Estimating high mosquito-producing rice fields using spectral and spatial data

Abstract

The cultivation of irrigated rice provides ideal larval habitat for a number of anopheline vcclors of malaria throughout the world. Anopheles freeborni, a potential vector of human malaria, is associated with the nearly 240 000 hectares of irrigalcd 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 dala revealed that rice fields with early season canopy development, that are located near bloodmcal 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 distances 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 cither a discriminant or Bayesian analysis, the identification of high mosquito-producing fields was made with 85 per cent 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.