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Error assessment in two lidar-derived TIN datasets / M.H. Peng in Photogrammetric Engineering & Remote Sensing, PERS, vol 72 n° 8 (August 2006)
[article]
Titre : Error assessment in two lidar-derived TIN datasets Type de document : Article/Communication Auteurs : M.H. Peng, Auteur ; T.Y. Shih, Auteur Année de publication : 2006 Article en page(s) : pp 933 - 947 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] canopée
[Termes IGN] classification dirigée
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] erreur de mesure
[Termes IGN] estimation statistique
[Termes IGN] modèle numérique de surface
[Termes IGN] occupation du sol
[Termes IGN] pente
[Termes IGN] point de vérification
[Termes IGN] précision des données
[Termes IGN] rugosité
[Termes IGN] rugosité du sol
[Termes IGN] semis de points
[Termes IGN] Triangulated Irregular Network
[Termes IGN] variabilité
[Termes IGN] végétationRésumé : (Auteur) An accuracy assessment of two lidar-derived elevation datasets was conducted in areas of rugged terrain (average slope 26.6°). Data from 906 ground checkpoints in various land-cover types were collected in situ as reference points. Analysis of the accuracy of lidar-derived elevation as a function of several factors including terrain slope, terrain aspect, and land-cover types was conducted. This paper attempts to characterize vegetation information derived from lidar data based on variables such as canopy volume, local roughness of point clouds, point spacing of lidar ground returns, and vegetation angle. This information was used to evaluate the accuracy of elevation as a function of vegetation type. The experimental results revealed that the accuracy of elevation was considerably correlated with five factors: terrain slope, vegetation angle, canopy volume, local roughness of point clouds, and point spacing of lidar ground returns. The results show a linear relationship between the elevation accuracy and the combination of vegetation angle and the point spacing of ground returns (r2 > 0.9). The combination of vegetation angle and point spacing of ground returns explains a significant amount of the variability in elevation accuracy. Elevation accuracy varied with different vegetation types. The elevation accuracy was also linearly correlated with the product of the point spacing of ground returns and the tangent of the slope (r2 = 0.9). A greater product value implies a greater elevation error. In addition, with regard to terrain aspect, one dense dataset with extra cross-flight data revealed a lesser impact of aspect on elevation accuracy. Copyright ASPRS Numéro de notice : A2006-312 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14358/PERS.72.8.933 En ligne : https://doi.org/10.14358/PERS.72.8.933 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28036
in Photogrammetric Engineering & Remote Sensing, PERS > vol 72 n° 8 (August 2006) . - pp 933 - 947[article]Land-cover mapping in the Brazilian amazon using SPOT-4 Vegetation data and machine learning classification methods / João M.B. Carreiras in Photogrammetric Engineering & Remote Sensing, PERS, vol 72 n° 8 (August 2006)
[article]
Titre : Land-cover mapping in the Brazilian amazon using SPOT-4 Vegetation data and machine learning classification methods Type de document : Article/Communication Auteurs : João M.B. Carreiras, Auteur ; J.M.C. Pereira, Auteur ; Y.E. Shimabukuro, Auteur Année de publication : 2006 Article en page(s) : pp 897 - 910 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse diachronique
[Termes IGN] apprentissage automatique
[Termes IGN] carte d'occupation du sol
[Termes IGN] cartographie numérique
[Termes IGN] classification ascendante hiérarchique
[Termes IGN] image SPOT-Végétation
[Termes IGN] Mato Grosso
[Termes IGN] occupation du solRésumé : (Auteur) The main objective of this study is to evaluate the feasibility of deriving a land-cover map of the state of Mato Grosso, Brazil, for the year 2000, using data from the 1 km SPOT-4 VEGETATION (VGT) sensor. For this purpose we used a VGT temporal series of 12 monthly composite images, which were further transformed to physical-meaningful fraction images of vegetation, soil, and shade. Classification of fraction images was implemented using several recent machine learning developments, namely, filtering input training data and probability bagging in a classification tree approach. A 10-fold cross validation accuracy assessment indicates that filtering and probability bagging are effective at increasing overall and class-specific accuracy. Overall accuracy and mean probability of class membership were 0.88 and 0.80, respectively. The map of probability of class membership indicates that the larger errors are associated with cerrado savonna and semi-deciduous forest. Copyright ASPRS Numéro de notice : A2006-313 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.72.8.897 En ligne : https://doi.org/10.14358/PERS.72.8.897 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28037
