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Monitoring of chronological stages of deforestation-afforestation: the case of Southern Chile / Nicolas Maestripieri in Photo interprétation, European journal of applied remote sensing, vol 51 n° 3 (septembre 2015)
[article]
Titre : Monitoring of chronological stages of deforestation-afforestation: the case of Southern Chile Type de document : Article/Communication Auteurs : Nicolas Maestripieri, Auteur ; Gilles Selleron, Auteur ; Martin Paegelow, Auteur Année de publication : 2015 Article en page(s) : pp 2 - 11 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse spatio-temporelle
[Termes IGN] Chili
[Termes IGN] détection de changement
[Termes IGN] données de terrain
[Termes IGN] Eucalyptus (genre)
[Termes IGN] gestion forestière
[Termes IGN] image Landsat
[Termes IGN] image SPOT
[Termes IGN] Pinus (genre)
[Termes IGN] surveillance forestière
[Termes IGN] sylvicultureRésumé : (auteur) Industrial forest plantation expansion is dramatically impacting the environment (biodiversity, soil, water, etc.) and social sphere. Since the enactment of Decree Law 701 (DL 701) in 1974 under the military government of Augusto Pinochet, forestry practices in Chile have become more intensive (genetic manipulation, high yield clearcutting and short rotation). The law (and its successive updates) covers up to 75% of plantation costs and is the keystone of pine and eucalyptus forest expansion. This paper presents a pluriannual detection model for monitoring and characterizing the high cutting frequency of these timber plantations. Thirteen Landsat and SPOT images taken between 1976 and 2008 are used and combined with ground data (oblique aerial photography, GPS field surveys and field sheets). A trichromatic composition is built from spectral information taken from a Red and Mid-Infrared (MIR) wavelength along a temporal gradient of 32 years. This multi-temporal on-screen visual interpretation has led to a dynamic interpretation grid which reflects forest management stages in direct relation with pine and eucalyptus crop cycles. The method was tested on various time-steps covering the entire time period on two spatial scales — local and regional. All the spatio-temporal results are conclusive and the model established by remote sensing is of operational value. Numéro de notice : A2015--106 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88269
in Photo interprétation, European journal of applied remote sensing > vol 51 n° 3 (septembre 2015) . - pp 2 - 11[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 104-2015031 SL Revue Centre de documentation Revues en salle Disponible On spectral unmixing resolution using extended support vector machines / Xiaofeng Li in IEEE Transactions on geoscience and remote sensing, vol 53 n° 9 (September 2015)
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Titre : On spectral unmixing resolution using extended support vector machines Type de document : Article/Communication Auteurs : Xiaofeng Li, Auteur ; Xiuping Jia, Auteur ; Liguo Wang, Auteur ; Kai Zhao, Auteur Année de publication : 2015 Article en page(s) : pp 4985 - 4996 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] analyse infrapixellaire
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] classification pixellaire
[Termes IGN] classification spectraleRésumé : (Auteur) Due to the limited spatial resolution of multispectral/hyperspectral data, mixed pixels widely exist and various spectral unmixing techniques have been developed for information extraction at the subpixel level in recent years. One of the challenging problems in spectral mixture analysis is how to model the data of a primary class. Given that the within-class spectral variability (WSV) is inevitable, it is more realistic to associate a group of representative spectra with a pure class. The unmixing method using the extended support vector machines (eSVMs) has handled this problem effectively. However, it has simplified WSV in the mixed cases. In this paper, a further development of eSVMs is presented to address two problems in multiple-endmember spectral mixture analysis: 1) one mixed pixel may be unmixed into different fractions (model overlap); and 2) one fraction may correspond to a group of mixed pixels (fraction overlap). Then, spectral unmixing resolution (SUR) is introduced to characterize how finely the mixture in a mixed pixel can be quantified. The quantitative relationship between SUR and WSV of endmembers is derived via a geometry analysis in support vector machine feature space. Thus, the possible SUR can be estimated when multiple endmembers for each class are given. Moreover, if the requirement of SUR is fixed, the acceptance level of WSV is then limited, which can be used as a guide to remove outliers and purify endmembers for each primary class. Experiments are presented to illustrate model and fraction overlap problems and the application of SUR in uncertainty analysis of spectral unmixing. Numéro de notice : A2015-527 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2415587 Date de publication en ligne : 21/04/2015 En ligne : https://doi.org/10.1109/TGRS.2015.2415587 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77555
