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Please use this identifier to cite or link to this item: http://hdl.handle.net/2067/2683

Title: Sampling strategies for estimating forest cover from remote sensing-based two-stage inventories
Authors: Corona, Piermaria
Fattorini, Lorenzo
Pagliarella, Maria Chiara
Keywords: Spatially balanced sampling
Auxiliary information
Horvitz-Thompson estimator
Difference estimator
Variance estimator
Forest monitoring
Issue Date: 2015
Publisher: Springer
Citation: Corona, P. et al. 2015. Sampling strategies for estimating forest cover from remote sensing-based two-stage inventories. "Forest Ecosystems" 2: 18
Abstract: Background: Remote sensing-based inventories are essential in estimating forest cover in tropical and subtropical countries, where ground inventories cannot be performed periodically at a large scale owing to high costs and forest inaccessibility (e.g. REDD projects) and are mandatory for constructing historical records that can be used as forest cover baselines. Given the conditions of such inventories, the survey area is partitioned into a grid of imagery segments of pre-fixed size where the
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DOI: 10.1186/s40663-015-0042-7
URI: http://hdl.handle.net/2067/2683
ISSN: 2197-5620
Appears in Collections:DiSAFRi - Archivio della produzione scientifica

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