Experimenting the design-based k-NN approach for mapping and estimation under forest management planning
Author(s)
Date Issued
2012
Type
article
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.
Additional information
L'articolo รจ disponibile sul sito dell'editore www.sisef.it
Citation
Mattioli, W. et al. 2012. Experimenting the design-based k-NN approach for mapping and estimation under forest management planning. "iForest" 5: 26-30
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