Descripteur
Documents disponibles dans cette catégorie (4899)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Etendre la recherche sur niveau(x) vers le bas
Spatially sensitive statistical shape analysis for pedestrian recognition from LIDAR data / Michalis A. Savelonas in Computer Vision and image understanding, vol 171 (June 2018)
[article]
Titre : Spatially sensitive statistical shape analysis for pedestrian recognition from LIDAR data Type de document : Article/Communication Auteurs : Michalis A. Savelonas, Auteur ; Ioannis Pratikakis, Auteur ; Theoharis Theoharis, Auteur ; Georgios Thanellas, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 1 - 9 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse comparative
[Termes IGN] analyse de sensibilité
[Termes IGN] analyse spatiale
[Termes IGN] classification barycentrique
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] codage
[Termes IGN] détection de piéton
[Termes IGN] discrétisation spatiale
[Termes IGN] distribution de Fisher
[Termes IGN] données lidar
[Termes IGN] échantillonnage de données
[Termes IGN] image à basse résolution
[Termes IGN] reconnaissance de formesRésumé : (auteur) Range-based pedestrian recognition is instrumental towards the development of autonomous driving and driving assistance systems. This work introduces encoding methods for pedestrian recognition, based on statistical shape analysis of 3D LIDAR data. The proposed approach has two variants, based on the encoding of local shape descriptors either in a spatially agnostic or spatially sensitive fashion. The latter method derives more detailed cues, by enriching the ‘gross’ information reflected by overall statistics of local shape descriptors, with ‘fine-grained’ information reflected by statistics associated with spatial clusters. Experiments on artificial LIDAR datasets, which include challenging samples, as well as on a large scale dataset of real LIDAR data, lead to the conclusion that both variants of the proposed approach (i) obtain high recognition accuracy, (ii) are robust against low-resolution sampling, (iii) are robust against increasing distance, and (iv) are robust against non-standard shapes and poses. On the other hand, the spatially-sensitive variant is more robust against partial occlusion and bad clustering. Numéro de notice : A2018-586 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.cviu.2018.06.001 Date de publication en ligne : 15/06/2018 En ligne : https://www.sciencedirect.com/science/article/pii/S1077314218300766 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92439
in Computer Vision and image understanding > vol 171 (June 2018) . - pp 1 - 9[article]Uncertainties in tree cover maps of Sub-Saharan Africa and their implications for measuring progress towards CBD Aichi Targets / Dorit Gross in Remote sensing in ecology and conservation, vol 4 n° 2 (June 2018)
[article]
Titre : Uncertainties in tree cover maps of Sub-Saharan Africa and their implications for measuring progress towards CBD Aichi Targets Type de document : Article/Communication Auteurs : Dorit Gross, Auteur ; Frédéric Achard, Auteur ; Grégoire Dubois, Auteur ; Andreas Brink, Auteur ; Herbert H.T. Prins, Auteur Année de publication : 2018 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Afrique subsaharienne
[Termes IGN] analyse diachronique
[Termes IGN] carte forestière
[Termes IGN] habitat (nature)
[Termes IGN] image Landsat-ETM+
[Termes IGN] image Landsat-TM
[Termes IGN] image Terra-MODIS
[Termes IGN] incertitude géométrique
[Termes IGN] politique de conservation (biodiversité)Résumé : (auteur) The growing access to Earth Observations and processing capabilities have stimulated the production of global and regional products that are commonly used to assess tree-covered habitats and their changes. The popularity of these products has led to their use for defining baselines and to assess progress in conserving natural habitats, in particular, in the context of the conservation targets to 2020 set by the UN Convention on Biological Diversity. In this paper, we reviewed three tree cover products commonly used over Sub-Saharan Africa: (1) MODIS Vegetation Continuous Field percent tree cover map, (2) Global Forest Change map and (3) TREES product. Over a systematic sample of 2045 map subsets, each having a size of 10 × 10 km², we calculated the extent and change