Multivariate classification of landscape metrics in multispectral digital images
Autor: | Jorge Lira, Sara Eugenia Cruz Morales |
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Rok vydání: | 2016 |
Předmět: |
Normalization (statistics)
010504 meteorology & atmospheric sciences Contextual image classification business.industry Computer science Multispectral image 0211 other engineering and technologies Pattern recognition 02 engineering and technology Image segmentation 01 natural sciences Fractal analysis Hierarchical clustering Metric (mathematics) Binary data General Earth and Planetary Sciences Artificial intelligence business 021101 geological & geomatics engineering 0105 earth and related environmental sciences |
Zdroj: | Journal of Applied Remote Sensing. 10:026039 |
ISSN: | 1931-3195 |
DOI: | 10.1117/1.jrs.10.026039 |
Popis: | The use of landscape metrics to characterize the morphological behavior of a landscape has been extensive in the last few years. It is recognized that a single metric is insufficient to characterize a landscape. Such metrics are used individually to derive the morphological aspect of a landscape. No joint use of various metrics has been reported. Therefore, we considered the joint use of landscape metrics in a multivariate classification. We derived the value of a number of landscape metrics of patches from several case studies. A multivariate classification was applied using a hierarchical clustering algorithm. The multivariate classification was carried out using the least correlated landscape metrics. To consider the multivariate classification, a normalization of metrics range was used. The results provided the morphological structure of patches grouped into four or five classes. The classes depicted a morphological structure of patches that ranged from simple to very complex. An index was proposed to quantify the morphological structure of a class-patch. Such an index was defined as the average of the landscape metrics for a class-patch. The distance among the class-patch was given by means of the Jeffries–Matusita distance. |
Databáze: | OpenAIRE |
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