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[n° ou bulletin]
est un bulletin de ISPRS Journal of photogrammetry and remote sensing / International society for photogrammetry and remote sensing (1980 -) (1990 -) 
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Exemplaires(1)
| Code-barres | Cote | Support | Localisation | Section | Disponibilité |
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| 081-2013061 | RAB | Revue | Centre de documentation | En réserve L003 | Disponible |
Dépouillements
Ajouter le résultat dans votre panierTexture augmented detection of macrophyte species using decision trees / Cameron Proctor in ISPRS Journal of photogrammetry and remote sensing, vol 80 (June 2013)
Titre : Texture augmented detection of macrophyte species using decision trees Type de document : Article/Communication Auteurs : Cameron Proctor, Auteur ; Yuhong He, Auteur ; Vincent Robinson, Auteur Année de publication : 2013 Article en page(s) : pp 10 - 20 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] algue
[Termes IGN] classification par arbre de décision
[Termes IGN] image panchromatique
[Termes IGN] image Quickbird
[Termes IGN] macrophyte
[Termes IGN] précision de la classification
[Termes IGN] rivière
[Termes IGN] séparabilité
[Termes IGN] texture d'imageRésumé : (Auteur) Image classification using multispectral sensors has shown good performance in detecting macrophytes at the species level. However, species level classification often does not utilize the texture information provided by high resolution images. This study investigated whether image texture provides useful vector(s) for the discrimination of monospecific stands of three floating macrophyte species in Quickbird imagery of the South Nation River. Semivariograms indicated that window sizes of 5 x 5 and 13 x 13 pixels were the most appropriate spatial scales for calculation of the grey level co-occurrence matrix and subsequent texture attributes from the multispectral and panchromatic bands. Of the 214 investigated vectors (13 Haralick texture attributes * 15 bands + 9 spectral bands + 10 transformations/indices), feature selection determined which combination of spectral and textural vectors had the greatest class separability based on the Mann–Whitney U-test and Jefferies–Matusita distance. While multispectral red and near infrared (NIR) performed satisfactorily, the addition of panchromatic-dissimilarity slightly improved class separability and the accuracy of a decision tree classifier (Kappa: red/NIR/panchromatic-dissimilarity – 93.2% versus red/NIR – 90.4%). Class separability improved by incorporating a second texture attribute, but resulted in a decrease in classification accuracy. The results suggest that incorporating image texture may be beneficial for separating stands with high spatial heterogeneity. However, the benefits may be limited and must be weighed against the increased complexity of the classifier. Numéro de notice : A2013-295 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.02.022 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.02.022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32433
in ISPRS Journal of photogrammetry and remote sensing > vol 80 (June 2013) . - pp 10 - 20[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-2013061 RAB Revue Centre de documentation En réserve L003 Disponible
Titre : Shadow detection in very high spatial resolution aerial images: A comparative study Type de document : Article/Communication Auteurs : Karine R.M. Adeline, Auteur ; M. Chen, Auteur ; Xavier Briottet Année de publication : 2013 Article en page(s) : pp 21 - 38 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] canyon urbain
[Termes IGN] détection d'ombre
[Termes IGN] image hyperspectrale
[Termes IGN] image multibande
[Termes IGN] rayonnement lumineux
[Termes IGN] rayonnement proche infrarouge
[Termes IGN] seuillage d'image
[Termes IGN] simulation numérique
[Termes IGN] test de performanceRésumé : (Auteur) Automatic shadow detection is a very important pre-processing step for many remote sensing applications, particularly for images acquired with high spatial resolution. In complex urban environments, shadows may occupy a significant portion of the image. Ignoring these regions would lead to errors in various applications, such as atmospheric correction and classification. To better understand the radiative impact of shadows, a physical study was conducted through the simulation of a synthetic urban canyon scene. Its results helped to explain the most common assumptions made on shadows from a physical point of view in the literature. With this understanding, state-of-the-art methods on shadow detection were surveyed and categorized into six classes: histogram thresholding, invariant color models, object segmentation, geometrical methods, physics-based methods, unsupervised and supervised machine learning methods. Among them, some methods were selected and tested on a large dataset of multispectral and hyperspectral airborne images with high spatial resolution. The dataset chosen contains a large variety of typical occidental urban scenes. The results were compared based on accurate reference shadow masks. In these experiments, histogram thresholding on RGB and NIR channels performed the best with an average accuracy of 92.5%, followed by physics-based methods, such as Richter’s method with 90.0%. Finally, this paper analyzes and discusses the limits of these algorithms, concluding with some recommendations for shadow detection. Numéro de notice : A2013-296 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.02.003 Date de publication en ligne : 03/04/2013 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2013.02.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32434
in ISPRS Journal of photogrammetry and remote sensing > vol 80 (June 2013) . - pp 21 - 38[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-2013061 RAB Revue Centre de documentation En réserve L003 Disponible
Titre : Derivation of tree skeletons and error assessment using LiDAR point cloud data of varying quality Type de document : Article/Communication Auteurs : Magnus Bremer, Auteur ; Martin Rutzinger, Auteur ; V. Wichmann, Auteur Année de publication : 2013 Article en page(s) : pp 39 - 50 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] arbre (flore)
[Termes IGN] artefact
[Termes IGN] données lidar
[Termes IGN] semis de points
[Termes IGN] squelettisation