of tree cover from each product for the period between 2000 and 2010. Our statistical and spatial comparison shows noticeable discrepancies between the three products, which lead to uncertainties when assessing tree cover across varying ecosystems. These differences are highest in habitats where tree cover is fragmented or reaches medium density levels and overlap with areas of high economic development potential, where habitat changes are likely to occur in the near future. We discuss these findings in the context of using these remotely sensed tree cover products to support current global biodiversity conservation policies. Numéro de notice : A2018-004 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1002/rse2.52 En ligne : https://doi.org/10.1002/rse2.52 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88737
in Remote sensing in ecology and conservation > vol 4 n° 2 (June 2018)[article]Documents numériques
en open access
Uncertainties in tree cover maps - pdf éditeurAdobe Acrobat PDF 3D reconstruction from multi-view VHR-satellite images in MicMac / Ewelina Rupnik in ISPRS Journal of photogrammetry and remote sensing, vol 139 (May 2018)
[article]
Titre : 3D reconstruction from multi-view VHR-satellite images in MicMac Type de document : Article/Communication Auteurs : Ewelina Rupnik , Auteur ; Marc Pierrot-Deseilligny , Auteur ; Arthur Delorme, Auteur Année de publication : 2018 Projets : TOSCA / Article en page(s) : pp 201 - 211 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] carte de profondeur
[Termes IGN] compensation par bloc
[Termes IGN] image Pléiades-HR
[Termes IGN] image Worldview
[Termes IGN] MicMac
[Termes IGN] modèle numérique de surface
[Termes IGN] modèle par fonctions rationnelles
[Termes IGN] programmation dynamiqueRésumé : (Auteur) This work addresses the generation of high quality digital surface models by fusing multiple depths maps calculated with the dense image matching method. The algorithm is adapted to very high resolution multi-view satellite images, and the main contributions of this work are in the multi-view fusion. The algorithm is insensitive to outliers, takes into account the matching quality indicators, handles non-correlated zones (e.g. occlusions), and is solved with a multi-directional dynamic programming approach. No geometric constraints (e.g. surface planarity) or auxiliary data in form of ground control points are required for its operation. Prior to the fusion procedures, the RPC geolocation parameters of all images are improved in a bundle block adjustment routine. The performance of the algorithm is evaluated on two VHR (Very High Resolution)-satellite image datasets (Pléiades, WorldView-3) revealing its good performance in reconstructing non-textured areas, repetitive patterns, and surface discontinuities. Numéro de notice : A2018-117 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.03.016 Date de publication en ligne : 20/03/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.03.016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89553
in ISPRS Journal of photogrammetry and remote sensing > vol 139 (May 2018) . - pp 201 - 211[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-2018051 RAB Revue Centre de documentation En réserve L003 Disponible An object-based approach for mapping forest structural types based on low-density LiDAR and multispectral imagery / Luis Angel Ruiz in Geocarto international, vol 33 n° 5 (May 2018)
[article]
Titre : An object-based approach for mapping forest structural types based on low-density LiDAR and multispectral imagery Type de document : Article/Communication Auteurs : Luis Angel Ruiz, Auteur ; Jorge Abel Recio, Auteur ; Pablo Crespo-Peremarch, Auteur ; Marta Sapena Moll, Auteur Année de publication : 2018 Article en page(s) : pp 443 - 457 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] arbre de décision
[Termes IGN] biomasse (combustible)
[Termes IGN] carte forestière
[Termes IGN] classification barycentrique
[Termes IGN] classification orientée objet
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt méditerranéenne
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Worldview
[Termes IGN] modèle de simulation
