Dr. Jorge Lira Profile

Dr. Jorge Lira

at UNAM

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SPIE Journal Paper | 28 June 2016

Multivariate classification of landscape metrics in multispectral digital images

Jorge Lira, Sara Morales

JARS, Vol. 10, Issue 02, 026039, (June 2016) https://doi.org/10.1117/12.10.1117/1.JRS.10.026039

KEYWORDS: Earth observing sensors, Image classification, Multispectral imaging, Image segmentation, Agriculture, Fractal analysis, Binary data, Image filtering, MATLAB, Vegetation

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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.

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