[Termes IGN] vecteur propreRésumé : (Auteur) The architecture of trees is of particular interest for 3D model creation in forestry and ecolocical applications. Terrestrial (TLS) and mobile laser scanning (MLS) systems are used to acquire detailed geometrical data of trees. Since 3D point clouds from laser scanning consist of large data amounts representing uninterpreted topographical information including noise and data gaps, an extraction of salient tree structures is important for further applications. We present a fully automated modular workflow for topological reliable reconstruction of tree architecture. Object-based point cloud processing such as branch extraction is combined with tree skeletonization. Branch extraction is performed using a segmentation procedure followed by segment-based analysis of form indices derived from eigenvector metrics. Extracted branch primitives are simplified and connected to line features during skeletonization. The modular workflow allows comprehensive parameter tests and error assessments that are used for a calibration of the module parameters with respect to various characteristics of the input data (e.g noise, scanning resolution, and the number of scan positions). The estimated parameter settings are validated using an exemplary MLS data set. The quality of input point cloud data, strongly influencing the quality of the skeleton results, can be improved by the presented branch extraction procedure. The potential for data improvement increases with increasing point densities. For our object-based appoach, we can show that the presence of erroneous structures and filtering artifacts have the strongest influence onto the quality of the derived skeletons. In contrast to traditional skeletonization approaches, the existance of data gaps has less influence onto the results. Numéro de notice : A2013-297 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.03.003 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.03.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32435
in ISPRS Journal of photogrammetry and remote sensing > vol 80 (June 2013) . - pp 39 - 50[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-2013061 RAB Revue Centre de documentation En réserve L003 Disponible
Titre : Improved topographic mapping through high-resolution SAR interferometry with atmospheric effect removal Type de document : Article/Communication Auteurs : Mingsheng Liao, Auteur ; Houjun Jiang, Auteur ; Yong Wang, Auteur ; et al., Auteur Année de publication : 2013 Article en page(s) : pp 72 - 79 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] bande X
[Termes IGN] cartographie topographique
[Termes IGN] Chine
[Termes IGN] effet atmosphérique
[Termes IGN] erreur en altitude
[Termes IGN] filtre passe-bas
[Termes IGN] image à haute résolution
[Termes IGN] image Cosmo-Skymed
[Termes IGN] image radar moirée
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] MNS SRTM
[Termes IGN] modèle numérique de terrain
[Termes IGN] régression linéaireRésumé : (Auteur) The application of SAR interferometry (InSAR) in topographic mapping is usually limited by geometric/temporal decorrelations and atmospheric effect, particularly in repeat-pass mode. In this paper, to improve the accuracy of topographic mapping with high-resolution InSAR, a new approach to estimate and remove atmospheric effect has been developed. Under the assumptions that there was no ground deformation within a short temporal period and insignificant ionosphere interference on high-frequency radar signals, e.g. X-bands, the approach was focused on the removal of two types of atmospheric effects, namely tropospheric stratification and turbulence. Using an available digital elevation model (DEM) of moderate spatial resolution, e.g. Shuttle Radar Topography Mission (SRTM) DEM, a differential interferogram was firstly produced from the high-resolution InSAR data pair. A linear regression model between phase signal and auxiliary elevation was established to estimate the stratified atmospheric effect from the differential interferogram. Afterwards, a combination of a low-pass and an adaptive filter was employed to separate the turbulent atmospheric effect. After the removal of both types of atmospheric effects in the high-resolution interferogram, the interferometric phase information incorporating local topographic details was obtained and further processed to produce a high-resolution DEM. The feasibility and effectiveness of this approach was validated by an experiment with a tandem-mode X-band COSMO-SkyMed InSAR data pair covering a mountainous area in Northwestern China. By using a standard Chinese national DEM of scale 1:50,000 as the reference, we evaluated the vertical accuracy of InSAR DEM with and without atmospheric effects correction, which shows that after atmospheric signal correction the root-mean-squared error (RMSE) has decreased from 13.6 m to 5.7 m. Overall, from this study a significant improvement to derive topographic maps with high accuracy has been achieved by using the proposed approach. Numéro de notice : A2013-298 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.03.008 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.03.008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32436
in ISPRS Journal of photogrammetry and remote sensing > vol 80 (June 2013) . - pp 72 - 79[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-2013061 RAB Revue Centre de documentation En réserve L003 Disponible
Titre : Change detection from remotely sensed images: From pixel-based to object-based approaches Type de document : Article/Communication Auteurs : Masroor Hussain, Auteur ; Dongmei Chen, Auteur ; Angela Cheng, Auteur ; et al., Auteur Année de publication : 2013 Article en page(s) : pp 91 - 106 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse spectrale
[Termes IGN] classification orientée objet
[Termes IGN] classification pixellaire
[Termes IGN] détection de changement
[Termes IGN] exploration de données géographiques
[Termes IGN] télédétectionRésumé : (Auteur) The appetite for up-to-date information about earth’s surface is ever increasing, as such information provides a base for a large number of applications, including local, regional and global resources monitoring, land-cover and land-use change monitoring, and environmental studies. The data from remote sensing satellites provide opportunities to acquire information about land at varying resolutions and has been widely used for change detection studies. A large number of change detection methodologies and techniques, utilizing remotely sensed data, have been developed, and newer techniques are still emerging. This paper begins with a discussion of the traditionally pixel-based and (mostly) statistics-oriented change detection techniques which focus mainly on the spectral values and mostly ignore the spatial context. This is succeeded by a review of object-based change detection techniques. Finally there is a brief discussion of spatial data mining techniques in image processing and change detection from remote sensing data. The merits and issues of different techniques are compared. The importance of the exponential increase in the image data volume and multiple sensors and associated challenges on the development of change detection techniques are highlighted. With the wide use of very-high-resolution (VHR) remotely sensed images, object-based methods and data mining techniques may have more potential in change detection Numéro de notice : A2013-299 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.03.006 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.03.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32437
in ISPRS Journal of photogrammetry and remote sensing > vol 80 (June 2013) . - pp 91 - 106[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-2013061 RAB Revue Centre de documentation En réserve L003 Disponible
