Planktonic patches are defined as areas where the abundance of planktonic organisms is above a threshold value thau. The estimation of patch size and shape can be approached using spatial statistical tools, using truncated random fields or indicator random fields as classifiers. In all these cases there is the risk of false positive and false negative errors. Here we present the results of a comparative study on the performance of four commonly used methods: conditional simulation and kriging, both in the original measurement units of the data and under an indicator transform. We used a misclassification cost function to compare the four methods. Our results show that conditional simulation in the original measurement units attains the lowest misclassification cost. We also illustrate how the point at which this minimum is attained can be used to chose an optimal cut-off value for binary classification.

Keywords: Patchiness; Kriging; Conditional simulation

Biography: Fisheries biologist, has worked in spatial modeling of planctonic distribution in aquatic systems during the last 5 years. Intersted in space- time modeling of natural resource distribution.