to agricultural work) and environmental metrics extracted from Earth observation (EO) data. The relationships observed often supported those found in the literature and field observations. The research highlighted the limited but potentially valuable use of EO data for monitoring socio-economic conditions which may be used to target development assistance in the future.
population, india, census, environment, remote sensing, logistic regression
284-303
Watmough, Gary R.
35e3ef1c-950a-4f43-95a1-035ee97ed778
Atkinson, Peter M.
96e96579-56fe-424d-a21c-17b6eed13b0b
Hutton, Craig W.
9102617b-caf7-4538-9414-c29e72f5fe2e
2013
Watmough, Gary R.
35e3ef1c-950a-4f43-95a1-035ee97ed778
Atkinson, Peter M.
96e96579-56fe-424d-a21c-17b6eed13b0b
Hutton, Craig W.
9102617b-caf7-4538-9414-c29e72f5fe2e
Watmough, Gary R., Atkinson, Peter M. and Hutton, Craig W.
(2013)
Exploring the links between census and environment using remotely sensed satellite sensor imagery.
Journal of Land Use Science, 8 (3), .
(doi:10.1080/1747423X.2012.667447).
Abstract
Relationships are often found between socio-economic variables and environmental factors for relatively small study regions. This research forms an exploratory data analysis using logistic regression to explore the (non-causal) relationships between socio-economic variables from a national census (female literacy and involvement in economic alternatives to agricultural work) and environmental metrics extracted from Earth observation (EO) data. The relationships observed often supported those found in the literature and field observations. The research highlighted the limited but potentially valuable use of EO data for monitoring socio-economic conditions which may be used to target development assistance in the future.
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Published date: 2013
Keywords:
population, india, census, environment, remote sensing, logistic regression
Organisations:
Global Env Change & Earth Observation
Identifiers
Local EPrints ID: 357154
URI: http://eprints.soton.ac.uk/id/eprint/357154
ISSN: 1747-423X
PURE UUID: 6de08706-d59d-461c-aa68-63e572973826
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Date deposited: 04 Oct 2013 13:22
Last modified: 15 Mar 2024 03:08
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Contributors
Author:
Gary R. Watmough
Author:
Peter M. Atkinson
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