59.pdf

URL: http://portal.igg.ac.mn/dataset/58dc0d61-0028-47e4-8065-f0f2648423b0/resource/97e582c6-e947-4d28-ba41-168d296e3f09/download/59.pdf

The aim of this study is to explore the performances of different data fusion techniques for the enhancement of urban features and evaluate the features obtained by the fusion techniques in terms of separation of different land cover classes. For the data fusion, multiplicative method, Brovey transform, principal component analysis (PCA), Gram-Schmidt fusion, wavelet-based fusion and Elhers fusion are used and the results are compared. Of these methods, the best result is obtained by the use of the wavelet-based fusion. Overall, the research indicates that multisource data sets can significantly improve the interpretation and analysis of land cover types.

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Data last updated February 3, 2020
Metadata last updated February 3, 2020
Created February 3, 2020
Format application/pdf
License Creative Commons Attribution
createdover 4 years ago
formatPDF
has viewsTrue
id97e582c6-e947-4d28-ba41-168d296e3f09
last modifiedover 4 years ago
mimetypeapplication/pdf
on same domainTrue
package id58dc0d61-0028-47e4-8065-f0f2648423b0
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size674.6 KiB
stateactive
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