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données lidarSynonyme(s)levé par lidarVoir aussi |
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3D radiative transfer modeling over complex vegetation canopies and forest reconstruction from LIDAR measurements / Jianbo Qi (2019)
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Titre : 3D radiative transfer modeling over complex vegetation canopies and forest reconstruction from LIDAR measurements Type de document : Thèse/HDR Auteurs : Jianbo Qi, Auteur ; Jean-Philippe Gastellu-Etchegorry, Directeur de thèse ; Guangjian Yan, Directeur de thèse Editeur : Toulouse : Université de Toulouse 3 Paul Sabatier Année de publication : 2019 Importance : 154 p. Format : 21 x 30 cm Note générale : bibliographie
Thèse en vue de l'obtention du Doctorat de l'Université de Toulouse, Surfaces et interfaces continentales, hydrologieLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] couvert végétal
[Termes IGN] données lidar
[Termes IGN] forêt
[Termes IGN] indice foliaire
[Termes IGN] interface graphique
[Termes IGN] milieu anisotrope
[Termes IGN] modèle de transfert radiatif
[Termes IGN] modélisation 3D
[Termes IGN] rendu réaliste
[Termes IGN] scène 3D
[Termes IGN] semis de pointsIndex. décimale : THESE Thèses et HDR Résumé : (auteur) Remote sensing is needed for better managing vegetation covers. Hence, three-dimensional (3D) radiative transfer (RT) modeling is essential for understanding remote sensing signals of complex 3D vegetation covers. Due to the complexity of 3D models, one-dimensional (1D) RT models are commonly used to retrieve vegetation parameters, e.g., leaf area index (LAI), from remote sensing data. However, 1D models are not adapted to actual vegetation covers because they abstract them as schematic 1D layers, which is not realistic. Much effort is devoted to the conception of 3D RT models that can consider the 3D architecture of vegetation covers. However, developing an efficient 3D RT model that works on large and realistic scenes is still a challenging task. Major difficulties are the intensive computational costs of 3D RT simulation and the acquisition of detailed 3D canopy structures. Therefore, 3D RT models usually only work on abstracted scenes or small realistic scenes. Scene abstraction may cause uncertainties, and the small-scale approach is not compatible with most satellite observations (e.g., MODIS). The computer graphics community provides the most accurate and efficient models (i.e., renderers). However, the initial renderer models were not designed for accurate RT modeling, which explains the difficulty to use them for remote sensing applications. Recently emerged advanced techniques in computer graphics and light detection and ranging area (LiDAR) make it more possible to solve the above problems. 3D RT can be greatly accelerated due to the increasing computer power and improvement of rendering algorithms (e.g., ray-tracing acceleration and computational optimization). Also, 3D high-resolution information from LiDARs and photogrammetry become more accessible to reconstruct realistic 3D scenes. This approach requires new processing methods to combine 3D information and 3D RT models, which is of great importance for better remote sensing survey of vegetation. This thesis is focused on 1) Development of a 3D RT model based on recent ray-tracing techniques and 2) Retrieval of 3D leaf volume density (LVD) for constructing 3D forest scenes. This first chapter presents the development of an efficient 3D RT model, named LESS (LargE-Scale remote sensing data and image Simulation framework). LESS makes full use of ray-tracing algorithms. Specifically, it simulates multispectral BRF and scene radiative budget with a weighted forward photon tracing method, and sensor images (e.g., fisheye images) or large-scale (e.g. 1 km2) spectral images are simulated with a backward path tracing method. In the forward mode, a "virtual photon" algorithm is used to simulate accurate BRF with few photons. The backward mode is used to simulate thermal infrared images and also atmosphere RT. LESS efficiency and accuracy were demonstrated with a model intercomparison and field measurements. In addition, LESS has an easy-to-use graphic user interface (GUI) to input parameters, construct and visualize 3D scenes. 3D forest reconstruction is done with a simulated LiDAR dataset to assess approaches that retrieve LVD from airborne LiDAR data. The dataset is simulated with the discrete anisotropic radiative transfer model (DART). Note de contenu : 1- Introduction
2- LESS: Ray-tracing based 3D radiative transfer model
3- Accuracy evaluation of LESS
4- Hybrid scene structuring for accelerating 3D radiative transfer
5- Physical interpretation of leaf area index from LiDAR data
6- Voxel-based reconstruction and simulation of 3D forest scene
7- Conclusions and perspectivesNuméro de notice : 25915 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Thèse française Note de thèse : Thèse de Doctorat : Surfaces et interfaces continentales, hydrologie : Toulouse 3 : 2019 Organisme de stage : CESBIO nature-HAL : Thèse DOI : sans En ligne : https://hal.science/tel-02498603 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96024 Analysis of the usability of mobile laser scanning data in snowy conditions / Mathilde Letard (2019)
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Titre : Analysis of the usability of mobile laser scanning data in snowy conditions Type de document : Mémoire Auteurs : Mathilde Letard, Auteur Editeur : Champs-sur-Marne : Ecole nationale des sciences géographiques ENSG Année de publication : 2019 Importance : 67 p. Format : 21 x 30 cm Note générale : Bibliographie
Rapport de projet pluridisciplinaire, cycle ING2Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] Antarctique
[Termes IGN] chaîne de traitement
[Termes IGN] changement climatique
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] lidar mobile
[Termes IGN] manteau neigeux
[Termes IGN] modèle numérique de surface
