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Wavelet for urban spatial feature discrimination: comparisons with fractal, spatial autocorrelation, and spatial co-occurrence approaches / Nina S-N Lam in Photogrammetric Engineering & Remote Sensing, PERS, vol 70 n° 7 (July 2004)

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 70 n° 7 (July 2004) . - pp 803 - 812 Titre : Wavelet for urban spatial feature discrimination: comparisons with fractal, spatial autocorrelation, and spatial co-occurrence approaches Type de document : Article/Communication Auteurs : Nina S-N Lam, Auteur ; S.W. Myint, Auteur ; J.M. Tyler, Auteur Année de publication : 2004 Article en page(s) : pp 803 - 812 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] analyse fractale [Termes descripteurs IGN] autocorrélation spatiale [Termes descripteurs IGN] classification dirigée [Termes descripteurs IGN] image multibande [Termes descripteurs IGN] matrice [Termes descripteurs IGN] milieu urbain [Termes descripteurs IGN] précision de la classification [Termes descripteurs IGN] transformation en ondelettes Résumé : (Auteur) Traditional image processing techniques have proven inadequate for urban mapping using high spatial resolution remote-sensing images. This study examined and evaluated wavelet transforms for urban texture analysis and image classification using high spatial resolution ATLAS imagery. For the purpose of comparison and to evaluate the effectiveness of the wavelet approaches, two different fractal approaches (isarithm and triangular prism), spatial autocorrelation (Moran's I and Geary's C), and spatial co-occurrence matrix of the selected urban classes were examined using 65 X 65, 33 X 33, and 17 X 17 samples with a pixel size of 2.5 m. Results from this study suggest that a multi-band and multi-level wavelet approach can be used to drastically increase the classification accuracy. The fractal techniques did not provide satisfactory classification accuracy. Spatial autocorrelation and spatial co-occurrence techniques were found to be relatively effective when compared to the fractal approaches. It can be concluded that the wavelet transform approach is the most accurate of all four approaches. Numéro de notice : A2004-273 Thématique : IMAGERIE Nature : Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26800 [article]

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A split model for extraction of subpixel impervious surface information / Y. Wang in Photogrammetric Engineering & Remote Sensing, PERS, vol 70 n° 7 (July 2004)

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 70 n° 7 (July 2004) . - pp 821 - 828 Titre : A split model for extraction of subpixel impervious surface information Type de document : Article/Communication Auteurs : Y. Wang, Auteur ; X. Zhang, Auteur Année de publication : 2004 Article en page(s) : pp 821 - 828 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] banlieue [Termes descripteurs IGN] classification par réseau neuronal [Termes descripteurs IGN] données multicapteurs [Termes descripteurs IGN] image Landsat-TM [Termes descripteurs IGN] milieu urbain [Termes descripteurs IGN] réseau neuronal artificiel [Termes descripteurs IGN] surface imperméable [Termes descripteurs IGN] valeur radiométrique Résumé : (Auteur) This paper introduces a Subpixel Proportional Land cover Information Transformation (SPLIT) model to extract proportions of impervious surfaces in urban and suburban areas. High spatial resolution airborne Digital Multispectral Videography (Dmsv) data provided subpixel information for Landsat TM data. The SPLIT model employed a Modularized Artificial Neural Network (MANN) to integrate multi-sensor remote sensing data and to extract proportions of impervious surfaces and other types of land cover within TM pixels. Through a control unit, the MANN was able to decompose a complex task into multiple subtasks by using a group of sub-networks. The SPLIT model identified spectral relations between TM pixel values and the corresponding DMSV subpixel patterns. The established relationship allows extrapolation of the SPLIT model to the areas beyond DMSV data coverage. We applied five intervals, i.e., 81 percent, to map the subpixel proportions of land cover types. We extrapolated the SPLIT model from training sites that have both TM and DMSV coverage into the entire DuPage County with TM data as the input. The extrapolation received 82.9 percent overall accuracyfor the extracted proportions of urban impervious surface. Numéro de notice : A2004-274 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26801 [article]

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Mobile GIS and speech recognition / A. Hunter in Photogrammetric Engineering & Remote Sensing, PERS, vol 70 n° 7 (July 2004)

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 70 n° 7 (July 2004) . - pp 851 - 860 Titre : Mobile GIS and speech recognition Type de document : Article/Communication Auteurs : A. Hunter, Auteur ; Naser El-Sheimy, Auteur Année de publication : 2004 Article en page(s) : pp 851 - 860 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes descripteurs IGN] géopositionnement [Termes descripteurs IGN] GML [Termes descripteurs IGN] reconnaissance de la parole [Termes descripteurs IGN] saisie de données [Termes descripteurs IGN] SIG nomade [Termes descripteurs IGN] télécommunication sans fil [Termes descripteurs IGN] temps réel Résumé : (Auteur) The research investigated whether a Mobile Geographic Information System (MGIS) incorporating speech recognition was a viable tool for locating defects in the streetscape. The Geography Markup Language for encoding spatial information was used to implement an application schema for street condition surveys. Speech accuracy exceeded 95 % in environments that were quiet or constantly loud. However, for tests where the noise level varied, recognition accuracy plummeted to 58 percent. Accuracy of captured defects was determined while "standing", "walking", "cycling", and "driving". Errors ranged from 0.27 m to 12.49 m at the 95 percent confidence interval. A web-based questionnaire indicated that municipal geographic information users are unhappy with the quality of their data, and as yet, do not require data in real-time. Future research involves investigating alternative ways of capturing spoken commands, the effect that mobile computing has on the cognitive abilities of the user, and wireless connectivity required for real time access to spatial data. Numéro de notice : A2004-275 Thématique : GEOMATIQUE Nature : Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26802 [article]

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