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Statistical data fusion of multi-sensor AOD over the Continental United States / Sweta Jinnagara Puttaswamy in Geocarto international, vol 29 n° 1 - 2 (February - April 2014)  

Public [article]  inGeocarto international > vol 29 n° 1 - 2 (February - April 2014) . - pp 48 - 64 Titre : Statistical data fusion of multi-sensor AOD over the Continental United States Type de document : Article/Communication Auteurs : Sweta Jinnagara Puttaswamy, Auteur ; Hai M. Nguyen, Auteur ; Amy Braverman, Auteur ; Xuefei Hu, Auteur ; Yang Liu, Auteur Année de publication : 2014 Article en page(s) : pp 48 - 64 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] aérosol [Termes IGN] données de terrain [Termes IGN] Etats-Unis [Termes IGN] fusion de données [Termes IGN] image GOES [Termes IGN] image Terra-MODIS [Termes IGN] interpolation linéaire [Termes IGN] krigeage [Termes IGN] profondeur Résumé : (Auteur) This article illustrates two techniques for merging daily aerosol optical depth (AOD) measurements from satellite and ground-based data sources to achieve optimal data quality and spatial coverage. The first technique is a traditional Universal Kriging (UK) approach employed to predict AOD from multi-sensor aerosol products that are aggregated on a reference grid with AERONET as ground truth. The second technique is spatial statistical data fusion (SSDF); a method designed for massive satellite data interpolation. Traditional kriging has computational complexity O(N3), making it impractical for large datasets. Our version of UK accommodates massive data inputs by performing kriging locally, while SSDF accommodates massive data inputs by modelling their covariance structure with a low-rank linear model. In this study, we use aerosol data products from two satellite instruments: the moderate resolution imaging spectrometer and the geostationary operational environmental satellite, covering the Continental United States. Numéro de notice : A2014-234 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2013.827750 Date de publication en ligne : 10/09/2013 En ligne : https://doi.org/10.1080/10106049.2013.827750 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=33137 [article]

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059-2014011	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Impervious surface area extraction from IKONOS imagery using an object-based fuzzy method / Xuefei Hu in Geocarto international, vol 26 n° 1 (February 2011)  

Public [article]  inGeocarto international > vol 26 n° 1 (February 2011) . - pp 3 - 20 Titre : Impervious surface area extraction from IKONOS imagery using an object-based fuzzy method Type de document : Article/Communication Auteurs : Xuefei Hu, Auteur ; Q. Weng, Auteur Année de publication : 2011 Article en page(s) : pp 3 - 20 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] classification floue [Termes IGN] détection d'objet [Termes IGN] extraction automatique [Termes IGN] image Ikonos [Termes IGN] image multibande [Termes IGN] Indianapolis [Termes IGN] logique floue [Termes IGN] milieu urbain [Termes IGN] pansharpening (fusion d'images) [Termes IGN] surface imperméable [Termes IGN] ville Résumé : (Auteur) The study of impervious surfaces is crucial to the sustainable development of urban areas due to its strong impact on urban environments. Remotely sensed high-resolution imagery has the advantage of providing more spatial details; however, digital image processing algorithms have not been well developed to accommodate this advantage and other characteristics of such imagery. In this article, an object-based fuzzy classification approach for impervious surface extraction was developed and applied to two pan-sharpened multi-spectral IKONOS images covering the residential and central business district (CBD) areas of Indianapolis, Indiana, USA. Fuzzy rules based on spectral, spatial and texture attributes, were developed to extract impervious surfaces. An accuracy assessment was performed for the final maps. The results indicated that the spatial patterns of extracted features were in accordance with those in the original images and the boundaries of features were appropriately delineated. Impervious surfaces were extracted with an accuracy of 95% in the residential area and 92% in the CBD area. Road extraction achieved accuracy a bit lower, with 93% and 90% from the residential and CBD area, respectively. Buildings were extracted with an accuracy of 94% from the residential area while 89% from the CBD area. It is suggested that the CBD area had a higher spectral complexity, building displacement and the shadow problem, leading to a more difficult estimation and mapping of impervious surfaces. Numéro de notice : A2011-034 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2010.535616 Date de publication en ligne : 01/10/2010 En ligne : https://doi.org/10.1080/10106049.2010.535616 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30815 [article]

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Code-barres	Cote	Support	Localisation	Section	Disponibilité
059-2011011	RAB	Revue	Centre de documentation	En réserve L003	Disponible