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Interpolating atmospheric water vapor delay by incorporating terrain elevation information / B. Xu in Journal of geodesy, vol 85 n° 9 (September 2011)  

Public [article]  inJournal of geodesy > vol 85 n° 9 (September 2011) . - pp 555 - 564 Titre : Interpolating atmospheric water vapor delay by incorporating terrain elevation information Type de document : Article/Communication Auteurs : B. Xu, Auteur ; Z.W. Li, Auteur ; J. Zhu, Auteur Année de publication : 2011 Article en page(s) : pp 555 - 564 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement du signal [Termes IGN] dégradation du signal [Termes IGN] écho radar [Termes IGN] interféromètrie par radar à antenne synthétique [Termes IGN] interpolation spatiale [Termes IGN] modèle numérique de surface [Termes IGN] propagation du signal [Termes IGN] signal GPS [Termes IGN] vapeur d'eau Résumé : (Auteur) In radio signal-based observing systems, such as Global Positioning System (GPS) and Interferometric Synthetic Aperture Radar (InSAR), the water vapor in the atmosphere will cause delays during the signal transmission. Such delays vary significantly with terrain elevation. In the case when atmospheric delays are to be eliminated from the measured raw signals, spatial interpolators may be needed. By taking advantage of available terrain elevation information during spatial interpolation process, the accuracy of the atmospheric delay mapping can be considerably improved. This paper first reviews three elevation-dependent water vapor interpolation models, i.e., the Best Linear Unbiased Estimator in combination with the water vapor Height Scaling Model (BLUE + HSM), the Best Linear Unbiased Estimator coupled with the Elevation-dependent Covariance Model (BLUE + ECM), and the Simple Kriging with varying local means based on the Baby semi-empirical model (SKlm + Baby for short). A revision to the SKlm + Baby model is then presented, where the Onn water vapor delay model is adopted to substitute the inaccurate Baby semi-empirical model (SKlm + Onn for short). Experiments with the zenith wet delays obtained through the GPS observations from the Southern California Integrated GPS Network (SCIGN) demonstrate that the SKlm + Onn model outperforms the other three. The RMS of SKlm + Onn is only 0.55 cm, while those of BLUE + HSM, BLUE + ECM and SKlm + Baby amount to 1.11, 1.49 and 0.77 cm, respectively. The proposed SKlm + Onn model therefore represents an improvement of 29–63% over the other known models. Numéro de notice : A2011-374 Affiliation des auteurs : non IGN Thématique : IMAGERIE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-011-0456-0 date de publication en ligne : 08/03/2011 En ligne : https://doi.org/10.1007/s00190-011-0456-0 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31153 [article]

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Urban land-use classification using variogram-based analysis with an aerial photograph / S.S. Wu in Photogrammetric Engineering & Remote Sensing, PERS, vol 72 n° 7 (July 2006)

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 72 n° 7 (July 2006) . - pp 813 - 822 Titre : Urban land-use classification using variogram-based analysis with an aerial photograph Type de document : Article/Communication Auteurs : S.S. Wu, Auteur ; B. Xu, Auteur ; L. Wang, Auteur Année de publication : 2006 Article en page(s) : pp 813 - 822 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] analyse texturale [Termes IGN] bati [Termes IGN] classification dirigée [Termes IGN] classification spectrale [Termes IGN] Kappa de Cohen [Termes IGN] milieu urbain [Termes IGN] photographie aérienne [Termes IGN] photographie infrarouge couleur [Termes IGN] utilisation du sol [Termes IGN] variogramme [Termes IGN] zone urbaine Résumé : (Auteur) In this study, a variogram-based texture analysis was tested for classifying detailed urban land-use classes, such as mobile home, single-family house, multi-family house, industrial, and commercial from a digital color infrared aerial photograph. Spectral classification was first carried out to separate the building class from non-building classes. Then, a building-presence binary image was generated so that building pixels were assigned a value of "1 " and non-building pixels were assigned a value of "0. " Multiple texture bands were further generated employing a variogram-based texture analysis and used for land-use classification. The generation of the building presence binary image allowed us not only to fully explore the capability of variogram-based analysis on spatial pattern detection, but also to prevent the variogram-based analysis from being disturbed by the natural fluctuation of spectral signals. The result from using a mosaic test image was considered satisfactory with a kappa coefficient of 0.72. Copyright ASPRS Numéro de notice : A2006-264 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27991 [article]

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Comparison of gray-level reduction and different texture spectrum encoding methods for land-use classification using a panchromatic Ikonos image / B. Xu in Photogrammetric Engineering & Remote Sensing, PERS, vol 69 n° 5 (May 2003)

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 69 n° 5 (May 2003) . - pp 529 - 536 Titre : Comparison of gray-level reduction and different texture spectrum encoding methods for land-use classification using a panchromatic Ikonos image Type de document : Article/Communication Auteurs : B. Xu, Auteur ; E. Seto, Auteur ; P. Gong, Auteur ; R. Spear, Auteur Année de publication : 2003 Article en page(s) : pp 529 - 536 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse spectrale [Termes IGN] analyse texturale [Termes IGN] classification contextuelle [Termes IGN] compression d'image [Termes IGN] image à résolution métrique [Termes IGN] image Ikonos [Termes IGN] image panchromatique [Termes IGN] niveau de gris (image) [Termes IGN] texture d'image [Termes IGN] uniformisation d'histogramme [Termes IGN] utilisation du sol Résumé : (Auteur) In this paper, we evaluate the potential of a frequency-based contextual classifier (FBC) for landuse classification with a panchromatic Ikonos image. To capture the spatial arrangement of image graylevel values and use such information in image classification, we applied texture spectrum (TS) directly in the FBC. The effects of several data preprocessing and reduction methods on the performance of the FBC are also evaluated. The methods include four graylevel reduction (GLR) techniques and several modifications to the TS technique. The purpose of data reduction is to improve the classification efficiency of the FBC. The GLR schemes were minmax linear compression (LC), gray level binning (BN), histogram equalization (HE), and piecewise nonlinear compression (PC). Instead of using the texture measures derived from the texture spectrum, we directly applied texture spectra of various sizes in the classification. We modified the encoding algorithm in the TS and were able to reduce the number of texture units from its original 6561 to 256, 81, and 16, leading to as much as a 410 times computation efficiency. The original image and GLR images were subsequently classified with the FBC. We compared the classification accuracies and found that the GLR methods resulted in accuracies similar to that of the original image (within 0.03 kappa value). There was little difference in classification accuracy (within 0.03 kappa value) among the three modified TS methods, which were all outperformed by the original TS method. All TS methods performed considerably better than the use of the original image and the GLR methods. Numéro de notice : A2003-083 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22379 [article]

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