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 9 (September 2015) . - pp 4985 - 4996[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2015091 SL Revue Centre de documentation Revues en salle Disponible Registration of aerial imagery and lidar data in desert areas using sand ridges / Na Li in Photogrammetric record, vol 30 n° 151 (September - November 2015)
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Titre : Registration of aerial imagery and lidar data in desert areas using sand ridges Type de document : Article/Communication Auteurs : Na Li, Auteur ; Xianfeng Huang, Auteur ; Fan Zhang, Auteur ; Deren Li, Auteur Année de publication : 2015 Article en page(s) : pp 263 – 278 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] algorithme ICP
[Termes IGN] crète (ligne)
[Termes IGN] désert
[Termes IGN] données lidar
[Termes IGN] dune
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] fusion de données multisource
[Termes IGN] image aérienne
[Termes IGN] recalage d'image
[Termes IGN] semis de pointsRésumé : (Auteur) Image registration is a prerequisite for multisource data fusion. In this paper the problem of registering aerial images with lidar point clouds in desert areas is addressed. Compared with urban areas, registration in desert regions is difficult due to the lack of man-made features which are typically used in traditional methods. However, sand ridges can be used as registration primitives. Firstly, sand-ridge information is extracted from both the aerial image and the lidar point cloud. Secondly, by extending the iterative closest point (ICP) approach, a perspective-ICP algorithm is proposed that achieves data registration through matching sand ridges. To automatically deal with outliers, an adaptive weighting strategy is adopted. Experiments and assessment using data from Dunhuang, Gobi Desert, China, demonstrate that the method can achieve efficient and reliable registration for desert areas. Numéro de notice : A2015-562 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1111/phor.12110 Date de publication en ligne : 27/07/2015 En ligne : https://doi.org/10.1111/phor.12110 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77679
in Photogrammetric record > vol 30 n° 151 (September - November 2015) . - pp 263 – 278[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 106-2015031 RAB Revue Centre de documentation En réserve L003 Disponible Street environment change detection from mobile laser scanning point clouds / Wen Xiao in ISPRS Journal of photogrammetry and remote sensing, vol 107 (September 2015)
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Titre : Street environment change detection from mobile laser scanning point clouds Type de document : Article/Communication Auteurs : Wen Xiao, Auteur ; Bruno Vallet , Auteur ; Mathieu Brédif
, Auteur ; Nicolas Paparoditis
, Auteur
Année de publication : 2015 Projets : 1-Pas de projet / Article en page(s) : pp 38 - 49 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] arbre k-d
[Termes IGN] détection de changement
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] milieu urbain
[Termes IGN] route
[Termes IGN] semis de points
[Termes IGN] théorie de Dempster-ShaferMots-clés libres : Occupancy grids Point-to-triangle distance Résumé : (auteur) Mobile laser scanning (MLS) has become a popular technique for road inventory, building modelling, infrastructure management, mobility assessment, etc. Meanwhile, due to the high mobility of MLS systems, it is easy to revisit interested areas. However, change detection using MLS data of street environment has seldom been studied. In this paper, an approach that combines occupancy grids and a distance-based method for change detection from MLS point clouds is proposed. Unlike conventional occupancy grids, our occupancy-based method models space based on scanning rays and local point distributions in 3D without voxelization. A local cylindrical reference frame is presented for the interpolation of occupancy between rays according to the scanning geometry. The Dempster–Shafer theory (DST) is utilized for both intra-data evidence fusion and inter-data consistency assessment. Occupancy of reference point cloud is fused at the location of target points and then the consistency is evaluated directly on the points. A point-to-triangle (PTT) distance-based method is combined to improve the occupancy-based method. Because it is robust to penetrable objects, e.g. vegetation, which cause self-conflicts when modelling occupancy. The combined method tackles irregular point density and occlusion problems, also eliminates false detections on penetrable objects. Numéro de notice : A2015-725 Affiliation des auteurs : IGN (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.04.011 Date de publication en ligne : 11/05/2015 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.04.011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78374
in ISPRS Journal of photogrammetry and remote sensing > vol 107 (September 2015) . - pp 38 - 49[article]Tracking 3D moving objects based on GPS/IMU navigation solution, laser scanner point cloud and GIS data / Siavash Hosseinyalamdary in ISPRS International journal of geo-information, vol 4 n°3 (September 2015)
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[article]
Titre : Tracking 3D moving objects based on GPS/IMU navigation solution, laser scanner point cloud and GIS data Type de document : Article/Communication Auteurs : Siavash Hosseinyalamdary, Auteur ; Yashar Balazadegan, Auteur ; Charles K. Toth, Auteur Année de publication : 2015 Article en page(s) : pp 1301 - 1316 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] détection d'objet
