What is it about?
This paper examines forest resource mapping from a statistical perspective, highlighting the opportunity to use a design-based approach to ensure inferential congruency with the estimation of averages and totals of forest attributes.
Featured Image
Why is it important?
Traditionally, in forest surveys estimates of averages and totals are obtained using design-unbiased estimators, with known variance expressions that can be easily estimated using standard sampling methodologies. The paper emphasizes the prominent role of kNN and Random Forest techniques in forest mapping while addressing the methodological limitations identified over more than thirty years of forest literature in efforts to estimate map precision. The critical importance of design-based map consistency, often overlooked in forest literature, is discussed and clarified, demonstrating that it allows for the development of design-based estimators of map precision through bootstrap resampling from the estimated maps.
Perspectives
This paper has explored the opportunity to use a design-based approach to ensure inferential congruency between mapping and the estimation of averages and totals of forest attributes, while also addressing the methodological challenges identified over more than thirty years of forest literature in attempts to estimate map precision. The proposed approach would ultimately enable statistically sound, design-based estimation of map precision, at least within the tessellated sampling schemes commonly used in forest surveys, particularly large-scale ones such as NFIs.
Piermaria Corona
University of Tuscia, Viterbo (Italy)
Read the Original
This page is a summary of: Statistical considerations for enhanced forest resource mapping, Silva Fennica, January 2025, Finnish Society of Forest Science,
DOI: 10.14214/sf.24063.
You can read the full text:
Contributors
The following have contributed to this page
