文化大學機構典藏 CCUR:Item 987654321/35391
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    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: https://irlib.pccu.edu.tw/handle/987654321/35391


    题名: Gap Shape Classification using Landscape Indices and Multivariate Statistics
    作者: Wu, CD (Wu, Chih-Da)
    Cheng, CC (Cheng, Chi-Chuan)
    Chang, CC (Chang, Che-Chang)
    Lin, C (Lin, Chinsu)
    Chang, KC (Chang, Kun-Cheng)
    Chuang, YC (Chuang, Yung-Chung)
    贡献者: 景觀系
    关键词: CANOPY GAPS
    SPECIES-DIVERSITY
    LONG-TERM
    FOREST
    GROWTH
    REGENERATION
    PATTERNS
    MORTALITY
    SEEDLINGS
    MODELS
    日期: 2016-11-30
    上传时间: 2017-02-13 10:28:44 (UTC+8)
    摘要: This study proposed a novel methodology to classify the shape of gaps using landscape indices and multivariate statistics. Patch-level indices were used to collect the qualified shape and spatial configuration characteristics for canopy gaps in the Lienhuachih Experimental Forest in Taiwan in 1998 and 2002. Non-hierarchical cluster analysis was used to assess the optimal number of gap clusters and canonical discriminant analysis was used to generate the discriminant functions for canopy gap classification. The gaps for the two periods were optimally classified into three categories. In general, gap type 1 had a more complex shape, gap type 2 was more elongated and gap type 3 had the largest gaps that were more regular in shape. The results were evaluated using Wilks' lambda as satisfactory (p < 0.001). The agreement rate of confusion matrices exceeded 96%. Differences in gap characteristics between the classified gap types that were determined using a one-way ANOVA showed a statistical significance in all patch indices (p = 0.00), except for the Euclidean nearest neighbor distance (ENN) in 2002. Taken together, these results demonstrated the feasibility and applicability of the proposed methodology to classify the shape of a gap.
    關聯: Scientific Reports 卷: 6 文獻號碼: 38217
    显示于类别:[景觀學系所] 期刊論文

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