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Complexity metrics to quantify semantic accuracy in segmented Landsat images / Alfred Stein in International Journal of Remote Sensing IJRS, vol 26 n° 14 (July 2005)
[article]
Titre : Complexity metrics to quantify semantic accuracy in segmented Landsat images Type de document : Article/Communication Auteurs : Alfred Stein, Auteur ; K. De Beurs, Auteur Année de publication : 2005 Article en page(s) : pp 2937 - 2951 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] agriculture
[Termes IGN] agriculture de précision
[Termes IGN] analyse comparative
[Termes IGN] classification
[Termes IGN] image Landsat
[Termes IGN] Kazakhstan
[Termes IGN] milieu rural
[Termes IGN] Pays-Bas
[Termes IGN] précision sémantique
[Termes IGN] segmentation d'image
[Termes IGN] spatial metricsRésumé : (Auteur) This paper addresses semantic accuracy in relation to images obtained with remote sensing. Semantic accuracy is defined in terms of map complexity. Complexity metrics are applied as a metric to measure complexity. The idea is that a homogeneous map of a low complexity is of a high semantic accuracy. In this study, complexity metrics like aggregation index, fragmentation index and patch size are applied on two images with different objectives, one from an agricultural area in the Netherlands, and one from a rural area in Kazakhstan. Images are segmented first using region merging segmentation. Effects on metrics and semantic accuracy are discussed. On the basis of well-defined subsets, we conclude that the complexity metrics are suitable to quantify the semantic accuracy of the map. Segmentation is the most useful for an agricultural area including various agricultural fields. Metrics are mutually comparable being highly correlated, but showing some different aspects in quantifying map homogeneity and identifying objects of a high semantic accuracy. Numéro de notice : A2005-295 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160500057749 En ligne : https://doi.org/10.1080/01431160500057749 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27431
in International Journal of Remote Sensing IJRS > vol 26 n° 14 (July 2005) . - pp 2937 - 2951[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-05141 RAB Revue Centre de documentation En réserve L003 Exclu du prêt Multivariate texture-based segmentation of remotely sensed imagery for extraction of objects and their uncertainty / Arko Lucieer in International Journal of Remote Sensing IJRS, vol 26 n° 14 (July 2005)
[article]
Titre : Multivariate texture-based segmentation of remotely sensed imagery for extraction of objects and their uncertainty Type de document : Article/Communication Auteurs : Arko Lucieer, Auteur ; Alfred Stein, Auteur ; Peter F. Fisher, Auteur Année de publication : 2005 Article en page(s) : pp 2917 - 2936 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse multivariée
[Termes IGN] extraction automatique
[Termes IGN] image CASI
[Termes IGN] image multibande
[Termes IGN] incertitude des données
[Termes IGN] niveau de gris (image)
[Termes IGN] objet géographique
[Termes IGN] segmentation d'image
[Termes IGN] texture d'imageRésumé : (Auteur) In this study, a segmentation procedure is proposed, based on grey-level and multivariate texture to extract spatial objects from an image scene. Object uncertainty was quantified to identify transitions zones of objects with indeterminate boundaries. The Local Binary Pattern (LBP) operator, modelling texture, was integrated into a hierarchical splitting segmentation to identifiy homogeneous texture regions in an image. We proposed a multivariate extension of the standard univariate LBP operator to describe colour texture. The paper is illustrated with two case studies. The first considers an image with a composite of texture regions. The two LBP operators provided good segmentation results on both grey-scale and colour textures, depicted by accuracy values of 96% and 98% respectively. The second case study involved segmentation of coastal land cover objects from a multispectral Compact Airborne Spectral Imager (CASI) image, of a coastal area in the UK. Segmentation based on the univariate LBP measure provided unsatisfactory segmentation results from a single CASI band (70% accuracy). A multivariate LBP-based segmentation of three CASI bands improved segmentation results considerably (77% accuracy). Uncertainty values for object building blocks provided valuable information for identification of object transition zones. We conclude that the multivariate LBP texture model in combinaison with a hierarchical splitting segmentation framework is suitable for identifying objects and for quantifying their uncertainty. Numéro de notice : A2005-294 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160500057723 En ligne : https://doi.org/10.1080/01431160500057723 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27430