[Termes IGN] structure d'un peuplement forestierRésumé : (Auteur) Mapping forest structure variables provides important information for the estimation of forest biomass, carbon stocks, pasture suitability or for wildfire risk prevention and control. The optimization of the prediction models of these variables requires an adequate stratification of the forest landscape in order to create specific models for each structural type or strata. This paper aims to propose and validate the use of an object-oriented classification methodology based on low-density LiDAR data (0.5 m−2) available at national level, WorldView-2 and Sentinel-2 multispectral imagery to categorize Mediterranean forests in generic structural types. After preprocessing the data sets, the area was segmented using a multiresolution algorithm, features describing 3D vertical structure were extracted from LiDAR data and spectral and texture features from satellite images. Objects were classified after feature selection in the following structural classes: grasslands, shrubs, forest (without shrubs), mixed forest (trees and shrubs) and dense young forest. Four classification algorithms (C4.5 decision trees, random forest, k-nearest neighbour and support vector machine) were evaluated using cross-validation techniques. The results show that the integration of low-density LiDAR and multispectral imagery provide a set of complementary features that improve the results (90.75% overall accuracy), and the object-oriented classification techniques are efficient for stratification of Mediterranean forest areas in structural- and fuel-related categories. Further work will be focused on the creation and validation of a different prediction model adapted to the various strata. Numéro de notice : A2018-140 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2016.1265595 Date de publication en ligne : 28/11/2016 En ligne : https://doi.org/10.1080/10106049.2016.1265595 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89690
in Geocarto international > vol 33 n° 5 (May 2018) . - pp 443 - 457[article]Comparison of total water vapour content in the Arctic derived from GNSS, AIRS, MODIS and SCIAMACHY / Dunya Alraddawi in Atmospheric measurement techniques, vol 11 n° 5 (May 2018)
[article]
Titre : Comparison of total water vapour content in the Arctic derived from GNSS, AIRS, MODIS and SCIAMACHY Type de document : Article/Communication Auteurs : Dunya Alraddawi, Auteur ; Alain Sarkissian, Auteur ; Philippe Keckhut, Auteur ; Olivier Bock , Auteur ; Stefan Noël, Auteur ; Slimane Bekki, Auteur ; Abdanour Irbah, Auteur ; Mustapha Meftah, Auteur ; Chantal Claud, Auteur Année de publication : 2018 Projets : GNSS4SWEC / , VEGAN / Bock, Olivier Article en page(s) : pp 2949 - 2965 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale
[Termes IGN] analyse comparative
[Termes IGN] Arctique
[Termes IGN] Atmospheric Infrared Sounder
[Termes IGN] données GNSS
[Termes IGN] données météorologiques
[Termes IGN] erreur systématique
[Termes IGN] image Aqua-MODIS
[Termes IGN] image Terra-MODIS
[Termes IGN] nébulosité
[Termes IGN] série temporelle
[Termes IGN] teneur en vapeur d'eauRésumé : (auteur) Atmospheric water vapour plays a key role in the Arctic radiation budget, hydrological cycle and hence climate, but its measurement with high accuracy remains an important challenge. Total column water vapour (TCWV) datasets derived from ground-based GNSS measurements are used to assess the quality of different existing satellite TCWV datasets, namely from the Moderate Resolution Imaging Spectroradiometer (MODIS), the Atmospheric Infrared Sounder (AIRS) and the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY). The comparisons between GNSS and satellite data are carried out for three reference Arctic observation sites (Sodankylä, Ny-Ålesund and Thule) where long homogeneous GNSS time series of more than a decade (2001–2014) are available. We select hourly GNSS data that are coincident with overpasses of the different satellites over the three sites and then average them into monthly means that are compared with monthly mean satellite products for different seasons. The agreement between GNSS and satellite time series is generally within 5 % at all sites for most conditions. The weakest correlations are found during summer. Among all the satellite data, AIRS shows the best agreement with GNSS time series, though AIRS TCWV is often slightly too high in drier atmospheres (i.e. high-latitude stations during autumn and winter). SCIAMACHY TCWV