Linking remote sensing, land cover and disease
Linking remote sensing, land cover and disease
Land cover is a critical variable in epidemiology and can be characterized remotely. A framework is used to describe both the links between land cover and radiation recorded in a remotely sensed image, and the links between land cover and the disease carried by vectors. The framework is then used to explore the issues involved when moving from remotely sensed imagery to land cover and then to vector density/disease risk. This exploration highlights the role of land cover: the need to develop a sound knowledge of each link in the predictive sequence; the problematic mismatch between the spatial units of the remotely sensed and epidemiological data and the challenges and opportunities posed by adding a temporal mismatch between the remotely sensed and epidemiological data. The paper concludes with a call for both greater understanding of the physical components of the proposed framework and the utilization of optimized statistical tools as prerequisites to progress in this field.
37-80
Curran, P.J.
3f5c1422-c154-4533-9c84-f2afb77df2de
Atkinson, P.M.
96e96579-56fe-424d-a21c-17b6eed13b0b
Milton, E.J.
f6cb5c0d-a5d4-47d7-860f-096de08e0c24
Foody, G.M.
06e50027-603d-4a5b-88f5-af2bb6235a37
2000
Curran, P.J.
3f5c1422-c154-4533-9c84-f2afb77df2de
Atkinson, P.M.
96e96579-56fe-424d-a21c-17b6eed13b0b
Milton, E.J.
f6cb5c0d-a5d4-47d7-860f-096de08e0c24
Foody, G.M.
06e50027-603d-4a5b-88f5-af2bb6235a37
Curran, P.J., Atkinson, P.M., Milton, E.J. and Foody, G.M.
(2000)
Linking remote sensing, land cover and disease.
[in special issue: Remote Sensing and Geographical Information Systems in Epidemiology]
Advances in Parasitology, 47, .
(doi:10.1016/S0065-308X(00)47006-5).
Abstract
Land cover is a critical variable in epidemiology and can be characterized remotely. A framework is used to describe both the links between land cover and radiation recorded in a remotely sensed image, and the links between land cover and the disease carried by vectors. The framework is then used to explore the issues involved when moving from remotely sensed imagery to land cover and then to vector density/disease risk. This exploration highlights the role of land cover: the need to develop a sound knowledge of each link in the predictive sequence; the problematic mismatch between the spatial units of the remotely sensed and epidemiological data and the challenges and opportunities posed by adding a temporal mismatch between the remotely sensed and epidemiological data. The paper concludes with a call for both greater understanding of the physical components of the proposed framework and the utilization of optimized statistical tools as prerequisites to progress in this field.
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Published date: 2000
Identifiers
Local EPrints ID: 17310
URI: http://eprints.soton.ac.uk/id/eprint/17310
ISSN: 0065-308X
PURE UUID: 4dedc5f5-6848-4d64-8c6f-a2224403e56d
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Date deposited: 24 Aug 2005
Last modified: 16 Mar 2024 02:46
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Author:
P.J. Curran
Author:
P.M. Atkinson
Author:
G.M. Foody
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