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Evaluating uniform manifold approximation and projection for dimension reduction and visualization of polinsar features

Schmitz, S.; Weidner, U.; Hammer, H.; Thiele, A.


In this paper, the nonlinear dimension reduction algorithm Uniform Manifold Approximation and Projection (UMAP) is investigated to visualize information contained in high dimensional feature representations of Polarimetric Interferometric Synthetic Aperture Radar (PolInSAR) data. Based on polarimetric parameters, target decomposition methods and interferometric coherences a wide range of features is extracted that spans the high dimensional feature space. UMAP is applied to determine a representation of the data in 2D and 3D euclidean space, preserving local and global structures of the data and still suited for classification. The performance of UMAP in terms of generating expressive visualizations is evaluated on PolInSAR data acquired by the F-SAR sensor and compared to that of Principal Component Analysis (PCA), Laplacian Eigenmaps (LE) and t-distributed Stochastic Neighbor embedding (t-SNE). For this purpose, a visual analysis of 2D embeddings is performed. In addition, a quantitative analysis is provided for evaluating the preservation of information in low dimensional representations with respect to separability of different land cover classes. ... mehr

Verlagsausgabe §
DOI: 10.5445/IR/1000140749
Veröffentlicht am 02.12.2021
DOI: 10.5194/isprs-annals-V-1-2021-39-2021
Zitationen: 2
Zitationen: 1
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Photogrammetrie und Fernerkundung (IPF)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2021
Sprache Englisch
Identifikator ISSN: 2194-9042
KITopen-ID: 1000140749
Erschienen in Volume V-1-2021, 2021 | XXIV ISPRS Congress Imaging today, foreseeing tomorrow, Commission I: 2021 edition, 5-9 July 2021. Ed.: N. Paparoditis
Veranstaltung 24th ISPRS Congress (2021), Online, 05.07.2021 – 09.07.2021
Verlag International Society for Photogrammetry and Remote Sensing (ISPRS)
Seiten 39-46
Serie ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences ; 5
Nachgewiesen in Dimensions
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