IPM from Space: Using Satellite Imagery to Construct Regional Crop Maps for Studying Crop—Insect Interaction

Areawide knowledge of the population dynamics of a pest and its natural enemies is an integral part of regional integrated pest management (IPM) programs. Often, spatially explicit population modeling can provide a better understanding of large-scale population dynamics in relation to the crop system. A drawback of spatial modeling for studying insects in agricultural systems is that maps of the crop system used to drive the models often are complex and difficult to construct. Here, we show how regional crop systems can be mapped using satellite remote sensing imagery and how the resulting crop maps are prepared for use with spatially explicit models to study insect—crop interactions. As an example, we map the agricultural region in Imperial Valley, CA, where the whitefly Bemisia argentifolii Bellows & Perring is a serious pest. Landsat satellite images of the valley are combined with ground survey data on the crop system to construct whitefly resource maps. We use a maximum likelihood method and training data sets prepared from ground survey data to identify the multispectral signatures of crops and other land-cover features recorded by the Landsat sensors. Further, we use whitefly reproduction as an example to show how the classified crop maps can be transformed into maps of biological parameters. The parameter maps then can be used to drive a spatially explicit population model to study whitefly dynamics and management strategies in the crop system.