Please use this identifier to cite or link to this item: http://hdl.handle.net/2067/2309
Title: Experimenting the design-based k-NN approach for mapping and estimation under forest management planning
Authors: Mattioli, Walter
Quatrini, Valerio
Di Paolo, Silvia
Di Santo, Daniele
Giuliarelli, Diego
Angelini, Alice
Portoghesi, Luigi
Corona, Piermaria
Keywords: Forest management planning;k-Nearest Neighbors;Landsat;Estimation;Mapping
Issue Date: 2012
Publisher: Italian Society of Silviculture and Forest Ecology
Source: Mattioli, W. et al. 2012. Experimenting the design-based k-NN approach for mapping and estimation under forest management planning. "iForest" 5: 26-30
Abstract: 
Estimation and mapping of forest attributes are a fundamental support for
forest management planning. This study describes a practical experimentation
concerning the use of design-based k-Nearest Neighbors (k-NN) approach to estimate
and map selected attributes in the framework of inventories at forest
management level. The study area was the Chiarino forest within the Gran Sasso
and Monti della Laga National Park (central Italy). Aboveground biomass and
current annual increment of tree volume were selected as the attributes of interest
for the test. Field data were acquired within 28 sample plots selected
by stratified random sampling. Satellite data were acquired by a Landsat 5 TM
multispectral image. Attributes from field surveys and Landsat image processing
were coupled by k-NN to predict the attributes of interest for each
pixel of the Landsat image. Achieved results demonstrate the effectiveness of
the k-NN approach for statistical estimation, that is compatible with the produced
forest attribute raster maps and also proves to be characterized, in the
considered study case, by a precision double than that obtained by conventional
inventory based on field sample plots only.
Description: 
L'articolo è disponibile sul sito dell'editore www.sisef.it
URI: http://hdl.handle.net/2067/2309
ISSN: 1971-7458
DOI: 10.3832/ifor0604-009
Appears in Collections:DiSAFRi - Archivio della produzione scientifica

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