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Linking remote sensing, land cover and disease

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Linking remote sensing, land cover and disease. / Curran, Paul J.; Atkinson, Peter M.; Milton, E. J. et al.
In: Advances in Parasitology, Vol. 47, 2000, p. 37-80.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Curran, PJ, Atkinson, PM, Milton, EJ & Foody, GM 2000, 'Linking remote sensing, land cover and disease', Advances in Parasitology, vol. 47, pp. 37-80. https://doi.org/10.1016/S0065-308X(00)47006-5

APA

Curran, P. J., Atkinson, P. M., Milton, E. J., & Foody, G. M. (2000). Linking remote sensing, land cover and disease. Advances in Parasitology, 47, 37-80. https://doi.org/10.1016/S0065-308X(00)47006-5

Vancouver

Curran PJ, Atkinson PM, Milton EJ, Foody GM. Linking remote sensing, land cover and disease. Advances in Parasitology. 2000;47:37-80. doi: 10.1016/S0065-308X(00)47006-5

Author

Curran, Paul J. ; Atkinson, Peter M. ; Milton, E. J. et al. / Linking remote sensing, land cover and disease. In: Advances in Parasitology. 2000 ; Vol. 47. pp. 37-80.

Bibtex

@article{8c7c5ef1a74f4d18b2e7ec5cbab260a1,
title = "Linking remote sensing, land cover and disease",
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.",
author = "Curran, {Paul J.} and Atkinson, {Peter M.} and Milton, {E. J.} and Foody, {Giles M.}",
year = "2000",
doi = "10.1016/S0065-308X(00)47006-5",
language = "English",
volume = "47",
pages = "37--80",
journal = "Advances in Parasitology",
issn = "0065-308X",
publisher = "Academic Press Inc.",

}

RIS

TY - JOUR

T1 - Linking remote sensing, land cover and disease

AU - Curran, Paul J.

AU - Atkinson, Peter M.

AU - Milton, E. J.

AU - Foody, Giles M.

PY - 2000

Y1 - 2000

N2 - 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.

AB - 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.

U2 - 10.1016/S0065-308X(00)47006-5

DO - 10.1016/S0065-308X(00)47006-5

M3 - Journal article

VL - 47

SP - 37

EP - 80

JO - Advances in Parasitology

JF - Advances in Parasitology

SN - 0065-308X

ER -