Distinguishing high and low anopheline-producing rice fields using remote sensing and GIS technologies

Byron Wood*, Robert Washino, Louisa Beck, Kathy Hibbard, Mike Pitcairn, Donald Roberts, Eliska Rejmankova, Jack Paris, Carl Hacker, Joan Salute, Paul Sebesta, Llewellyn Legters

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

57 Scopus citations

Abstract

Worldwide, 140 million ha are devoted to rice cultivation, mostly in developing countries of the tropics and subtropics where malaria still constitutes a serious human health problem. Because rice fields are flood-irrigated on a semi-permanent basis during each growing season, they provide an ideal breeding habitat for a number of potential mosquito vectors of malaria. One of these vectors, Anopheles freeborni, is distributed throughout nearly 240 000 ha of irrigated rice in northern and central California, and may serve as a model for the study of rice field mosquito population dynamics using spectral and spatial information. Analysis of field data revealed that rice fields with rapid early season vegetation canopy development, located near livestock pastures (i.e. bloodmeal sources), had greater mosquito larval populations than fields with more slowly developing vegetation canopies located further from pastures. Remote sensing reflectance measurements of early season rice canopy development and geographic information system (GIS) measurements of distance to livestock pasture were combined to distinguish between high and low mosquito-producing rice fields. These distinctions were made with 90% accuracy nearly 2 months before anopheline larval populations peaked.

Original languageEnglish
Pages (from-to)277-288
Number of pages12
JournalPreventive Veterinary Medicine
Volume11
Issue number3-4
DOIs
StatePublished - Dec 1991
Externally publishedYes

Fingerprint

Dive into the research topics of 'Distinguishing high and low anopheline-producing rice fields using remote sensing and GIS technologies'. Together they form a unique fingerprint.

Cite this