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Per-pixel and object-oriented classification methods for mapping urban land cover extraction using SPOT 5 imagery / Mustafa Neamah Jebur in Geocarto international, vol 29 n° 7 - 8 (November - December 2014)
[article]
Titre : Per-pixel and object-oriented classification methods for mapping urban land cover extraction using SPOT 5 imagery Type de document : Article/Communication Auteurs : Mustafa Neamah Jebur, Auteur ; Helmi Zulhaidi Mohd Shafri, Auteur ; Biswajeet Pradhan, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 792 - 806 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] cartographie urbaine
[Termes IGN] classification dirigée
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] extraction automatique
[Termes IGN] image SPOT 5
[Termes IGN] utilisation du solRésumé : (Auteur) To have sustainable management and proper decision-making, timely acquisition and analysis of surface features are necessary. Traditional pixel-based analysis is the popular way to extract different categories, but it is not comparable by the achievements that can be achieved through the object-based method that uses the additional characteristics of features in the process of classification. In this paper, three types of classification were used to classify SPOT 5 satellite image in mapping land cover; Support vector machine (SVM) pixel-based, SVM object-based and Decision Tree (DT) pixel-based classification. Normalised Difference Vegetation Index and the brightness value of two infrared bands (NIR and SWIR) were used in manually developed DT classification. The classification of the SVM (pixel based) was generated using the selected groups of pixels that represent the selected features. In addition, the SVM (object based) was implemented by using radial-based function kernel. The classified features were oil palm, rubber, urban area, soil, water and other vegetation. The study found that the overall classification of the DT was the lowest at 69.87% while those of SVM (pixel based) and SVM (object based) were 76.67 and 81.25%, respectively. Numéro de notice : A2014-468 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2013.848944 En ligne : https://doi.org/10.1080/10106049.2013.848944 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74045
in Geocarto international > vol 29 n° 7 - 8 (November - December 2014) . - pp 792 - 806[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2014041 RAB Revue Centre de documentation En réserve L003 Disponible Apport de l'imagerie satellitaire à haute et très haute résolution pour la recherche d'indices de drainage superficiel : Application aux aires d'alimentation de captage (AAC) d'eau potable / Sébastien Rucquoi in Revue Française de Photogrammétrie et de Télédétection, n° 208 (Octobre 2014)
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Titre : Apport de l'imagerie satellitaire à haute et très haute résolution pour la recherche d'indices de drainage superficiel : Application aux aires d'alimentation de captage (AAC) d'eau potable Type de document : Article/Communication Auteurs : Sébastien Rucquoi, Auteur ; Christelle Bosc, Auteur ; El Bachir Araqui, Auteur ; et al., Auteur Année de publication : 2014 Conférence : Pleiades Days 2014 01/04/2014 03/04/2014 Toulouse France Article en page(s) : pp 77 - 82 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] drainage
[Termes IGN] eau potable
[Termes IGN] extraction automatique
[Termes IGN] image Pléiades
[Termes IGN] image SPOT 5
[Termes IGN] image tri-stéréoscopique
[Termes IGN] modèle numérique de surface
[Termes IGN] modèle numérique de terrain
[Termes IGN] pollution des eaux
[Termes IGN] qualité des eaux
[Termes IGN] réseau hydrographique
[Termes IGN] surface cultivéeRésumé : (Auteur) La loi sur l'eau et les milieux aquatiques de décembre 2006 a renforcé les dispositifs existants de lutte contre les pollutions diffuses d'origine agricole en créant des "zones de protection des Aires d'Alimentation de Captage (AAC)" d'eau potable, avec comme principal objectif de préserver ou de restaurer la qualité des ressources en eau. L'objectif de cet article est d'évaluer l'apport de l'imagerie satellitaire pour la caractérisation de ces aires à partir d'un panorama de méthodes d'extraction d'indices de drainages superficiels, d'origine naturelle et artificielle, ainsi que de tests méthodologiques. En effet, la connaissance précise des réseaux de drainage susceptibles de transporter des pollutions constitue l'un des éléments déterminant pour qualifier le captage et son environnement. Numéro de notice : A2014-608 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.52638/rfpt.2014.140 En ligne : https://doi.org/10.52638/rfpt.2014.140 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74909
