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Auteur C. Hendrix |
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A comparison of urban mapping methods using high-resolution digital imagery / N. Thomas in Photogrammetric Engineering & Remote Sensing, PERS, vol 69 n° 9 (September 2003)
[article]
Titre : A comparison of urban mapping methods using high-resolution digital imagery Type de document : Article/Communication Auteurs : N. Thomas, Auteur ; C. Hendrix, Auteur ; Russell G. Congalton, Auteur Année de publication : 2003 Article en page(s) : pp 963 - 972 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse comparative
[Termes IGN] Arizona (Etats-Unis)
[Termes IGN] cartographie urbaine
[Termes IGN] classification ascendante hiérarchique
[Termes IGN] classification dirigée
[Termes IGN] classification non dirigée
[Termes IGN] image à résolution métrique
[Termes IGN] image à très haute résolution
[Termes IGN] segmentation d'imageRésumé : (Auteur) Recent advances in digital airborne sensors and satellite platforms make spatially accurate, high-resolution multispectral imagery readily available. These advances provide the opportunity for a host of new applications to address and solve problems. High-resolution imagery is particularly well suited to urban applications. Previous data sources (such as Landsat TM) did not show the spatial detail necessary to provide many urban planning solutions. This paper provides an overview of a project in which one-meter digital imagery was used to produce a map of pervious and impervious surfaces to be used by the city of Scottsdale, Arizona for storm-water estimation. The increased spatial information in one-meter or less resolution imagery strains the usefulness of image classification using traditional supervised and unsupervised spectral classification algorithms. This study assesses the accuracy of three different methods for extracting land-cover/land-use information from high-resolution imagery of urban environments : (1) combined supervised/unsupervised spectral classification, (2) raster-based spatial modeling and (3) image segmentation classification using tree analysis. A discussion of the results and relative merits of each method is included. Numéro de notice : A2003-226 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.69.9.963 En ligne : https://doi.org/10.14358/PERS.69.9.963 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22521
in Photogrammetric Engineering & Remote Sensing, PERS > vol 69 n° 9 (September 2003) . - pp 963 - 972[article]