in Photogrammetric Engineering & Remote Sensing, PERS > vol 72 n° 8 (August 2006) . - pp 897 - 910[article]A patch-based image classification by integrating hyperspectral data with GIS / B. Zhang in International Journal of Remote Sensing IJRS, vol 27 n°15-16 (August 2006)
[article]
Titre : A patch-based image classification by integrating hyperspectral data with GIS Type de document : Article/Communication Auteurs : B. Zhang, Auteur ; Xiuping Jia, Auteur ; et al., Auteur Année de publication : 2006 Article en page(s) : pp 3337 - 3346 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification dirigée
[Termes IGN] classification pixellaire
[Termes IGN] image hyperspectrale
[Termes IGN] image PHI
[Termes IGN] système d'information géographiqueRésumé : (Auteur) Hyperspectral remote sensing data provide detailed spectral information and are widely used for pixel-based image classification. However, without considering spatial correlation among neighbouring pixels, a generated thematic map may have a ‘salt-and-pepper’ appearance. With the development of the Geographic Information System (GIS), the spatial relationship between a pixel and its neighbours can be recorded readily and used together with remote sensing data. The objective of this study was to integrate hyperspectral data with the GIS for effective thematic mapping. To date, GIS data have been used mainly in field surveys or training field selection for remote sensing data interpretation. Here we propose a patch-classification based on integration of the GIS with remote sensing data. The classification results obtained by using this method can be easily saved in a vector format as used for GIS files. Computational cost is decreased compared with a pixel-by-pixel classification. The issue of how to identify pure or mixed patches is addressed and a three-level simple and effective checking method is developed. A case study is presented with a hyperspectral data set recorded by the Pushbroom Hyperspectral Imager (PHI) and related GIS data. Numéro de notice : A2006-337 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160500409577 En ligne : https://doi.org/10.1080/01431160500409577 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28061
in International Journal of Remote Sensing IJRS > vol 27 n°15-16 (August 2006) . - pp 3337 - 3346[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 080-06081 RAB Revue Centre de documentation En réserve L003 Disponible Performance of change detection using remotely sensed data and evidential fusion: comparison of three cases of application / Sylvie Le Hégarat-Mascle in International Journal of Remote Sensing IJRS, vol 27 n°15-16 (August 2006)
[article]
Titre : Performance of change detection using remotely sensed data and evidential fusion: comparison of three cases of application Type de document : Article/Communication Auteurs : Sylvie Le Hégarat-Mascle, Auteur ; R. Seltz, Auteur ; Laurence Hubert-Moy, Auteur ; Samuel Corgne, Auteur ; Nicolas Stach , Auteur Année de publication : 2006 Article en page(s) : pp 3515 - 3532 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse comparative
[Termes IGN] analyse texturale
[Termes IGN] changement climatique
[Termes IGN] classification de Dempster-Shafer
[Termes IGN] cultures
[Termes IGN] détection de changement
[Termes IGN] forêt
[Termes IGN] Pinus (genre)
[Termes IGN] théorie de l'informationRésumé : (Auteur) The detection of changes affecting continental surfaces has important applications in hydrological, meteorological and climatic modelling. Using remote sensing data, numerous change indices have already been proposed. Previous work showed the interest of combining several of these to improve change detection performance, using the Dempster–Shafer evidence theory framework. This study analyses the performance of different change indices and their combination in different cases of application: forest logging either in pine forest or in mixed forest, and winter vegetation cover of fields in intensive farming areas, in comparison to the forest fire case presented in previous work. The interest of indices derived from Information Theory, some of which are original, is shown. Numéro de notice : A2006-338 Affiliation des auteurs : IFN+Ext (1958-2011) Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160500300255 Date de publication en ligne : 22/02/2007 En ligne : https://doi.org/10.1080/01431160500300255 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28062