[Termes IGN] données localisées 3D
[Termes IGN] filtre de Kalman
[Termes IGN] objet géographique 3D
[Termes IGN] objet mobile
[Termes IGN] poursuite de cible
[Termes IGN] semis de points
[Termes IGN] surveillance routière
[Termes IGN] trafic routierRésumé : (auteur) Monitoring vehicular road traffic is a key component of any autonomous driving platform. Detecting moving objects, and tracking them, is crucial to navigating around objects and predicting their locations and trajectories. Laser sensors provide an excellent observation of the area around vehicles, but the point cloud of objects may be noisy, occluded, and prone to different errors. Consequently, object tracking is an open problem, especially for low-quality point clouds. This paper describes a pipeline to integrate various sensor data and prior information, such as a Geospatial Information System (GIS) map, to segment and track moving objects in a scene. We show that even a low-quality GIS map, such as OpenStreetMap (OSM), can improve the tracking accuracy, as well as decrease processing time. A bank of Kalman filters is used to track moving objects in a scene. In addition, we apply non-holonomic constraint to provide a better orientation estimation of moving objects. The results show that moving objects can be correctly detected, and accurately tracked, over time, based on modest quality Light Detection And Ranging (LiDAR) data, a coarse GIS map, and a fairly accurate Global Positioning System (GPS) and Inertial Measurement Unit (IMU) navigation solution. Numéro de notice : A2015-711 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi4031301 En ligne : https://doi.org/10.3390/ijgi4031301 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78348
in ISPRS International journal of geo-information > vol 4 n°3 (September 2015) . - pp 1301 - 1316[article]Color and texture interpolation between orthoimagery and vector data / Charlotte Hoarau in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol II-3 W5 (October 2015)
PermalinkAn unsupervised urban change detection procedure by using luminance and saturation for multispectral remotely sensed images / Su Ye in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 8 (August 2015)
PermalinkChange-detection map learning using matching pursuit / Y. Li in IEEE Transactions on geoscience and remote sensing, vol 53 n° 8 (August 2015)
PermalinkFull-waveform data for building roof step edge localization / Małgorzata Słota in ISPRS Journal of photogrammetry and remote sensing, vol 106 (August 2015)
PermalinkA local approach to optimize the scale parameter in multiresolution segmentation for multispectral imagery / F. Cánovas-García in Geocarto international, vol 30 n° 7 - 8 (August - September 2015)
PermalinkSequential spectral change vector analysis for iteratively discovering and detecting multiple changes in hyperspectral images / Sicong Liu in IEEE Transactions on geoscience and remote sensing, vol 53 n° 8 (August 2015)
PermalinkAn adaptive semisupervised approach to the detection of user-defined recurrent changes in image time series / Daniel Zanotta in IEEE Transactions on geoscience and remote sensing, vol 53 n° 7 (July 2015)
PermalinkAutomatic transformation of different levels of detail in 3D GIS city models in CityGML / Yichuan Deng in International journal of 3-D information modeling, vol 4 n° 3 (July - September 2015)
PermalinkCartographie du châtaignier en Alsace par imagerie satellite multi-date / Colette Meyer in Revue Française de Photogrammétrie et de Télédétection, n° 211 - 212 (juillet - décembre 2015)
PermalinkDétection à haute résolution spatiale de la desserte forestière en milieu montagneux / António Ferraz in Revue Française de Photogrammétrie et de Télédétection, n° 211 - 212 (juillet - décembre 2015)
PermalinkA Landsat data tiling and compositing approach optimized for change detection in the conterminous United States / Kurtis J. Nelson in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 7 (July 2015)
PermalinkLocal binary patterns and extreme learning machine for hyperspectral imagery classification / Wei Li in IEEE Transactions on geoscience and remote sensing, vol 53 n° 7 (July 2015)
PermalinkMulticlass feature learning for hyperspectral image classification: Sparse and hierarchical solutions / Devis Tuia in ISPRS Journal of photogrammetry and remote sensing, vol 105 (July 2015)
PermalinkNew approach for object detection and extraction from digital images for providing a 3D model applicable in 3D GIS / Amir Aeed Homainejad in International journal of 3-D information modeling, vol 4 n° 3 (July - September 2015)
PermalinkA novel negative abundance‐oriented hyperspectral unmixing algorithm / Rubén Marrero in IEEE Transactions on geoscience and remote sensing, vol 53 n° 7 (July 2015)
PermalinkOperationalizing measurement of forest degradation: Identification and quantification of charcoal production in tropical dry forests using very high resolution satellite imagery / K. Dons in International journal of applied Earth observation and geoinformation, vol 39 (July 2015)
PermalinkRandom Forest and Rotation Forest for fully polarized SAR image classification using polarimetric and spatial features / Peijun Du in ISPRS Journal of photogrammetry and remote sensing, vol 105 (July 2015)