in International Journal of Remote Sensing IJRS > vol 26 n° 14 (July 2005) . - pp 2917 - 2936[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-05141 RAB Revue Centre de documentation En réserve L003 Exclu du prêt Detecting vegetation changes in a wetland area in Northern Germany using earth observation and geodata / Konstanze Kleinod in Journal for nature conservation, vol 13 n° 2-3 (July 2005)
[article]
Titre : Detecting vegetation changes in a wetland area in Northern Germany using earth observation and geodata Type de document : Article/Communication Auteurs : Konstanze Kleinod, Auteur ; Michael Wissen, Auteur ; Michaël Bock, Auteur Année de publication : 2005 Article en page(s) : pp 115 - 125 Note générale : biblographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Allemagne
[Termes IGN] carte de la végétation
[Termes IGN] détection de changement
[Termes IGN] image aérienne
[Termes IGN] image Landsat-TM
[Termes IGN] restauration du milieu naturel
[Termes IGN] végétation
[Termes IGN] zone humideRésumé : (auteur) Monitoring land use and landscape dynamics in conservation areas is important to understand and influence nature and restoration processes. Earth observation data can help to detect changes automatically in extensive areas. In a wetland area in Northern Germany different change detection methods have been tested to detect wetland restoration processes, especially succession of wetland and moorland vegetation over 11 years. Therefore a change detection method based on a selective principal component analysis followed by a fuzzy membership function introduced by Weiers et al. (2001). was tested with dual date Landsat TM/ETM+ images. As comparison vegetation maps and Colour-infrared (CIR)-aerial photographs were analysed. The main objectives were to find out (1) if changes, especially vegetation changes, can be detected on the study area by the method as described by Weiers et al. (2001), (2) which changes can be detected and (3) which is the best method on the study area, respectively: the Landsat change detection method, the analysis of vegetation maps or the interpretation of CIR-aerial photographs. For detecting vegetation changes the most detailed information were achieved by interpreting CIR-aerial photographs, while the Landsat change detection method turned out to be more suitable for detecting changes of wetness. Numéro de notice : A2005-009 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.jnc.2005.01.004 Date de publication en ligne : 23/01/2005 En ligne : http://dx.doi.org/10.1016/j.jnc.2005.01.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81062
in Journal for nature conservation > vol 13 n° 2-3 (July 2005) . - pp 115 - 125[article]Object-oriented methods for habitat mapping at multiple scales : Case studies from Northern Germany and Wye Downs, UK / Michaël Bock in Journal for nature conservation, vol 13 n° 2-3 (July 2005)
[article]
Titre : Object-oriented methods for habitat mapping at multiple scales : Case studies from Northern Germany and Wye Downs, UK Type de document : Article/Communication Auteurs : Michaël Bock, Auteur ; Panteleimon Xofis, Auteur ; Jonathan Mitchley, Auteur ; Godela Rossner, Auteur ; Michael Wissen, Auteur Année de publication : 2005 Article en page(s) : pp 75 - 89 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] classification orientée objet
[Termes IGN] écotone
[Termes IGN] habitat (nature)
[Termes IGN] image à très haute résolution
[Termes IGN] image aérienne
[Termes IGN] image Landsat-ETM+
[Termes IGN] image Landsat-TM
[Termes IGN] prairie
[Termes IGN] Schleswig-Holstein (Allemagne)
[Termes IGN] site Natura 2000
[Termes IGN] zone humide
[Vedettes matières IGN] Ecologie forestièreRésumé : (auteur) This paper presents an application of object-oriented techniques for habitat classification based on remotely sensed images and ancillary data. The study reports the results of habitat mapping at multiple scales using Earth Observation (EO) data at various spatial resolutions and multi temporal acquisition dates. We investigate the role of object texture and context in classification as well as the value of integrating knowledge from ancillary data sources. Habitat maps were produced at regional and local scales in two case studies; Schleswig-Holstein, Germany and Wye Downs, United Kingdom. At the regional scale, the main task was the development of a consistent object-oriented classification scheme that is transferable to satellite images for other years. This is demonstrated for a time series of Landsat TM/ETM+ scenes. At the local scale, investigations focus on the development of appropriate object-oriented rule networks for the detailed mapping of habitats, e.g. dry grasslands and wetlands using very high resolution satellite and airborne scanner images. The results are evaluated using statistical accuracy assessment and visual comparison with traditional field-based habitat maps. Whereas the application of traditional pixel-based classification result in a pixelised (salt and pepper) representation of land cover, the object-based classification technique result in solid habitat objects allowing easy integration into a vector-GIS for further analysis. The level of detail obtained at the local scale is comparable to that achieved by visual interpretation of aerial photographs or field-based mapping and also retains spatially explicit, fine scale information such as scrub encroachment or ecotone patterns within habitats. Numéro de notice : A2005-597 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.jnc.2004.12.002 En ligne : http://dx.doi.org/10.1016/j.jnc.2004.12.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80352
