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European Journal of Forest Research

, Volume 125, Issue 1, pp 57–66 | Cite as

The assessment of tree row attributes by stratified two-stage sampling

  • Piermaria CoronaEmail author
  • Lorenzo Fattorini
Original Paper

Abstract

Tree row inventories are of increasing interest because tree rows mitigate wind erosion and desertification, protect agricultural crops, enhance rural landscape quality, act as bio-corridors, carbon sinks, and a source for bio-energy. The main objective of tree row inventories is to estimate population parameters such as total tree numbers, total tree numbers by species, the mean stem diameter at breast height, the mean tree height and total wood volume. The estimation of these quantities may be straightforwardly carried out whenever aerial images are available in such a way that tree rows can be counted: in these cases, a two-stage cluster sampling may be performed in which the primary units sampled in the first stage are the tree rows in the study area while the secondary units sampled in the second stage are the trees within the selected rows. This paper proposes two sets of two-stage estimators for the interest parameters, based on the Horvitz–Thompson and ratio criteria, together with the corresponding estimators for their sampling variances. The use of stratification is also considered. The proposed procedure was applied to perform a tree row inventory in the Pontina plain (Central Italy): in this case, the tree rows were enumerated by means of ortho-corrected airborne images and stratification was carried out on the basis of the prevailing species and age classes. The inventory results are interesting from a forestry perspective as well as for checking the effectiveness of the procedure.

Keywords

Linear tree systems Windbreaks Multiresource forest inventories Two-stage sampling Horvitz–Thompson estimators Ratio estimators Italy 

Notes

Acknowledgements

The work, carried out by the authors in equal parts, was funded by ARSIAL (Latium Region). We are grateful for technical assistance from Simone Bollati and Giuseppe Clementi for their fieldwork. We would also like thanking two anonymous reviewers for their helpful comments on an earlier draft.

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Copyright information

© Springer-Verlag 2005

Authors and Affiliations

  1. 1.Dipartimento di Scienze dell’Ambiente Forestale e delle sue RisorseUniversità della TusciaViterboItaly
  2. 2.Dipartimento di Metodi QuantitativiUniversità di SienaSienaItaly

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