PermalinkSemantic point cloud interpretation based on optimal neighborhoods, relevant features and efficient classifiers / Martin Weinmann in ISPRS Journal of photogrammetry and remote sensing, vol 105 (July 2015)
PermalinkToward evaluating multiscale segmentations of high spatial resolution remote sensing images / Xueliang Zhang in IEEE Transactions on geoscience and remote sensing, vol 53 n° 7 (July 2015)
PermalinkAssessment of wildfire risk in Lebanon using geographic object-based image analysis / George Mitri in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 6 (June 2015)
PermalinkExtension of the linear chromodynamics model for spectral change detection in the presence of residual spatial misregistration / Karmon Vongsy in IEEE Transactions on geoscience and remote sensing, vol 53 n° 6 (June 2015)
PermalinkFast forward feature selection of hyperspectral images for classification with gaussian mixture models / Mathieu Fauvel in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol 8 n° 6 (June 2015)
PermalinkA fuzzy spatial reasoner for multi-scale GEOBIA ontologies / Argyros Argyridis in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 6 (June 2015)
PermalinkA graph-based segmentation algorithm for tree crown extraction using airborne LiDAR data / Victor F. Strimbu in ISPRS Journal of photogrammetry and remote sensing, vol 104 (June 2015)
PermalinkIntegrating user needs on misclassification error sensitivity into image segmentation quality assessment / Hugo Costa in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 6 (June 2015)
PermalinkInvariant rules for multipolarization SAR change detection / Vincenzo Carotenuto in IEEE Transactions on geoscience and remote sensing, vol 53 n° 6 (June 2015)
PermalinkMangrove tree crown delineation from high-resolution imagery / Muditha K. Heenkenda in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 6 (June 2015)
PermalinkObject-based building change detection from a single multispectral image and pre-existing geospatial information / Georgia Doxani in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 6 (June 2015)
PermalinkObject detection in optical remote sensing images based on weakly supervised learning and high-level feature learning / Junwei Han in IEEE Transactions on geoscience and remote sensing, vol 53 n° 6 (June 2015)
PermalinkSemi-automated building footprint extraction from orthophotos / Rheannon Brooks in Geomatica, vol 69 n° 2 (June 2015)
PermalinkSubstance dependence constrained sparse NMF for hyperspectral unmixing / Yuan Yuan in IEEE Transactions on geoscience and remote sensing, vol 53 n° 6 (June 2015)
PermalinkVery high resolution image matching based on local features and k-means clustering / Amin Sedaghat in Photogrammetric record, vol 30 n° 150 (June - August 2015)
PermalinkComplementarity of discriminative classifiers and spectral unmixing techniques for the interpretation of hyperspectral images / Jun Li in IEEE Transactions on geoscience and remote sensing, vol 53 n° 5 (mai 2015)
PermalinkForest species recognition based on dynamic classifier selection and dissimilarity feature vector representation / J.G. Martins in Machine Vision and Applications, vol 26 n° 2-3 (April 2015)
PermalinkPermalinkA multiscale and hierarchical feature extraction method for terrestrial laser scanning point cloud classification / Z. Wang in IEEE Transactions on geoscience and remote sensing, vol 53 n° 5 (mai 2015)
PermalinkPattern-mining approach for conflating crowdsourcing road networks with POIs / Bisheng Yang in International journal of geographical information science IJGIS, vol 29 n° 5 (May 2015)
PermalinkRefining high spatial resolution remote sensing image segmentation for man-made objects through acollinear and ipsilateral neighborhood model / Min Wang in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 5 (May 2015)
PermalinkSpectral–spatial classification for hyperspectral data using rotation forests with local feature extraction and markov random fields / Junshi Xia in IEEE Transactions on geoscience and remote sensing, vol 53 n° 5 (mai 2015)
PermalinkUse of Landsat and Corona data for mapping forest cover change from the mid-1960s to 2000s: Case studies from the Eastern United States and Central Brazil / Dan-Xia Song in ISPRS Journal of photogrammetry and remote sensing, vol 103 (May 2015)
PermalinkL'approche détection des changements pour estimer l'humidité du sol en milieu semi-aride à partir d'images ASAR, cas des hautes plaines de l'Est de l'Algérie / Mokhtar Guerfi in Revue Française de Photogrammétrie et de Télédétection, n° 210 (Avril 2015)
PermalinkClassifying compound structures in satellite images : A compressed representation for fast queries / Lionel Gueguen in IEEE Transactions on geoscience and remote sensing, vol 53 n° 4 (April 2015)
PermalinkExtraction des éléments de façade de bâtiments du patrimoine architectural à partir de données issues de scanner laser terrestre / Kenza Aitelkadi in Revue Française de Photogrammétrie et de Télédétection, n° 210 (Avril 2015)
PermalinkFast subpixel mapping algorithms for subpixel resolution change detection / Qunming Wang in IEEE Transactions on geoscience and remote sensing, vol 53 n° 4 (April 2015)
PermalinkLinear spectral mixture analysis via multiple-kernel learning for hyperspectral image classification / Keng-Hao Liu in IEEE Transactions on geoscience and remote sensing, vol 53 n° 4 (April 2015)
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