Assessment of sampling strategies utilizing auxiliary information in large-scale forest inventory

Abstract

The National Forest Inventory of Finland (NFI) produces national-and regional-level statistics for sustainability assessment and strategical-level decision making. So far, the regional-level statistics are based on a systematic sampling design with geographical stratification. Auxiliary information such as remote sensing is not used for design or estimation at the regional level, but it is used at the small-area level, i.e., for municipality-level results. To improve the cost efficiency of the NFI, possibilities for using auxiliary data in both the design and estimation are of interest. We assessed the improvements obtainable by using an interpreted satellite image — the multisource NFI result from a previous NFI — as auxiliary information in the design phase. The results show that even though the multisource NFI map is not very accurate, significant improvements in efficiency can be obtained by using either the local pivotal method (LPM) or stratification. LPM improves efficiency by matching the sample distribution to population distribution. These results encourage us to further investigate (i) what would be the improvement with more accurate auxiliary information, for example, laser scanning data, and (ii) how LPM fits in a real-life situation where part of the plots are permanent and it would be used to select only the temporary plots.