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Estuarine shoreline change detection using Japanese ALOS PALSAR HH and JERS-1 L-HH SAR data in the Albemarle-Pamlico Sounds, North Carolina, USA / Y. Wang in International Journal of Remote Sensing IJRS, vol 29 n° 15-16 (August 2008)  

Public [article]  inInternational Journal of Remote Sensing IJRS > vol 29 n° 15-16 (August 2008) . - pp 4429 - 4442 Titre : Estuarine shoreline change detection using Japanese ALOS PALSAR HH and JERS-1 L-HH SAR data in the Albemarle-Pamlico Sounds, North Carolina, USA Type de document : Article/Communication Auteurs : Y. Wang, Auteur ; T. Allen, Auteur Année de publication : 2008 Article en page(s) : pp 4429 - 4442 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] analyse diachronique [Termes IGN] bande L [Termes IGN] Caroline du Nord (Etats-Unis) [Termes IGN] détection de changement [Termes IGN] données polarimétriques [Termes IGN] érosion côtière [Termes IGN] estuaire [Termes IGN] image ALOS-PALSAR [Termes IGN] image JERS [Termes IGN] polarimétrie radar [Termes IGN] trait de côte Résumé : (Auteur) An edge extraction model has been developed that uses multitemporal satellite synthetic aperture radar data to delineate shorelines in estuaries. Using Japanese ALOS PALSAR HH data acquired in December 2006 and JERS-1 L-HH SAR data in December 1994, we mapped shorelines of the outer Pamlico Peninsula, Dare County, North Carolina, USA, spanning 12 years. To assess the validity and accuracy of the delineation, we compared (a) 1994 shorelines versus those derived from the 1993 digital orthophotographs, and (b) 2006 shorelines versus field data collected in February 2007. With promising results, we then analysed and quantified the shoreline changes between 1994 and 2006 on the north, east, and south sides of the Peninsula. Virtually no discernible changes on the north and south sides were found. However, significant landward migration in the middle to southern portion on the east shore was observed. Spatial retreat of shorelines varied greatly, with the maximum rate averaged over a span of 12 years exceeding 11 m year?-1? The results support further monitoring of shorelines in estuaries using active remote sensing and the potential for the methodology developed to identify erosional hotspots. Copyright Taylor & Francis Numéro de notice : A2008-528 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160801932525 En ligne : https://doi.org/10.1080/01431160801932525 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29598 [article]

Integration of multitemporal/polarization C-band SAR data sets for land-cover classification / N. Park in International Journal of Remote Sensing IJRS, vol 29 n° 15-16 (August 2008)  

Public [article]  inInternational Journal of Remote Sensing IJRS > vol 29 n° 15-16 (August 2008) . - pp 4667 - 4688 Titre : Integration of multitemporal/polarization C-band SAR data sets for land-cover classification Type de document : Article/Communication Auteurs : N. Park, Auteur ; K.H. Chi, Auteur Année de publication : 2008 Article en page(s) : pp 4667 - 4688 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] analyse en composantes principales [Termes IGN] angle d'incidence [Termes IGN] bande C [Termes IGN] carte agricole [Termes IGN] image Envisat-ASAR [Termes IGN] image radar [Termes IGN] image Radarsat [Termes IGN] intégration de données [Termes IGN] occupation du sol [Termes IGN] polarimétrie radar Résumé : (Auteur) This paper investigates the potential of multitemporal/polarization C-band SAR data for land-cover classification. Multitemporal Radarsat-1 data with HH polarization and ENVISAT ASAR data with VV polarization acquired in the Yedang plain, Korea are used for the classification of typical five land-cover classes in an agricultural area. The presented methodologies consist of two analytical stages: one for feature extraction and the other for classification based on the combination of features. Both a traditional SAR signal property analysis-based approach and principal-component analysis (PCA) are applied in the feature extraction stage. Special concerns are in the interpretation of each principal component by using principal-component loading. The tau model applied as a decision-level fusion methodology can provide a formal framework in which the posteriori probabilities derived from different sensor data can be combined. From the case study results, the combination of PCA-based features showed improved classification accuracy for both Radarsat-1 and ENVISAT ASAR data, as compared with the traditional SAR signal property analysis-based approach. The integration of PCA-based features based on multiple polarization (i.e. HH from Radarsat-1, and both VV and VH from ENVISAT ASAR) and different incidence angles contributed to a significant improvement of discrimination capability for dry fields which could not be properly classified by using only Radarsat-1 or ENVISAT ASAR data, and thus showed the best classification accuracy. The results of this case study indicate that the use of multiple polarization SAR data with a proper feature extraction stage would improve classification accuracy in multitemporal SAR data classification, although further consideration should be given to the polarization and incidence angle dependency of complex land-cover classes through more experiments. Numéro de notice : A2008-530 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160801947341 En ligne : https://doi.org/10.1080/01431160801947341 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29600 [article]