http://www.cnr.it/ontology/cnr/individuo/prodotto/ID5442

Computer-assisted discrimination of morphological units on north-central Crete (Greece), by applying multivariate statistics to local relief gradients (Articolo in rivista)

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Computer-assisted discrimination of morphological units on north-central Crete (Greece), by applying multivariate statistics to local relief gradients (Articolo in rivista) (literal)

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Adediran O. A. (1), Parcharidis I. (2), Poscolieri. M. (3), Pavlopoulos K. (4) (2004)
Computer-assisted discrimination of morphological units on north-central Crete (Greece), by applying multivariate statistics to local relief gradients
in Geomorphology (Amst.); Academic Press Ltd., Elsevier Science Ltd., London (Regno Unito)
(literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori

Adediran O. A. (1), Parcharidis I. (2), Poscolieri. M. (3), Pavlopoulos K. (4) (literal)

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(1) Department of Environmental Management, Mediterranean Agronomic Institute of Chania (Maich), Chania, Crete, Greece (2) Department of Geophysics-Geothermic, Faculty of Geology, University of Athens, Greece (3) CNR Istituto di Astrofisica Spaziale e Fisica Cosmica, Rome, Italy (4) Department of Geography, Harokopio University of Athens, Athens 17671, Greece (literal)

Titolo

Computer-assisted discrimination of morphological units on north-central Crete (Greece), by applying multivariate statistics to local relief gradients (literal)

Abstract

Traditional manual methods have been employed for decades to measure geomorphometric properties from topographic maps. Such measurement techniques tend to be tedious and time-consuming and the designated landform elements cannot be easily overlaid on any digital map and imagery for further applied research. This study deals with a new quantitative geomorphometric procedure, based on the multivariate statistical analysis of local topographic gradients within a part of northcentral Crete. This method employs sets of computer algorithms that automatically extract and classify geomorphometric properties from Digital Elevation Models (DEMs). This was done by evaluating the morphological setting around each pixel of the DEM along the eight azimuth directions. ISODATA unsupervised classification was implemented to generate 10 morphometric classes showing the spatial distribution of areas with a similar geomorphic scenario. Results revealed that this approach permitted a quick estimation of the spatial distribution of morphologically homogeneous terrain units. It also demonstrated the ability of the delineated landform elements to be superimposed on any digital map and imagery for further investigation. This became apparent during the examination of the relationship between the geomorphological units and the land-cover/land-use types in the study area. Both relative association and the dominant land cover/land use types in relation to geomorphological units are presented. (literal)

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