|Table of Contents|

Optimization of Divisional Methods Based on Principal Composition Cluster Analysis on Suitable Ecological Region for Introduced Pinus ponderosa(PDF)

《北方园艺》[ISSN:1001-0009/CN:23-1247/S]

Issue:
2012年18期
Page:
92-95
Research Field:
Publishing date:

Info

Title:
Optimization of Divisional Methods Based on Principal Composition Cluster Analysis on Suitable Ecological Region for Introduced Pinus ponderosa
Author(s):
WANG Rong-fanTANG De-rui
College of Forestry,Northwest Agriculture and Forestry University,Yangling,Shaanxi 712100
Keywords:
Pinus ponderosaintroductionprincipal component analysiscluster analysis
PACS:
S 722.7
DOI:
-
Abstract:
Principal component analysis and cluster analysis were used to study 12 climate indicators of Pinus ponderosa in 42 places in China, such as annual average temperature, temperature in the hottest and coldest month, extreme maximum and minimum temperature, ≥10℃ accumulated temperature, frost-free period, average annual rainfall and evaporation, the average wind speed, the average wind speed and annual sunshine hours and average altitude. They were divided into 4 types, the most suitable area, suitable area, sub-suitable area and unsuitable area, and comparisons were made among two analytic methods combined with the actual growth of Pinus ponderosa. The results showed that the principal component-cluster analysis not only can classify multivariate data, but also is able to make a comprehensive evaluation; it correctly reflects the most suitable areas for Pinus ponderosa. After testing by the actual growth of Pinus ponderosa, we confirm the method was practicable.

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Last Update: 2014-08-29