Photogrammetric Engineering & Remote Sensing, PERS / American society for photogrammetry and remote sensing . vol 74 n° 4Paru le : 01/04/2008 ISBN/ISSN/EAN : 0099-1112 |
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Ajouter le résultat dans votre panierSize-Constrained Region Merging (SCRM): an automated delineation tool for assisted photointerpretation / G. Castilla in Photogrammetric Engineering & Remote Sensing, PERS, vol 74 n° 4 (April 2008)
[article]
Titre : Size-Constrained Region Merging (SCRM): an automated delineation tool for assisted photointerpretation Type de document : Article/Communication Auteurs : G. Castilla, Auteur ; G. Hay, Auteur ; J. Ruiz-Gallardo, Auteur Année de publication : 2008 Article en page(s) : pp 409 - 419 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photo-interprétation
[Termes IGN] carte d'occupation du sol
[Termes IGN] contrainte géométrique
[Termes IGN] détection de contours
[Termes IGN] fusion de données
[Termes IGN] photo-identification
[Termes IGN] photo-interprétation assistée par ordinateur
[Termes IGN] traitement d'imageRésumé : (Auteur) The manual delineation of vegetation patches or forest stands is a costly and crucial stage in any land-cover mapping project or forest inventory based upon photointerpretation. Recent computer techniques have eased the task of the interpreter; however, a good deal of craftsmanship is still required in the delineation. In an effort to contribute to the automation of this process, we introduce Size-Constrained Region Merging (SCRM), a recently implemented software tool that provides the interpreter with an initial template of the to be mapped area that may reduce the manual digitization portion of the interpretation. In essence, SCRM transforms an ortho-rectified aerial or satellite image (single or multichannel) into a polygon vector layer that resembles the work of a human interpreter, whom with no a priori knowledge of the scene, was given the task of partitioning the image into a number of homogeneous polygons all exceeding a minimum size. We provide background information on SCRM foundations and workflow, and illustrate its application on three different types of satellite images. Copyright ASPRS Numéro de notice : A2008-121 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.74.4.409 En ligne : https://doi.org/10.14358/PERS.74.4.409 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29116
in Photogrammetric Engineering & Remote Sensing, PERS > vol 74 n° 4 (April 2008) . - pp 409 - 419[article]Reducing edge effects in the classification of high resolution imagery / Guiyun Zhou in Photogrammetric Engineering & Remote Sensing, PERS, vol 74 n° 4 (April 2008)
[article]
Titre : Reducing edge effects in the classification of high resolution imagery Type de document : Article/Communication Auteurs : Guiyun Zhou, Auteur ; Nina S.-N. Lam, Auteur Année de publication : 2008 Article en page(s) : pp 431 - 441 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse texturale
[Termes IGN] contour
[Termes IGN] fenêtre (informatique)
[Termes IGN] image à haute résolution
[Termes IGN] polygone
[Termes IGN] précision géométrique (imagerie)Résumé : (Auteur) Edge effects have been a problem in image classification especially when scale-based textural methods were included in the classification process. This paper proposes a new approach to reducing edge effects. The essence of the new approach is that all pixels in a moving window make use of the textural information instead of only the center pixel as in the traditional moving window method. The performance of the new approach was tested in three classification scenarios. The results show that the new approach generally produced higher accuracy with larger window size and was much less affected by the edge issues than the traditional moving window method. The new approach yields satisfactory results as long as the window size is smaller than the land-use polygons and the class boundaries are not too complex. Copyright ASPRS Numéro de notice : A2008-122 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.74.4.431 En ligne : https://doi.org/10.14358/PERS.74.4.431 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29117
in Photogrammetric Engineering & Remote Sensing, PERS > vol 74 n° 4 (April 2008) . - pp 431 - 441[article]Per-pixel classification of high spatial resolution satellite imagery for urban land-cover mapping / D. Hester in Photogrammetric Engineering & Remote Sensing, PERS, vol 74 n° 4 (April 2008)
[article]
Titre : Per-pixel classification of high spatial resolution satellite imagery for urban land-cover mapping Type de document : Article/Communication Auteurs : D. Hester, Auteur ; H. Cakir, Auteur ; et al., Auteur Année de publication : 2008 Article en page(s) : pp 463 - 471 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] Caroline du Nord (Etats-Unis)
[Termes IGN] carte d'occupation du sol
[Termes IGN] cartographie urbaine
[Termes IGN] classification pixellaire
[Termes IGN] erreur de classification
[Termes IGN] image à très haute résolution
[Termes IGN] image Quickbird
[Termes IGN] précision géométrique (imagerie)Résumé : (Auteur) Commercial high spatial resolution satellite data now provide a synoptic and consistent source of digital imagery with detail comparable to that of aerial photography. In the work described here, per-pixel classification, image fusion, and GIS-based map refinement techniques were tailored to pan-sharpened 0.61 m QuickBird imagery to develop a six-category urban land-cover map with 89.3 percent overall accuracy (k = 0.87). The study area was a rapidly developing 71.5 km2 part of suburban Raleigh, North Carolina, U.S.A., within the Neuse River basin. “Edge pixels” were a source of classification error as was spectral overlap between bare soil and impervious surfaces and among vegetated cover types. Shadows were not a significant source of classification error. These findings demonstrate that conventional spectral-based classification methods can be used to generate highly accurate maps of urban landscapes using high spatial resolution imagery. Copyright ASPRS Numéro de notice : A2008-123 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.74.4.463 En ligne : https://doi.org/10.14358/PERS.74.4.463 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29118
in Photogrammetric Engineering & Remote Sensing, PERS > vol 74 n° 4 (April 2008) . - pp 463 - 471[article]