in Journal for nature conservation > vol 13 n° 2-3 (July 2005) . - pp 75 - 89[article]DEM generation and building detection from Lidar data / R. Ma in Photogrammetric Engineering & Remote Sensing, PERS, vol 71 n° 7 (July 2005)
[article]
Titre : DEM generation and building detection from Lidar data Type de document : Article/Communication Auteurs : R. Ma, Auteur Année de publication : 2005 Article en page(s) : pp 847 - 854 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] contour
[Termes IGN] densité des points
[Termes IGN] détection du bâti
[Termes IGN] données lidar
[Termes IGN] données localisées
[Termes IGN] modèle numérique de surface
[Termes IGN] point d'appui
[Termes IGN] reconstruction 3DRésumé : (Auteur) Object reconstruction has attracted great attention from both computer vision and photogrammetry communities, and new technologies are being introduced into this research society. Lidar (Light Detection And Ranging) has become well recognized in the geomatics community since the late 1990s. Compared with traditional photogrammetry, lidar has advantages in measuring surface in terms of accuracy and density, automation, and fast delivery time. There is a large market in geo-data acquisition and object recognition for lidar technology (Baltsavias, 1999). In a general sense, lidar is a companion technology for traditional photogrammetry. The direct product that can be derived from lidar data is the DSM (Digital Surface Model), which depicts the topography of the earth's surface, including objects above the terrain. Further processing can be carried out to generate DEM (Digital Terrain Model) and object models like buildings, which is very useful information in telecommunication, city planning, flood control, and tourism. Morphology and classification are two commonly used methods in DEM generation and object reconstruction. However, these two methods are either sensitive to errors or of low accuracy. In this paper, a new method is proposed to extract ground points for DEM generation and to detect points belonging to buildings. A new method for boundary regularization is also proposed. The results show that buildings can be detected with high accuracy from lidar data. Numéro de notice : A2005-299 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.71.7.847 En ligne : https://doi.org/10.14358/PERS.71.7.847 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27435
in Photogrammetric Engineering & Remote Sensing, PERS > vol 71 n° 7 (July 2005) . - pp 847 - 854[article]A split-and-merge technique for automated reconstruction of roof planes / Kourosh Khoshelham in Photogrammetric Engineering & Remote Sensing, PERS, vol 71 n° 7 (July 2005)PermalinkStructural damage assessments from Ikonos data using change detection, object-oriented segmentation, and classification techniques / D.H.A. Khudhairy in Photogrammetric Engineering & Remote Sensing, PERS, vol 71 n° 7 (July 2005)PermalinkApplication of multi-temporal high-resolution imagery GPS in a study of the motion of a canyon rim landslide / John Chadwick in ISPRS Journal of photogrammetry and remote sensing, vol 59 n° 4 (June - July 2005)PermalinkConstruction of the planar partition postal code map based on cadastral registration / F. Penninga in Geoinformatica, vol 9 n° 2 (June - August 2005)PermalinkImages, modèles et biomasse immergée : cartographie des herbiers de zostères en Camargue à partir d'images SPOT-5 / C. Puech in Revue internationale de géomatique, vol 15 n° 2 (juin – août 2005)PermalinkPhotogrammetric and Lidar data registration using linear features / A. Habib in Photogrammetric Engineering & Remote Sensing, PERS, vol 71 n° 6 (June 2005)PermalinkTélédétection et photogrammétrie, chaînons dans la détermination du climat urbain à Strasbourg / Tania Landes in XYZ, n° 103 (juin - août 2005)PermalinkThe use of remote sensing techniques and empirical tectonic models for inference of geological structures: bridging from regional to local scales / P.C. Fernandes Da Silva in Remote sensing of environment, vol 96 n° 1 (15/05/2005)PermalinkRadial basis function neural networks classification using very high spatial resolution satellite imagery: an application to the habitat area of Lake Kerkini (Greece) / Iphigenia Keramitsoglou in International Journal of Remote Sensing IJRS, vol 26 n° 9 (May 2005)PermalinkSatellite remote sensing for detailed landslide inventories using change detection and image fusion / J. Nichol in International Journal of Remote Sensing IJRS, vol 26 n° 9 (May 2005)Permalink