On the use of auxiliary information in spatial sampling

Technology development has led to a growing availability of low-cost data ready-to-use, frequently derived from large scale observations (i.e. pervasive systems like GPS sensors, or remote sensing earth observation technologies). Oftentimes, these can’t directly answer specific questions posed by researchers and users, even if they can are subject measurement errors self-selection bias. In both cases it is still necessary rely, at least partially, on ad-hoc probabilistic surveys. On the other hand, precision quality surveys estimates be improved using new sources as auxiliary information in design phase and/or estimation phase. We present sequential sampling strategy, suitable investigate spatially-related phenomenon, which exploits level order obtain efficient when relation between study variables not completely known univocally defined for whole population under study. Using this strategy final sample obtained after two (or more) steps: (i) first step we collect an initial target variable, used also variables; (ii) then, exploited tailor subsequent step; (iii) additional steps included applying procedure iteratively. The performance suggested investigated through Monte Carlo experiments considering several scenarios, differ distributions their relation.