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Record #204448:

Comparing matrix distance measures for unsupervised POLSAR data of sea ice based on agglomerative clustering / Mohammed Dabboor, and 3 others.

Title: Comparing matrix distance measures for unsupervised POLSAR data of sea ice based on agglomerative clustering / Mohammed Dabboor, and 3 others.
Author(s): Dabboor, Mohammed.
Date: 2013.
In: International Journal of Remote Sensing. (2013.), Vol. 34(4) (2013)
Abstract: Uses agglomerative clustering of RADARSAT-2 POLSAR data over sea ice in Hudson Bay (offshore Churchill) to compare six matrix distance measures: Manhattan (l₁ metric), Euclidean (l₂ metric), Bartlett, revised Wishart, Wishart test statistic, and Wishart Chernoff. Uses measures separately as similarity criteria for hierarchical merging of clusters into appropriate number of classes (based on log-likelihood algorithm). Compares evaluated appropriate numbers of classes and classification results for each distance measure. Sections describe theoretical background of distance measures; implementation of agglomerative clustering based on these; classification results. Concludes that Bartlett, revised Wishart and Wishart Chernoff distances produced most accurate classifications.
Notes:

International Journal of Remote Sensing. Vol. 34(4) :1492-1505 (2013).

Keywords: 551.32 -- Glaciology.
53.087.23 -- Remote sensing.
551.326.7 -- Sea ice.
551.326.021 -- Floating ice, satellite sensing.
519.2 -- Statistical methods.
621.396.96 -- Radar.
E10 -- Glaciology: snow and avalanches.
(*623) -- Hudson Bay.
SPRI record no.: 204448

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100 1# ‡aDabboor, Mohammed.
245 10 ‡aComparing matrix distance measures for unsupervised POLSAR data of sea ice based on agglomerative clustering /‡cMohammed Dabboor, and 3 others.
260 ## ‡a[S.l.] :‡b[s.n.],‡c2013.
300 ## ‡ap. 1492-1505 :‡bill., diags., tables, maps.
500 ## ‡aInternational Journal of Remote Sensing. Vol. 34(4) :1492-1505 (2013).
520 3# ‡aUses agglomerative clustering of RADARSAT-2 POLSAR data over sea ice in Hudson Bay (offshore Churchill) to compare six matrix distance measures: Manhattan (l₁ metric), Euclidean (l₂ metric), Bartlett, revised Wishart, Wishart test statistic, and Wishart Chernoff. Uses measures separately as similarity criteria for hierarchical merging of clusters into appropriate number of classes (based on log-likelihood algorithm). Compares evaluated appropriate numbers of classes and classification results for each distance measure. Sections describe theoretical background of distance measures; implementation of agglomerative clustering based on these; classification results. Concludes that Bartlett, revised Wishart and Wishart Chernoff distances produced most accurate classifications.
530 ## ‡aAlso issued online ‡uurn:doi:10.1080/01431161.2012.727040‡uhttps://dx.doi.org/10.1080/01431161.2012.727040
650 07 ‡a551.32 -- Glaciology.‡2udc
650 07 ‡a53.087.23 -- Remote sensing.‡2udc
650 07 ‡a551.326.7 -- Sea ice.‡2udc
650 07 ‡a551.326.021 -- Floating ice, satellite sensing.‡2udc
650 07 ‡a519.2 -- Statistical methods.‡2udc
650 07 ‡a621.396.96 -- Radar.‡2udc
650 07 ‡aE10 -- Glaciology: snow and avalanches.‡2local
651 #7 ‡a(*623) -- Hudson Bay.‡2udc
773 0# ‡7nnas ‡tInternational Journal of Remote Sensing. ‡gVol. 34(4) (2013) ‡wSPRI-1038
916 ## ‡a2013/09/18 -- RF
917 ## ‡aUnenhanced record from Muscat, imported 2019
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