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Application of Principal Component Analysis (PCA) in Taxonomy Research to Derive Plant Functional Types for Use in Dynamics Models

Forest management is essential for maintaining environmental stability and ecological biodiversity. The high species diversity of tropical rainforest forests obstructs the development of forest dynamic models. A lot of tree species exist in the forest for which each type of species will have insuffi...

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Main Authors: Yasmin Yahya, Roslan Ismail, (UniKL MIIT)
Format:
Published: ACM 2015
Subjects:
Principal component analysis (PCA)
cluster analysis (CA)
diversity
classification
Online Access:http://localhost/xmlui/handle/123456789/9717
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id my.unikl.ir-9717
record_format eprints
spelling my.unikl.ir-97172015-03-30T03:15:05Z Application of Principal Component Analysis (PCA) in Taxonomy Research to Derive Plant Functional Types for Use in Dynamics Models Yasmin Yahya Roslan Ismail (UniKL MIIT) Principal component analysis (PCA) cluster analysis (CA) diversity classification Forest management is essential for maintaining environmental stability and ecological biodiversity. The high species diversity of tropical rainforest forests obstructs the development of forest dynamic models. A lot of tree species exist in the forest for which each type of species will have insufficient data for reliable parameter estimation. The best way to avoid bias prediction is to group the trees based on their characteristics similarity. In a tropical rain forest in Koh Kong province, Cambodia, four species groups have been classified using statistical analyses of principal component analysis (PCA) and cluster analysis. Some indices related to diameter structure, growth, mortality and recruitment of species were formed from measurement data rather than the parameter estimates of some predetermined growth regression functions. 2015-03-30T03:15:05Z 2015-03-30T03:15:05Z 2015-01 Yasmin Yahya and Roslan Ismail. 2015. Application of principal component analysis (PCA) in taxonomy research to derive plant functional types for use in dynamics models. In Proceedings of the 9th International Conference on Ubiquitous Information Management and Communication (IMCOM '15). ACM, New York, NY, USA, , Article 14 , 6 pages. DOI=10.1145/2701126.2701166 http://doi.acm.org/10.1145/2701126.2701166 978-1-4503-3377-1 http://localhost/xmlui/handle/123456789/9717 ACM
institution Universiti Kuala Lumpur
building UniKL Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Kuala Lumpur
content_source UniKL Institutional Repository
url_provider http://ir.unikl.edu.my/
topic Principal component analysis (PCA)
cluster analysis (CA)
diversity
classification
spellingShingle Principal component analysis (PCA)
cluster analysis (CA)
diversity
classification
Yasmin Yahya
Roslan Ismail
(UniKL MIIT)
Application of Principal Component Analysis (PCA) in Taxonomy Research to Derive Plant Functional Types for Use in Dynamics Models
description Forest management is essential for maintaining environmental stability and ecological biodiversity. The high species diversity of tropical rainforest forests obstructs the development of forest dynamic models. A lot of tree species exist in the forest for which each type of species will have insufficient data for reliable parameter estimation. The best way to avoid bias prediction is to group the trees based on their characteristics similarity. In a tropical rain forest in Koh Kong province, Cambodia, four species groups have been classified using statistical analyses of principal component analysis (PCA) and cluster analysis. Some indices related to diameter structure, growth, mortality and recruitment of species were formed from measurement data rather than the parameter estimates of some predetermined growth regression functions.
format
author Yasmin Yahya
Roslan Ismail
(UniKL MIIT)
author_facet Yasmin Yahya
Roslan Ismail
(UniKL MIIT)
author_sort Yasmin Yahya
title Application of Principal Component Analysis (PCA) in Taxonomy Research to Derive Plant Functional Types for Use in Dynamics Models
title_short Application of Principal Component Analysis (PCA) in Taxonomy Research to Derive Plant Functional Types for Use in Dynamics Models
title_full Application of Principal Component Analysis (PCA) in Taxonomy Research to Derive Plant Functional Types for Use in Dynamics Models
title_fullStr Application of Principal Component Analysis (PCA) in Taxonomy Research to Derive Plant Functional Types for Use in Dynamics Models
title_full_unstemmed Application of Principal Component Analysis (PCA) in Taxonomy Research to Derive Plant Functional Types for Use in Dynamics Models
title_sort application of principal component analysis (pca) in taxonomy research to derive plant functional types for use in dynamics models
publisher ACM
publishDate 2015
url http://localhost/xmlui/handle/123456789/9717
_version_ 1644485128498446336
score 13.214268

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