Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Quantification of similarity between land cover categories
The transformation from forest and rural to developed land is growing dramatically worldwide. A measure of the underlying structure of this shift is needed to better understand the nature of this change and to be able to establish control mechanisms at a regional scale. Landscape metrics evaluate the morphology of the spatial pattern at the object level (patch) through the categorization of Land Cover, generally without considering the similarities or dissimilarities between categories in the classification. This work uses the Mean Edge Contrast Index (MECI) to quantify the structure of the counties around Columbus, OH. This index doesn’t make a hard distinction between categories, since it uses a matrix that assigns a value to the contrast between each Land Cover class pairwise, and measures the degree of contrast between each patch and its immediate neighborhood. The values of the matrix are obtained through the comparison of MECI and a studied variable, obtaining a measure of the similarity or dissimilarity of each class that better explains each variable. These relationships are visualized with different techniques to better understand their similarities. ; Peer Reviewed
Quantification of similarity between land cover categories
The transformation from forest and rural to developed land is growing dramatically worldwide. A measure of the underlying structure of this shift is needed to better understand the nature of this change and to be able to establish control mechanisms at a regional scale. Landscape metrics evaluate the morphology of the spatial pattern at the object level (patch) through the categorization of Land Cover, generally without considering the similarities or dissimilarities between categories in the classification. This work uses the Mean Edge Contrast Index (MECI) to quantify the structure of the counties around Columbus, OH. This index doesn’t make a hard distinction between categories, since it uses a matrix that assigns a value to the contrast between each Land Cover class pairwise, and measures the degree of contrast between each patch and its immediate neighborhood. The values of the matrix are obtained through the comparison of MECI and a studied variable, obtaining a measure of the similarity or dissimilarity of each class that better explains each variable. These relationships are visualized with different techniques to better understand their similarities. ; Peer Reviewed
Quantification of similarity between land cover categories
Valls Dalmau, Francesc (Autor:in) / Roca Cladera, Josep (Autor:in)
01.10.2012
Sonstige
Elektronische Ressource
Englisch
Cities and towns -- Ohio -- Columbus -- Growth , Spatial Pattern Analysis , Desenvolupament urbà -- Estats Units d'Amèrica -- Columbus , Sòl , Data Visualization , Sistemes d'informació geogràfica , Àrees temàtiques de la UPC::Urbanisme , Sprawl , Urban -- Ohio -- Columbus , Edge Contrast , Ús urbà del -- Estats Units d'Amèrica -- Columbus , Machine Learning , Land use , Geographic information systems
DDC:
710
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