in Revue Française de Photogrammétrie et de Télédétection > n° 208 (Octobre 2014) . - pp 77 - 82[article]Fusion of airborne LiDAR with multispectral SPOT 5 image for enhancement of feature extraction using dempster–shafer theory / Vahideh Saeidi in IEEE Transactions on geoscience and remote sensing, vol 52 n° 10 tome 1 (October 2014)
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Titre : Fusion of airborne LiDAR with multispectral SPOT 5 image for enhancement of feature extraction using dempster–shafer theory Type de document : Article/Communication Auteurs : Vahideh Saeidi, Auteur ; Biswajeet Pradhan, Auteur ; O. Idrees Mohammed, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 6017 - 6025 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] données lidar
[Termes IGN] fusion d'images
[Termes IGN] image SPOT 5
[Termes IGN] indice de végétation
[Termes IGN] théorie de Dempster-ShaferRésumé : (Auteur) This paper presents an application of data-driven Dempster-Shafer theory (DST) of evidence to fuse multisensor data for land-cover feature extraction. Over the years, researchers have focused on DST for a variety of applications. However, less attention has been given to generate and interpret probability, certainty, and conflict maps. Moreover, quantitative assessment of DST performance is often overlooked. In this paper, for implementation of DST, two main types of data were used: multisensor data such as Light Detection and Ranging (LiDAR) and multispectral satellite imagery [Satellite Pour l'Observation de la Terre 5 (SPOT 5)]. The objectives are to classify land-cover types from fused multisensor data using DST, to quantitatively assess the accuracy of the classification, and to examine the potential of slope data derived from LiDAR for feature detection. First, we derived the normalized difference vegetation index (NDVI) from SPOT 5 image and the normalized digital surface model (DSM) (nDSM) from LiDAR by subtracting the digital terrain model from the DSM. The two products were fused using the DST algorithm, and the accuracy of the classification was assessed. Second, we generated a surface slope from LiDAR and fused it with NDVI. Subsequently, the classification accuracy was assessed using an IKONOS image of the study area as ground truth data. From the two processing stages, the NDVI/nDSM fusion had an overall accuracy of 88.7%, while the NDVI/slope fusion had 75.3%. The result indicates that NDVI/nDSM integration performed better than NDVI/slope. Although the overall accuracy of the former is better than the latter (NDVI/slope), the contribution of individual class reveals that building extraction from fused slope and NDVI performed poorly. This study proves that DST is a time- and cost-effective method for accurate land-cover feature identification and extraction without the need for a prior knowledge of the scene. Furthermore, the ability to generate other products like certainty, conflict, and maximum probability maps for better visual understanding of the decision process makes it more reliable for applications such as urban planning, forest management, 3-D feature extraction, and map updating. Numéro de notice : A2014-488 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2294398 En ligne : https://doi.org/10.1109/TGRS.2013.2294398 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74077
in IEEE Transactions on geoscience and remote sensing > vol 52 n° 10 tome 1 (October 2014) . - pp 6017 - 6025[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2014101A RAB Revue Centre de documentation En réserve L003 Disponible Quantification of L-band InSAR coherence over volcanic areas using LiDAR and in situ measurements / Mélanie Arab-Sedze in Remote sensing of environment, vol 152 (September 2014)
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Titre : Quantification of L-band InSAR coherence over volcanic areas using LiDAR and in situ measurements Type de document : Article/Communication Auteurs : Mélanie Arab-Sedze, Auteur ; Essam Heggy, Auteur ; Frédéric Bretar, Auteur ; Daniel Berveiller, Auteur ; Stéphane Jacquemoud, Auteur Année de publication : 2014 Article en page(s) : pp 202 - 216 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] image ALOS-PALSAR
[Termes IGN] image SPOT 5
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] Leaf Area Index
[Termes IGN] Piton de la Fournaise (volcan)
[Termes IGN] propriété diélectrique
[Termes IGN] Réunion, île de la
