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The process of land planning, addressed to operate the synthesis between development aims and appropriate policies of preservation and management of territorial resources, requires detailed analysis of the territory. Generally this analysis is carried out on the whole area of interest by making use of data stored in Geographic Information Systems (GIS), but a detailed analysis of changes in the landscape can be carried out only on a sample of the whole territory. A very efficient sample design is the adaptive sequential procedure with permanent random numbers (ASPRN) proposed by Carfagna and Marzialetti (2009). However, ASPRN obliges the environmental engineer to jump from one side to another of the study area. Carfagna (2007) proposed a two-steps selection procedure with permanent random numbers (TSPRN) which allows to overcome the operational drawbacks of the ASPRN. In this paper we apply both procedures to a study area, in order to compare them from an operational viewpoint and to set up a methodology which enables an efficient estimate of the change of main landscape features on large areas.

In this paper we propose a way to restrict extension bounds induced by coherent conditional lower-upper probability assessments. Such shrinkage turns out to be helpful whenever the natural bounds are too vague to be used. Since coherence of a conditional lower-upper probability assessment can be characterized through a class of conditional probability distributions, the idea is to take the intersection of the extension bounds induced by each single element of the class instead of the convex combination, as it is usually done. Coherence of such method is proved for extensions performed on both conditional events logical dependent and not-dependent on the initial domain.