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Pregled bibliografske jedinice broj: 596390

Using self-organizing maps in the visualization and analysis of forest inventory


Klobučar, Damir; Subašić Marko
Using self-organizing maps in the visualization and analysis of forest inventory // iForest, 5 (2012), 216-223 doi:10.3832/ifor0629-005 (međunarodna recenzija, članak, znanstveni)


CROSBI ID: 596390 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Using self-organizing maps in the visualization and analysis of forest inventory

Autori
Klobučar, Damir ; Subašić Marko

Izvornik
IForest (1971-7458) 5 (2012); 216-223

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
forest inventory; stand structural parameters; self-organizing maps; forest data visualization; neural networks

Sažetak
A lot of useful data on forest condition can be gathered from the Forest Inventory (FI). Without the help of data analysis tools, human experts cannot manually interpret information in such a large data set. Conventional multivariate statistical analyses provide results that are difficult to interpret and often do not represent the information in a satisfactory way. Our goal is to identify an alternative approach that will enable fast and efficient interpretation and analysis of the FI data. Such interpretation and analysis can be performed automatically with a clustering method, but all clustering methods have some shortcomings. Therefore, our aim was also to provide information in a form suitable for fast and intuitive visualization. Kohonen’s Self Organizing Map (SOM) is an alternative approach to data visualization and analysis of large multidimensional data sets. SOM provides different possibilities and our experiments are presented with component matrices of individual stand parameters and label matrices. In forming data clusters, we experimented with hierarchical and non hierarchical clustering methods. Our experiments showed that SOM provides useful information in a form suitable for data clustering and data visualization. This enables an efficient analysis of large FI data sets at different analysis scales. Clustering results obtained with SOM and two clustering algorithms are in accordance with ground truth. We have also considered the efficiency of SOM component matrices by visual comparison and correlation among structural parameters and by determining contributions of individual stand parameters to clustering input data. SOM application in visualization and analysis of stand structural parameters enables gathering quickly and efficiently holistic information on the current condition of forest stands and forest ecosystem development. Therefore we recommend the application of Kohonen’s SOM for visualization and analysis of FI data.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Računarstvo, Šumarstvo



POVEZANOST RADA


Projekti:
036-0362214-1989 - Inteligentne metode obrade i analize slika (Lončarić, Sven, MZO ) ( CroRIS)
068-0681966-2786 - Praćenje zdravstvenog stanja šuma metodama daljinskih istraživanja (Pernar, Renata, MZOS ) ( CroRIS)

Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb,
Fakultet šumarstva i drvne tehnologije

Profili:

Avatar Url Marko Subašić (autor)

Avatar Url Damir Klobučar (autor)

Poveznice na cjeloviti tekst rada:

doi www.sisef.it

Citiraj ovu publikaciju:

Klobučar, Damir; Subašić Marko
Using self-organizing maps in the visualization and analysis of forest inventory // iForest, 5 (2012), 216-223 doi:10.3832/ifor0629-005 (međunarodna recenzija, članak, znanstveni)
Klobučar, D. & Subašić Marko (2012) Using self-organizing maps in the visualization and analysis of forest inventory. iForest, 5, 216-223 doi:10.3832/ifor0629-005.
@article{article, author = {Klobu\v{c}ar, Damir}, year = {2012}, pages = {216-223}, DOI = {10.3832/ifor0629-005}, keywords = {forest inventory, stand structural parameters, self-organizing maps, forest data visualization, neural networks}, journal = {iForest}, doi = {10.3832/ifor0629-005}, volume = {5}, issn = {1971-7458}, title = {Using self-organizing maps in the visualization and analysis of forest inventory}, keyword = {forest inventory, stand structural parameters, self-organizing maps, forest data visualization, neural networks} }
@article{article, author = {Klobu\v{c}ar, Damir}, year = {2012}, pages = {216-223}, DOI = {10.3832/ifor0629-005}, keywords = {forest inventory, stand structural parameters, self-organizing maps, forest data visualization, neural networks}, journal = {iForest}, doi = {10.3832/ifor0629-005}, volume = {5}, issn = {1971-7458}, title = {Using self-organizing maps in the visualization and analysis of forest inventory}, keyword = {forest inventory, stand structural parameters, self-organizing maps, forest data visualization, neural networks} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus


Uključenost u ostale bibliografske baze podataka::


  • Journal Citation Reports - Science Edition
  • Scopus


Citati:





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