data are generally drier than GNSS measurements at all the stations during the summer. This study suggests that these biases are associated with cloud cover, especially at Ny-Ålesund and Thule. The dry biases of MODIS and SCIAMACHY observations are most pronounced at Sodankylä during the snow season (from October to March). Regarding SCIAMACHY, this bias is possibly linked to the fact that the SCIAMACHY TCWV retrieval does not take accurately into account the variations in surface albedo, notably in the presence of snow with a nearby canopy as in Sodankylä. The MODIS bias at Sodankylä is found to be correlated with cloud cover fraction and is also expected to be affected by other atmospheric or surface albedo changes linked for instance to the presence of forests or anthropogenic emissions. Overall, the results point out that a better estimation of seasonally dependent surface albedo and a better consideration of vertically resolved cloud cover are recommended if biases in satellite measurements are to be reduced in the polar regions. Numéro de notice : A2018-240 Affiliation des auteurs : LASTIG LAREG+Ext (2012-mi2018) Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/amt-11-2949-2018 Date de publication en ligne : 18/05/2018 En ligne : https://doi.org/10.5194/amt-11-2949-2018 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90215
in Atmospheric measurement techniques > vol 11 n° 5 (May 2018) . - pp 2949 - 2965[article]Improving the analysis of biogeochemical patterns associated with internal waves in the strait of Gibraltar using remote sensing images / Gabriel Navarro in Estuarine, Coastal and Shelf Science, vol 204 (May 2018)PermalinkA new scheme for urban impervious surface classification from SAR images / Hongsheng Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 139 (May 2018)PermalinkCartographie des défoliations du massif forestier du Pays des étangs en Lorraine : Apports potentiels de la télédétection / Thierry Bélouard in Revue forestière française, vol 70 n° 5 (2018)PermalinkGeneric rule-sets for automated detection of urban tree species from very high-resolution satellite data / Razieh Shojanoori in Geocarto international, vol 33 n° 4 (April 2018)PermalinkMapping spatial variability of foliar nitrogen in coffee (Coffea arabica L.) plantations with multispectral Sentinel-2 MSI data / Abel Chemura in ISPRS Journal of photogrammetry and remote sensing, vol 138 (April 2018)PermalinkTowards automatic SAR-optical stereogrammetry over urban areas using very high resolution imagery / Chunping Qiu in ISPRS Journal of photogrammetry and remote sensing, vol 138 (April 2018)PermalinkAccuracy assessment of different digital surface models / Ugur Alganci in ISPRS International journal of geo-information, vol 7 n° 3 (March 2018)PermalinkActive tectonics of the onshore Hengchun Fault using UAS DSM combined with ALOS PS-InSAR time series (Southern Taiwan) / Benoit Deffontaines in Natural Hazards and Earth System Sciences, vol 18 n° 3 ([01/03/2018])PermalinkGenerative street addresses from satellite imagery / İlke Demir in ISPRS International journal of geo-information, vol 7 n° 3 (March 2018)PermalinkHarmonic regression of Landsat time series for modeling attributes from national forest inventory data / Barry T. Wilson in ISPRS Journal of photogrammetry and remote sensing, vol 137 (March 2018)PermalinkMapping tree cover with Sentinel-2 data using the Support Vector Machine (SVM) / Anna Mirończuk in Geoinformation issues, Vol 9 n° 1 (2017)PermalinkRemote estimation of canopy leaf area index and chlorophyll content in Moso bamboo (Phyllostachys edulis (Carrière) J. Houz.) forest using MODIS reflectance data / Xiaojun Xu in Annals of Forest Science, vol 75 n° 1 (March 2018)PermalinkSensitivity analysis of pansharpening in hyperspectral change detection / Seyd Teymoor Seydi in Applied geomatics, vol 10 n° 1 (March 2018)PermalinkUnderstanding the temporal dimension of the red-edge spectral region for forest decline detection using high-resolution hyperspectral and Sentinel-2a imagery / Pablo J. Zarco-Tejada in ISPRS Journal of photogrammetry and remote sensing, vol 137 (March 2018)PermalinkAnalyse de l'incertitude et de la précision thématique de classifications GEOBIA d'une image WorldView-2 / François Messner in Revue Française de Photogrammétrie et de Télédétection, n° 216 (février 2018)PermalinkEstimating