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Non-industrial private forestry is important in many European countries as well as in the United States and eastern provinces of Canada. Private forests are especially important in Finland because the forest industries are highly dependent on private timber supply. In this article, we present the Finnish monitoring system for private forestry. Forest owners receive mailed inquiries regarding demographics, holding characteristics, ownership objectives, areas of silvicultural treatments, and timber sales, as well as connections with extension organizations. Studies based on such data have been useful in planning and implementation of national forestry programs and policies.

Landowner classifications based on their objectives have been used to describe the heterogeneous group of landowners. As the accurate information on landowners preferences is essential in policy planning and evaluation of the effects of various policy instruments, there is a need to develop feasible methods for classifying land owners. In this study we apply objective based classification to farmland owners using the data of Finnish farmland owners. We compare two classification methods, traditional cluster analysis and latent class analysis, in terms of their criterion validity. The comparison of criterion validity, consisting from convergent, concurrent, discriminant and predictive components of validity, revealed that latent class analysis was superior method. The analysis showed that objective grouping of farmland owners was relevant predictor of landowner behavior, and is thus valuable information for agricultural policy makers.3

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