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Title: Estimation of small woodlot and tree row attributes in large-scale forest inventories
Authors: Baffetta, Federica
Fattorini, Lorenzo
Corona, Piermaria
Keywords: Tessellation stratified sampling;Hansen–Hurvitz estimator;Horvitz–Thompson estimator;Variance estimator;Tessellation stratified sampling · Hansen–Hurvitz estimator · Horvitz–Thompson estimator · Variance estimator · Monte Carlo study;Trees-outside-forests
Issue Date: 2011
Publisher: Springer Verlag
Source: Baffetta, F., Fattorini, L., Corona, P. 2011. Estimation of small woodlot and tree row attributes in large-scale forest inventories. "Environmental and Ecological Statistics" 18:147–167
Forest surveys performed over a large scale (e.g. national inventories)
involve several phases of sampling. The first phase is usually performed by means of
a systematic search of the study region, in which the region is partitioned into regular
polygons of the same size and points are randomly or systematically selected, one per
polygon. In most cases, first-phase points are selected and recognized in orthophotos or
very high resolution satellite images available for the whole study area. Disregarding
the subsequent phases, the first phase of sampling can be effectively adopted to select
small woodlots and tree rows, in the sense that a unit is selected when at least one firstphase
point falls within it. On the basis of such a scheme of sampling, approximately
unbiased estimators of abundance, coverage and other physical attributes readily measurable
from orthophotos (e.g. tree-row length) are proposed, together with estimators
of the corresponding variances. A simulation study is performed in order to check the
performance of the estimators under several distributions of units over the study area
(random, clustered, spatially trended).
L'articolo è disponibile sul sito dell'editore
ISSN: 1352-8505
DOI: 10.1007/s10651-009-0125-0
Appears in Collections:DiSAFRi - Archivio della produzione scientifica

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