forest standing biomass in savanna woodlands as an indicator of forest productivity using the new generation WorldView-2 sensor / Timothy Dube in Geocarto international, vol 33 n° 2 (February 2018)PermalinkEstimation of forest aboveground biomass from HJ1B imagery using a canopy reflectance model and a forest growth model / Xinyun Wang in Geocarto international, vol 33 n° 2 (February 2018)PermalinkNouvelle méthode en cascade pour la classification hiérarchique multi-temporelle ou multi-capteur d'images satellitaires haute résolution / Ihsen Hedhli in Revue Française de Photogrammétrie et de Télédétection, n° 216 (février 2018)PermalinkAdapting an existing semi-automatized image processing chain to enable Sentinel-2 data classification. / Hiyam Elbadri (2018)PermalinkPermalinkAutomated delineation of wildfire areas using Sentinel-2 satellite imagery / Mira Weirather in GI Forum, vol 2018 n° 1 ([01/01/2018])PermalinkCartographie des déformations de surface sur l’île de Taiwan par interférométrie RADAR Sentinel-1 / Miloud Fekaouni (2018)PermalinkCartographier l'occupation du sol à grande échelle : optimisation de la photo-interprétation par segmentation d'image / Maxime Vitter (2018)PermalinkPermalinkClassification à très haute résolution (THR) spatiale et fusion d'occupation des sols (OCS) / Tristan Postadjian (2018)PermalinkClassification à très large échelle d'images satellite à très haute résolution spatiale par réseaux de neurones convolutifs / Tristan Postadjian (2018)PermalinkA comparative analysis of the NDVIg and NDVI3g in monitoring vegetation phenology changes in the Northern Hemisphere / Qing Chang in Geocarto international, vol 33 n° 1 (January 2018)PermalinkConception d’une méthode radar de suivi bimensuel des déforestations et d’une méthode optique de classification d’occupation des sols / Luc Baudoux (2018)PermalinkContribution actuelle de la calotte Antarctique à la variation du niveau marin / Clémence Chupin (2018)PermalinkCrop-rotation structured classification using multi-source sentinel images and LPIS for crop type mapping / Simon Bailly (2018)PermalinkDecision fusion of SPOT6 and multitemporal Sentinel2 images for urban area detection / Cyril Wendl (2018)PermalinkDétection de changement par imagerie radar sur les zones naturelles et agricoles en milieu tropical / Jérôme Lebreton (2018)PermalinkEstimation of surface roughness over bare agricultural soil from Sentinel-1 data / Mohammad Choker (2018)PermalinkEtude préalable à l'installation d'un coin radar sur le site de co-localisation de Calern / Guillaume Schmidt (2018)PermalinkEvaluation des performances des modèles numérique d’élévation issus de l’imagerie tri-stéréo Pléiades pour le suivi de l’évolution morphologique des dunes littorales / Mannaïg L'haridon (2018)PermalinkExploring image fusion of ALOS/PALSAR data and LANDSAT data to differentiate forest area / Saygin Abdikan in Geocarto international, vol 33 n° 1 (January 2018)PermalinkExploring the impact of seasonality on urban land-cover mapping using multi-season sentinel-1A and GF-1 WFV images in a subtropical monsoon-climate region / Tao Zhou in ISPRS International journal of geo-information, vol 7 n° 1 (January 2018)PermalinkPermalinkFusion tardive d’images SPOT-6/7 et de données multitemporelles Sentinel-2 pour la détection de la tache urbaine / Cyril Wendl (2018)PermalinkGeometric multi-wavelet total variation for SAR image time series analysis / Abdourrahmane M. Atto (2018)PermalinkA hybrid training approach for leaf area index estimation via Cubist and random forests machine-learning / Rasmus M. Houborg in ISPRS Journal of photogrammetry and remote sensing, vol 135 (January 2018)PermalinkUn inventaire forestier multisource pour la gestion des territoires / Dinesh Babu Irulappa-Pillai-Vijayakumar (2018)PermalinkLearning multiscale deep features for high-resolution satellite image scene classification / Qingshan Liu in IEEE Transactions on geoscience and remote sensing, vol 56 n° 1 (January 2018)PermalinkMapping grassland management intensity using Sentinel-2 satellite data / Marijke Elisabeth Bekkema in GI Forum, vol 2018 n° 1 ([01/01/2018])PermalinkMise en évidence de l’activité récente des failles du bassin de Naryn (Kyrgyzstan) à partir de données photogrammétriques Pléiades et drone : un nouvel apport pour l’aléa sismique / Aurélie Médard (2018)Permalink