Identification of central Kenyan Rift Valley Fever virus vector habitats with landsat TM and evaluation of their flooding status with airborne imaging radar
Identifieur interne : 006607 ( Main/Exploration ); précédent : 006606; suivant : 006608Identification of central Kenyan Rift Valley Fever virus vector habitats with landsat TM and evaluation of their flooding status with airborne imaging radar
Auteurs : K. O. Pope [États-Unis] ; E. J. Sheffner [États-Unis] ; K. J. Linthicum [États-Unis] ; C. L. Bailey [États-Unis] ; T. M. Logan [États-Unis] ; E. S. Kasischke [États-Unis] ; K. Birney [États-Unis] ; A. R. Njogu [Kenya] ; C. R. Roberts [Kenya]Source :
- Remote Sensing of Environment [ 0034-4257 ] ; 1992.
English descriptors
- Teeft :
- Active vector, Animal health, Aperture radar, Arbovirus research, Avhrr, Avhrr data, Avhrr sensor, Backscatter, Backscatter characteristics, Band data, Best channel, Canadian aeronautics, Central kenya, Confidence interval, Control area, Control efforts, Corner reflectors, Dambo, Dambo classes, Dambos, Development center, Digital imagery, Emergent, Emergent grass, Emergent grasses, Emergent vegetation, Error bars, Field maps, Fifth symposium, Final classification, Flood detection, Full polarimetric, Future research, High rainfall, High resolution, Ieee trans, Infectious disease, Kenya, Landsat, Life cycle, Limited test, Linthicum, Medical research, Mosquito, Nasa ames research center, Nonflooded, Nonflooded areas, Nonflooded sites, Optical sensors, Outbreak, Overflight, Phase data, Pixel, Possible dambo, Possible dambo classes, Possible dambos, Probable dambo, Probable dambos, Queensland institute, Radar data, Reference site, Remote sens, Research institute, Rift, Rift valley fever, Rift valley fever epizootic, Rift valley fever vector, Sample areas, Season image, Second overflight, Sedge, Sens, Short grass, Short grass dambos, Short grasses, Significant change, Significant differences, Soil moisture, Space institute, Speckle noise, Standard deviation, Study area, Surface soil moisture, Tenth canadian symposium, Test site, Test sites, Track resolution, Vector habitats, Vegetation, Vegetation boundaries, Viral activity, Water surface, Wetland mapping.
Abstract
Abstract: Rift Valley Fever (RVF) is a mosquito-borne virus that affects livestock and humans in Africa. Landsat Thematic Mapper (TM) data are shown to be effective in identifying dambos, intermittently flooded areas that are potential mosquito breeding sites, in an area north of Nairobi, Kenya. Positive results were obtained from a limited test of flood detection in dambos with airborne high resolution L, C, and X band multipolarization synthetic aperture radar (SAR) imagery. L and C bands were effective in detecting flooded dambos, but LHH was by far the best channel for discrimination (p < 0.01) between flooded and nonflooded sites in both sedge and short grass environments. This study demonstrates the feasibility of a combined passive and active remote sensing program for monitoring the location and condition of RVF vector habitats, thus making future control of the disease more promising.
Url:
DOI: 10.1016/0034-4257(92)90002-2
Affiliations:
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R." last="Njogu">A. R. Njogu</name><affiliation wicri:level="1"><country xml:lang="fr">Kenya</country><wicri:regionArea>Kenya Trypanosomiasis Research Institute, Kikuyu</wicri:regionArea><wicri:noRegion>Kikuyu</wicri:noRegion></affiliation></author><author><name sortKey="Roberts, C R" sort="Roberts, C R" uniqKey="Roberts C" first="C. R." last="Roberts">C. R. Roberts</name><affiliation wicri:level="1"><country xml:lang="fr">Kenya</country><wicri:regionArea>U.S. Army Medical Research Unit, Nairobi</wicri:regionArea><wicri:noRegion>Nairobi</wicri:noRegion></affiliation></author></analytic><monogr></monogr><series><title level="j">Remote Sensing of Environment</title><title level="j" type="abbrev">RSE</title><idno type="ISSN">0034-4257</idno><imprint><publisher>ELSEVIER</publisher><date type="published" when="1992">1992</date><biblScope unit="volume">40</biblScope><biblScope unit="issue">3</biblScope><biblScope unit="page" from="185">185</biblScope><biblScope unit="page" to="196">196</biblScope></imprint><idno type="ISSN">0034-4257</idno></series></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0034-4257</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="Teeft" xml:lang="en"><term>Active vector</term><term>Animal health</term><term>Aperture radar</term><term>Arbovirus research</term><term>Avhrr</term><term>Avhrr data</term><term>Avhrr sensor</term><term>Backscatter</term><term>Backscatter