Sampling design for binary geostatistical data, application to inspection actions of fishing activity in Portugal

Abstract

The definition of surveillance routes is a very important but complex issue. The Portuguese Navy, in its common form of operation is in charge of the Naval Standard Device, which is distributed throughout the various coastal areas of the country. Enforcement actions can involve very high costs, so a good plan for the sampling designs used are in order, as to maximize the efficiency in obtaining information from the data of the actions developed over the area under consideration. The main objective of this study is to propose sampling design criteria based on geostatistical models, in the context of binary data on presumed maritime infractions in the Portuguese coast, that are advantageous in the optimization of maritime surveillance actions, in terms of efforts employed in their execution, in the maritime area of Portugal's responsibility. Two sampling design selection criteria are proposed: Maximum Risk Sampling design and Maximum Variance Risk Sampling Design. These are compared to the simple random design by the root mean square error (RMSE). A comparison of the designs at different sample sizes is made and the estimated risk maximization sampling design presents the best RMSE value. The proposed sampling designs may assist in the creation of alternative enforcement Portuguese Navy routes, optimizing the scheduling that maximizes the probability of finding a higher number of presumed fishing perpetrators with less resource efforts.