Phenological analysis of a Mediterranean maquis vegetation based on data processing routines of digital images
Abstract
Data di Pubblicazione:
2015
Abstract:
Near-surface remote sensing techniques are used to quantify, at high temporal resolution, and with
a certain degree of spatial integration, the seasonal variations of the surface optical and radiometric
properties. These data provide information on vegetation phenological and ecophysiological
responses (Richardson et al 2009; Sonnentag 2011). The ECO-SCALE (Integrated High
Resolution Monitoring of Mediterranean vegetation) project is aimed to the development and
validation of new technologies and methodologies for the identification of functional responses of
natural vegetation in a Mediterranean area to environmental and climatic changes. In particular,
the project aims to develop an integrated system for environmental monitoring based on digital
photography, hyperspectral radiometry, and micrometeorological techniques. The analyses of
integrated data obtained from different methods and techniques would improve our knowledge of
the mechanisms underlying the development processes of Mediterranean species. In this paper
results of the specific work package of the project aimed to implement a methodology based on
digital images for the automated phenological vegetation monitoring are presented, with particular
regards to those related to the analysis of a phenological behavior based on digital image. To the
end of retrieve phenological information from digital images, a routine of commands to process
the digital image file using the program MATLAB (R2014b, The MathWorks, Natick, Mass.) was
specifically created. The color channel information was extracted and the RGB value was
correlated with the pattern of phenological development. Results showed that the use of digital
images is well-suited to identify phenological pattern of shrubland Mediterranean species.
Tipologia CRIS:
04.02 Abstract in Atti di convegno
Keywords:
near-surface remote sensing; Mediterranean vegetation; automated phenological monitoring; digital images
Elenco autori:
Piga, Alessandra; Duce, Pierpaolo; Cesaraccio, Carla
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