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Titolo:
Accounting for spatial dependence in the processing of multi-temporal SAR images using factorial kriging
Autore:
Van Meirvenne, M; Goovaerts, P;
Indirizzi:
State Univ Ghent, Dept Soil Management & Soil Care, B-9000 Ghent, Belgium State Univ Ghent Ghent Belgium B-9000 & Soil Care, B-9000 Ghent, Belgium Univ Michigan, Dept Civil & Environm Engn, Ann Arbor, MI 48109 USA Univ Michigan Ann Arbor MI USA 48109 vironm Engn, Ann Arbor, MI 48109 USA
Titolo Testata:
INTERNATIONAL JOURNAL OF REMOTE SENSING
fascicolo: 2, volume: 23, anno: 2002,
pagine: 371 - 387
SICI:
0143-1161(200201)23:2<371:AFSDIT>2.0.ZU;2-B
Fonte:
ISI
Lingua:
ENG
Soggetto:
SOIL-MOISTURE; SOURCE AREAS;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Physical, Chemical & Earth Sciences
Citazioni:
26
Recensione:
Indirizzi per estratti:
Indirizzo: Van Meirvenne, M State Univ Ghent, Dept Soil Management & Soil Care, Coupure 653, B-9000 Ghent, Belgium State Univ Ghent Coupure 653 Ghent Belgium B-9000 elgium
Citazione:
M. Van Meirvenne e P. Goovaerts, "Accounting for spatial dependence in the processing of multi-temporal SAR images using factorial kriging", INT J REMOT, 23(2), 2002, pp. 371-387

Abstract

The interpretation or classification of multi-temporal satellite images that share large portions of redundant information can generally be improved by principal component analysis (PCA). A shortcoming of PCA is that the spatial structure of the images is ignored. Spatial variability often consistsof several nested levels of variance and their blending could mask information that is dominant at a specific level or spatial scale. Factorial kriging (FK) is a geostatistical technique that allows the filtering of spatial components identified from nested variograms and is here used to extract scale-dependent information from satellite images prior to PCA. The benefit of this geostatistical pre-processing of multitemporal images is investigated using a winter sequence of eight European Remote Sensing (ERS 1/2) Synthetic Aperture Radar (SAR) images. Each image was processed by FK to isolate the variation present at a 'regional' scale (between 289 and 700 m) prior to a PCA of the filtered images. Compared to an earlier study where PCA was performed on the original images, filtering enhanced the relation between the first three principal components and land characteristics associated with topography, soil drainage conditions and land use.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 10/04/20 alle ore 02:27:58