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Estimating high mosquito-producing rice fields using spectral and spatial dataThe cultivation of irrigated rice provides ideal larval habitat for a number of anopheline vectors of malaria throughout the world. Anopheles freeborni, a potential vector of human malaria, is associated with the nearly 240,000 hectares of irrigated rice grown annually in Northern and Central California; therefore, this species can serve as a model for the study of rice field anopheline population dynamics. Analysis of field data revealed that rice fields with early season canopy development, that are located near bloodmeal sources (i.e., pastures with livestock) were more likely to produce anopheline larvae than fields with less developed canopies located further from pastures. Remote sensing reflectance measurements of early-season canopy development and geographic information system (GIS) measurements of distanes between rice fields and pastures with livestock were combined to distinguish between high and low mosquito-producing rice fields. Using spectral and distance measures in either a discriminant or Bayesian analysis, the identification of high mosquito-producing fields was made with 85 percent accuracy nearly two months before anopheline larval populations peaked. Since omission errors were also minimized by these approaches, they could provide a new basis for directing abatement techniques for the control of malaria vectors.
Document ID
19930028443
Acquisition Source
Legacy CDMS
Document Type
Reprint (Version printed in journal)
Authors
Wood, B. L.
(NASA Ames Research Center Moffett Field, CA, United States)
Beck, L. R.
(TGS Technology, Inc.; NASA, Ames Research Center Moffett Field, CA, United States)
Washino, R. K.
(California Univ. Davis, United States)
Hibbard, K. A.
(TGS Technology, Inc.; NASA, Ames Research Center Moffett Field, CA, United States)
Salute, J. S.
(NASA Ames Research Center Moffett Field, CA, United States)
Date Acquired
August 15, 2013
Publication Date
October 1, 1992
Publication Information
Publication: International Journal of Remote Sensing
Volume: 13
Issue: 15
ISSN: 0143-1161
Subject Category
Earth Resources And Remote Sensing
Accession Number
93A12440
Distribution Limits
Public
Copyright
Other

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