in International Journal of Remote Sensing IJRS > vol 27 n°15-16 (August 2006) . - pp 3515 - 3532[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 080-06081 RAB Revue Centre de documentation En réserve L003 Disponible A support vector method for anomaly detection in hyperspectral imagery / Amit Banerjee in IEEE Transactions on geoscience and remote sensing, vol 44 n° 8 (August 2006)
[article]
Titre : A support vector method for anomaly detection in hyperspectral imagery Type de document : Article/Communication Auteurs : Amit Banerjee, Auteur ; Philippe Burlina, Auteur ; Chris Diehl, Auteur Année de publication : 2006 Article en page(s) : pp 2282 - 2291 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] aide à la décision
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] détection d'erreur
[Termes IGN] détection de cible
[Termes IGN] image hyperspectrale
[Termes IGN] méthode fondée sur le noyau
[Termes IGN] test statistiqueRésumé : (Auteur) This paper presents a method for anomaly detection in hyperspectral images based on the support vector data description (SVDD), a kernel method for modeling the support of a distribution. Conventional anomaly-detection algorithms are based upon the popular Reed-Xiaoli detector. However, these algorithms typically suffer from large numbers of false alarms due to the assumptions that the local background is Gaussian and homogeneous. In practice, these assumptions are often violated, especially when the neighborhood of a pixel contains multiple types of terrain. To remove these assumptions, a novel anomaly detector that incorporates a nonparametric background model based on the SVDD is derived. Expanding on prior SVDD work, a geometric interpretation of the SVDD is used to propose a decision rule that utilizes a new test statistic and shares some of the properties of constant false-alarm rate detectors. Using receiver operating characteristic curves, the authors report results that demonstrate the improved performance and reduction in the false-alarm rate when using the SVDD-based detector on wide-area airborne mine detection (WAAMD) and hyperspectral digital imagery collection experiment (HYDICE) imagery. Copyright IEEE Numéro de notice : A2006-396 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2006.873019 En ligne : https://doi.org/10.1109/TGRS.2006.873019 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28120
in IEEE Transactions on geoscience and remote sensing > vol 44 n° 8 (August 2006) . - pp 2282 - 2291[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-06081 RAB Revue Centre de documentation En réserve L003 Disponible Tree cover and height estimation in the Fennoscandian tundra-taiga transition zone using multiangular MISR data / J. Heiskanen in Remote sensing of environment, vol 103 n° 1 (15 July 2006)PermalinkFuzzy classification: a case study using Landsat TM images in Iran / A.M. Lak in GIM international, vol 20 n° 7 (July 2006)PermalinkIncorporating domain knowledge and spatial relationships into land cover classifications: a rule-based approach / A.E. Daniels in International Journal of Remote Sensing IJRS, vol 27 n°12-13-14 (July 2006)PermalinkMapping the results of geographically weighted regression / J. Mennis in Cartographic journal (the), vol 43 n° 2 (July 2006)PermalinkPopulation landscape: a geometric approach to studying spatial patterns of the US urban hierarchy / L. Mu in International journal of geographical information science IJGIS, vol 20 n° 6 (july 2006)PermalinkA practical map labeling algorithm utilizing morphological image processing and force-directed methods / G. Stadler in Cartography and Geographic Information Science, vol 33 n° 3 (July 2006)PermalinkSélection adaptative des dimensions de l'indexation visuelle d'images mal annotées en fonction du mot recherché / S. Tollari in Ingénierie des systèmes d'information, ISI : Revue des sciences et technologies de l'information, RSTI, vol 11 n° 4 (juillet - août 2006)PermalinkSome issues in the classification of DAIS hyperspectral data / M. Pal in International Journal of Remote Sensing IJRS, vol 27 n°12-13-14 (July 2006)PermalinkStudy of tectonics in relation to the seismic activity of the Davalt area, Nasik district, Maharashtra, India using remote sensing and GIS techniques / J. Sarup in International Journal of Remote Sensing IJRS, vol 27 n°12-13-14 (July 2006)PermalinkUrban land-use classification using variogram-based analysis with an aerial photograph / S.S. Wu in Photogrammetric Engineering & Remote Sensing, PERS, vol 72 n° 7 (July 2006)Permalink