[Termes IGN] volcanRésumé : (auteur) Interferometric Synthetic Aperture Radar (InSAR) is a powerful tool to monitor large-scale ground deformation at active volcanoes. However, vegetation and pyroclastic deposits degrade the radar coherence and therefore the measurement of 3-D surface displacements. In this article, we explore the complementarity between ALOS–PALSAR coherence images, airborne LiDAR data and in situ measurements acquired over the Piton de La Fournaise volcano (Reunion Island, France) to determine the sources of errors that may affect repeat-pass InSAR measurements. We investigate three types of surfaces: terrains covered with vegetation, lava flows (a′a, pahoehoe or slabby pahoehoe lava flows) and pyroclastic deposits (lapilli). To explain the loss of coherence observed over the Dolomieu crater between 2008 and 2009, we first use laser altimetry data to map topographic variations. The LiDAR intensity, which depends on surface reflectance, also provides ancillary information about the potential sources of coherence loss. In addition, surface roughness and rock dielectric properties of each terrain have been determined in situ to better understand how electromagnetic waves interact with such media: rough and porous surfaces, such as the a′a lava flows, produce a higher coherence loss than smoother surfaces, such as the pahoehoe lava flows. Variations in dielectric properties suggest a higher penetration depth in pyroclasts than in lava flows at L-band frequency. Decorrelation over the lapilli is hence mainly caused by volumetric effects. Finally, a map of LAI (Leaf Area Index) produced using SPOT 5 imagery allows us to quantify the effect of vegetation density: radar coherence is negatively correlated with LAI and is unreliable for values higher than 7.5. Numéro de notice : A2014-812 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2014.06.011 Date de publication en ligne : 11/07/2014 En ligne : https://doi.org/10.1016/j.rse.2014.06.011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89039
in Remote sensing of environment > vol 152 (September 2014) . - pp 202 - 216[article]Assessment of the image misregistration effects on object-based change detection / Gang Chen in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)
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Titre : Assessment of the image misregistration effects on object-based change detection Type de document : Article/Communication Auteurs : Gang Chen, Auteur ; Kaiguang Zhao, Auteur ; Ryan Powers, Auteur Année de publication : 2014 Article en page(s) : pp 19 - 27 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse diachronique
[Termes IGN] classification orientée objet
[Termes IGN] détection de changement
[Termes IGN] estimation de précision
[Termes IGN] image multitemporelle
[Termes IGN] image SPOT 5Résumé : (Auteur) High-spatial resolution remote sensing imagery provides unique opportunities for detailed characterization and monitoring of landscape dynamics. To better handle such data sets, change detection using the object-based paradigm, i.e., object-based change detection (OBCD), have demonstrated improved performances over the classic pixel-based paradigm. However, image registration remains a critical pre-process, with new challenges arising, because objects in OBCD are of various sizes and shapes. In this study, we quantified the effects of misregistration on OBCD using high-spatial resolution SPOT 5 imagery (5 m) for three types of landscapes dominated by urban, suburban and rural features, representing diverse geographic objects. The experiments were conducted in four steps: (i) Images were purposely shifted to simulate the misregistration effect. (ii) Image differencing change detection was employed to generate difference images with all the image-objects projected to a feature space consisting of both spectral and texture variables. (iii) The changes were extracted using the Mahalanobis distance and a change ratio. (iv) The results were compared to the ‘real’ changes from the image pairs that contained no purposely introduced registration error. A pixel-based change detection method using similar steps was also developed for comparisons. Results indicate that misregistration had a relatively low impact on object size and shape for most areas. When the landscape is comprised of small mean object sizes (e.g., in urban and suburban areas), the mean size of ‘change’ objects was smaller than the mean of all objects and their size discrepancy became larger with the decrease in object size. Compared to the results using the pixel-based paradigm, OBCD was less sensitive to the misregistration effect, and the sensitivity further decreased with an increase in local mean object size. However, high-spatial resolution images typically have higher spectral variability within neighboring pixels than the relatively low resolution datasets. As a result, accurate image registration remains crucial to change detection even if an object-based approach is used. Numéro de notice : A2014-008 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.10.007 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.10.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32913
in ISPRS Journal of photogrammetry and remote sensing > vol 87 (January 2014) . - pp 19 - 27[article]Réservation
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