characteristics</term><term>Band data</term><term>Best channel</term><term>Canadian aeronautics</term><term>Central kenya</term><term>Confidence interval</term><term>Control area</term><term>Control efforts</term><term>Corner reflectors</term><term>Dambo</term><term>Dambo classes</term><term>Dambos</term><term>Development center</term><term>Digital imagery</term><term>Emergent</term><term>Emergent grass</term><term>Emergent grasses</term><term>Emergent vegetation</term><term>Error bars</term><term>Field maps</term><term>Fifth symposium</term><term>Final classification</term><term>Flood detection</term><term>Full polarimetric</term><term>Future research</term><term>High rainfall</term><term>High resolution</term><term>Ieee trans</term><term>Infectious disease</term><term>Kenya</term><term>Landsat</term><term>Life cycle</term><term>Limited test</term><term>Linthicum</term><term>Medical research</term><term>Mosquito</term><term>Nasa ames research center</term><term>Nonflooded</term><term>Nonflooded areas</term><term>Nonflooded sites</term><term>Optical sensors</term><term>Outbreak</term><term>Overflight</term><term>Phase data</term><term>Pixel</term><term>Possible dambo</term><term>Possible dambo classes</term><term>Possible dambos</term><term>Probable dambo</term><term>Probable dambos</term><term>Queensland institute</term><term>Radar data</term><term>Reference site</term><term>Remote sens</term><term>Research institute</term><term>Rift</term><term>Rift valley fever</term><term>Rift valley fever epizootic</term><term>Rift valley fever vector</term><term>Sample areas</term><term>Season image</term><term>Second overflight</term><term>Sedge</term><term>Sens</term><term>Short grass</term><term>Short grass dambos</term><term>Short grasses</term><term>Significant change</term><term>Significant differences</term><term>Soil moisture</term><term>Space institute</term><term>Speckle noise</term><term>Standard deviation</term><term>Study area</term><term>Surface soil moisture</term><term>Tenth canadian symposium</term><term>Test site</term><term>Test sites</term><term>Track resolution</term><term>Vector habitats</term><term>Vegetation</term><term>Vegetation boundaries</term><term>Viral activity</term><term>Water surface</term><term>Wetland mapping</term></keywords></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Abstract: Rift Valley Fever (RVF) is a mosquito-borne virus that affects livestock and humans in Africa. Landsat Thematic Mapper (TM) data are shown to be effective in identifying dambos, intermittently flooded areas that are potential mosquito breeding sites, in an area north of Nairobi, Kenya. Positive results were obtained from a limited test of flood detection in dambos with airborne high resolution L, C, and X band multipolarization synthetic aperture radar (SAR) imagery. L and C bands were effective in detecting flooded dambos, but LHH was by far the best channel for discrimination (p < 0.01) between flooded and nonflooded sites in both sedge and short grass environments. This study demonstrates the feasibility of a combined passive and active remote sensing program for monitoring the location and condition of RVF vector habitats, thus making future control of the disease more promising.</div></front></TEI><affiliations><list><country><li>Kenya</li><li>États-Unis</li></country><region><li>Californie</li></region></list><tree><country name="États-Unis"><region name="Californie"><name sortKey="Pope, K O" sort="Pope, K O" uniqKey="Pope K" first="K. O." last="Pope">K. O. Pope</name></region><name sortKey="Bailey, C L" sort="Bailey, C L" uniqKey="Bailey C" first="C. L." last="Bailey">C. L. Bailey</name><name sortKey="Birney, K" sort="Birney, K" uniqKey="Birney K" first="K." last="Birney">K. Birney</name><name sortKey="Kasischke, E S" sort="Kasischke, E S" uniqKey="Kasischke E" first="E. S." last="Kasischke">E. S. Kasischke</name><name sortKey="Linthicum, K J" sort="Linthicum, K J" uniqKey="Linthicum K" first="K. J." last="Linthicum">K. J. Linthicum</name><name sortKey="Logan, T M" sort="Logan, T M" uniqKey="Logan T" first="T. M." last="Logan">T. M. Logan</name><name sortKey="Sheffner, E J" sort="Sheffner, E J" uniqKey="Sheffner E" first="E. J." last="Sheffner">E. J. Sheffner</name></country><country name="Kenya"><noRegion><name sortKey="Njogu, A R" sort="Njogu, A R" uniqKey="Njogu A" first="A. R." last="Njogu">A. R. Njogu</name></noRegion><name sortKey="Roberts, C R" sort="Roberts, C R" uniqKey="Roberts C" first="C. R." last="Roberts">C. R. Roberts</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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