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Titre du document / Document title

Consequences of spatial resolution transformations for land-use classification

Auteur(s) / Author(s)

FEHRENBACH U. (1) ; SCHERER D. (1) ;

Affiliation(s) du ou des auteurs / Author(s) Affiliation(s)

(1) MCR Laboratory, University of Basel, SUISSE

Résumé / Abstract

This paper presents consequences of spatial resolution transformations of input data sets for the classification of areal types and ventilation situations. Areal types are aggregated land-use units determined from areal percentages of pixel classes resulting from maximum-likelihood classifications of Landsat-5 TM and ERS-1 SAR imagery. Spatial resolution of pixel classes is 30 m, while areal percentages were computed for different spatial resolutions between 25 and 1'000 m. Ventilation situations are numerical representatives of the most relevant ventilation conditions, and are classified from land-use and terrain parameters. Areal percentages and digital terrain models with corresponding spatial resolutions were used to derive these input parameters. All input data sets show significant changes for different spatial resolutions effecting spatial distributions and total areas of the resulting areal types and ventilation situations. The paper discusses these effects focussing on the satellite-based data sets. The necessity of adequate spatial resolutions for urban and regional planning applications of remote sensing data could be demonstrated by this study.

Source / Source

Congrès
Remote sensing in the 21st century : economic and environmental applications :   ( Valladolid, 31 May - 2 June 1999 )
EARSeL symposium on remote sensing in the 21st century No19, Vallodolid , ESPAGNE (31/05/1999)
2000  , pp. 113-117[Note(s) : XIV, 610 p., ] (13 ref.) ISBN 90-5809-096-5 ;  Illustration : Illustration ;

Langue / Language

Anglais

Editeur / Publisher

Balkema, Rotterdam, PAYS-BAS  (2000) (Monographie)

Mots-clés anglais / English Keywords

Space remote sensing

;

synthetic aperture radar

;

transformations

;

classification

;

Thematic Mapper

;

Landsat

;

maximum likelihood

;

land use

;

digital terrain models

;

spatial distribution

;

Mots-clés français / French Keywords

Télédétection spatiale

;

Radar antenne synthétique

;

Transformation

;

Classification

;

Thematic Mapper

;

LANDSAT

;

Maximum vraisemblance

;

Utilisation terrain

;

Modèle numérique terrain

;

Distribution spatiale

;

ERS-1

;

Radar ouverture synthétique

;

Radar synthèse ouverture

;

Ventilation

;

Mots-clés espagnols / Spanish Keywords

Teledetección espacial

;

Transformación

;

Clasificación

;

Utilización terreno

;

Distribución espacial

;

Localisation / Location

INIST-CNRS, Cote INIST : Y 32607, 35400008005788.0190

Nº notice refdoc (ud4) : 1370270



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