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Emerging and vector-borne diseases: Role of high spatial resolution and hyperspectral images in analyses and forecasts

dc.contributor.authorWilson, Mark L.en_US
dc.date.accessioned2006-09-08T20:14:29Z
dc.date.available2006-09-08T20:14:29Z
dc.date.issued2002-03en_US
dc.identifier.citationWilson, Mark L.; (2002). "Emerging and vector-borne diseases: Role of high spatial resolution and hyperspectral images in analyses and forecasts." Journal of Geographical Systems 4(1): 31-42. <http://hdl.handle.net/2027.42/42346>en_US
dc.identifier.issn1435-5930en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/42346
dc.description.abstract Many infectious diseases that are emerging or transmitted by arthropod vectors have a strong link to landscape features. Depending on the source of infection or ecology of the transmitting vector, micro-habitat characteristics at the spatial scale of square meters or less may be important. Recently, satellite images have been used to classify habitats in an attempt to understand associations with infectious diseases. Whether high spatial resolution and hyperspectral (HSRH) images can be useful in studies of such infectious diseases is addressed. The nature of questions that such studies address and the desired accuracy and precision of answers will determine the utility of HSRH data. Need for such data should be based on the goals of the effort. Examples of kinds of questions and applications are discussed. The research implications and public health applications may depend on available analytic tools as well as epidemiological observations.en_US
dc.format.extent181459 bytes
dc.format.extent3115 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherSpringer-Verlag; Springer-Verlag Berlin Heidelbergen_US
dc.subject.otherJEL Classification: I1, I18en_US
dc.subject.otherLegacyen_US
dc.subject.otherKey Words: Epidemiology, Infectious Diseases, Remote Sensing, GIS, Environmenten_US
dc.titleEmerging and vector-borne diseases: Role of high spatial resolution and hyperspectral images in analyses and forecastsen_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelPhilosophyen_US
dc.subject.hlbsecondlevelNatural Resources and Environmenten_US
dc.subject.hlbsecondlevelGeography and Mapsen_US
dc.subject.hlbsecondlevelCivil and Environmental Engineeringen_US
dc.subject.hlbsecondlevelAtmospheric, Oceanic and Space Sciencesen_US
dc.subject.hlbtoplevelHumanitiesen_US
dc.subject.hlbtoplevelSocial Sciencesen_US
dc.subject.hlbtoplevelEngineeringen_US
dc.subject.hlbtoplevelScienceen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartments of Epidemiology and of Ecology and Evolutionary Biology, The University of Michigan, Ann Arbor, MI 48104-2029, USA (e-mail: wilsonml@umich.edu), USen_US
dc.contributor.affiliationumcampusAnn Arboren_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/42346/1/10109-4-1-31_20040031.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1007/s101090100072en_US
dc.identifier.sourceJournal of Geographical Systemsen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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