Semi-Automated Classification of Landform Elements in Armenia Based on SRTM DEM using K-Means Unsupervised Classification

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F17%3A00096313" target="_blank" >RIV/00216224:14310/17:00096313 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.degruyter.com/view/j/quageo.2017.36.issue-1/quageo-2017-0007/quageo-2017-0007.xml?format=INT" target="_blank" >https://www.degruyter.com/view/j/quageo.2017.36.issue-1/quageo-2017-0007/quageo-2017-0007.xml?format=INT</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1515/quageo-2017-0007" target="_blank" >10.1515/quageo-2017-0007</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Semi-Automated Classification of Landform Elements in Armenia Based on SRTM DEM using K-Means Unsupervised Classification

Popis výsledku v původním jazyce

Land elements have been used as basic landform descriptors in many science disciplines, including soil mapping, vegetation mapping, and landscape ecology. This paper presents a semi-automatic method based on k-means unsupervised classification to analyze geomorphometric features as landform elements in Armenia. First, several data layers were derived from DEM: elevation, slope, profile curvature, plan curvature and flow path length. Then, k-means algorithm has been used for classifying landform elements based on these morphomertic parameters. The classification has seven landform classes. Overall, landform classification is performed in the form of a three-level hierarchical scheme. The resulting map reflects the general topography and landform character of Armenia.

Název v anglickém jazyce

Semi-Automated Classification of Landform Elements in Armenia Based on SRTM DEM using K-Means Unsupervised Classification

Popis výsledku anglicky

Land elements have been used as basic landform descriptors in many science disciplines, including soil mapping, vegetation mapping, and landscape ecology. This paper presents a semi-automatic method based on k-means unsupervised classification to analyze geomorphometric features as landform elements in Armenia. First, several data layers were derived from DEM: elevation, slope, profile curvature, plan curvature and flow path length. Then, k-means algorithm has been used for classifying landform elements based on these morphomertic parameters. The classification has seven landform classes. Overall, landform classification is performed in the form of a three-level hierarchical scheme. The resulting map reflects the general topography and landform character of Armenia.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10508 - Physical geography

Projekt

—

Návaznosti

N - Vyzkumna aktivita podporovana z neverejnych zdroju

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Quaestiones geographicae

ISSN

0137-477X

e-ISSN

—

Svazek periodika

36

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

PL - Polská republika

Počet stran výsledku

11

Strana od-do

93-103

Kód UT WoS článku

000400495600007

EID výsledku v databázi Scopus

2-s2.0-85016054482