[Termes IGN] modèle numérique de terrainIndex. décimale : PROJET Mémoires : Rapports de projet - stage des ingénieurs de 2e année Résumé : (Auteur) Les modèles climatiques sont essentiels dans la lutte contre le changement climatique, et les connaissances sur les environnements polaires nécessaires à leur création. Le projet GRAVLASER du Finnish Geospatial Research Institute a été créé dans le but d’approfondir la connaissance de l’Antarctique par le biais du LIDAR. Cette étude montre que le LIDAR mobile peut produire des modèles numériques de terrains enneigés de haute résolution et que ceux-ci sont assez précis pour réaliser des mesures de gravité et des études sur la neige. Elle démontre ainsi l’existence d’une option permettant de contourner les obstacles techniques créés par le climat très rude de l’Antarctique tout en permettant d’améliorer les modèles climatiques dans la région. Ce travail explore aussi l’influence des conditions d’acquisition des données et de leur traitement sur les modèles finaux et propose une chaîne de production et des outils de visualisation et de comparaison de ceux-ci. Note de contenu : Introduction
1. Context and characteristics of the study
1.1 Context and presentation of the data
1.2 State of the art on snow covered surfaces modelling
1.3 Method followed
2. Data processing
2.1 Pre-processing
2.2 Creation of the reference surface model
2.3 Testing of different DTM generating methods
3. Analysis of the output and the results
3.1 Results obtained using MLS in snowy conditions
3.2 Discussion
Conclusion
A. GANTT Diagram of the project
B. Calibration proofing
C. Distance threshold
D. Characteristics of the files
E. DTMs comparisons
F. Visualization tool
G. Comparison toolNuméro de notice : 26118 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Mémoire de projet pluridisciplinaire Organisme de stage : Finnish Geospatial Research Institute Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93860 Documents numériques
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Analysis of the usability of mobile laser scanning data... - pdf auteurAdobe Acrobat PDFAutomatic determination of stream networks from DEMs by using road network data to locate culverts / Ville Mäkinen in International journal of geographical information science IJGIS, Vol 33 n° 1-2 (January - February 2019)
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Titre : Automatic determination of stream networks from DEMs by using road network data to locate culverts Type de document : Article/Communication Auteurs : Ville Mäkinen, Auteur ; Juha Oksanen, Auteur ; Tapani Sarjakoski, Auteur ; Tapani Sarjakoski, Auteur Année de publication : 2019 Article en page(s) : pp 291 - 313 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] détection automatique
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] écoulement des eaux
[Termes IGN] Finlande
[Termes IGN] itération
[Termes IGN] modèle numérique de surface
[Termes IGN] réseau hydrographique
[Termes IGN] réseau routier
[Termes IGN] semis de points
[Termes IGN] Triangulated Irregular NetworkRésumé : (auteur) Determining stream networks automatically from digital elevation models is an issue that is actively being studied. The quality of elevation models has increased over time, but many hydrologically critical features, such as culverts, are often missing from the elevation data. To analyze the surficial water flow, one must either prepare a special elevation model or post-process an already-existing model. This study builds on the traditional, well-established method of determining the stream network from digital elevation models. We have extended the traditional method by locating culverts automatically, using road network data as an input. We show, by comparison to the reference data, that the culverts being most relevant for the stream network can be found with good accuracy. We demonstrate that by including the automatically located culverts in the automatic stream network determination, the quality of the generated network can be noticeably improved. Numéro de notice : A2019-021 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1530353 Date de publication en ligne : 11/10/2018 En ligne : https://doi.org/10.1080/13658816.2018.1530353 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91686
in International journal of geographical information science IJGIS > Vol 33 n° 1-2 (January - February 2019) . - pp 291 - 313[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2019011 RAB Revue Centre de documentation En réserve L003 Disponible Challenges in grassland mowing event detection with multimodal Sentinel images / Anatol Garioud (2019)
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Titre : Challenges in grassland mowing event detection with multimodal Sentinel images Type de document : Article/Communication Auteurs : Anatol Garioud , Auteur ; Sébastien Giordano
, Auteur ; Silvia Valero, Auteur ; Clément Mallet
, Auteur
Editeur : Saint-Mandé : Institut national de l'information géographique et forestière - IGN (2012-) Année de publication : 2019 Projets : 2-Pas d'info accessible - article non ouvert / Conférence : MultiTemp 2019, 10th International Workshop on the Analysis of Multitemporal Remote Sensing Images 05/08/2019 07/08/2019 Shanghai Chine Proceedings IEEE Importance : pp 1 - 4 Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] apprentissage profond
[Termes IGN] détection d'événement
[Termes IGN] données lidar
[Termes IGN] image multibande
[Termes IGN] image RapidEye
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Sentinel-SAR
[Termes IGN] image TerraSAR-X
[Termes IGN] méthode robuste
[Termes IGN] nébulosité
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] Perceptron multicouche
[Termes IGN] prairie
[Termes IGN] régression
[Termes IGN] réseau neuronal récurrent
[Termes IGN] série temporelle
[Termes IGN] surveillance de la végétationRésumé : (auteur) Permanent Grasslands (PG) are heterogeneous environments with high spatial and temporal dynamics, subject to increasing environmental challenges. This study aims to identify requirements, key constraining factors and solutions for robust and complete detection of Mowing Events. Remote sensing is a powerful tool to monitor and investigate Near-Real-Time and seasonally PG cover. Here, pros and cons of Sentinel-2 (S2) and Sentinel-1 (S1) time series exploitation for Mowing Events (MowEve) detection are analysed. A deep-based approach is proposed to obtain consistent and homogeneous biophysical parameter times series for MowEve detection. Recurrent Neural Networks are proposed as regression strategy allowing the synergistic integration of optical and Synthetic Aperture Radar data to reconstruct dense NDVI times series. Experimental results corroborates the interest of deriving consistent and homogeneous series of biophysical parameters for subsequent MowEve detection. Numéro de notice : C2019-028 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Autre URL associée : vers HAL Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/Multi-Temp.2019.8866914 Date de publication en ligne : 29/11/2019 En ligne : https://doi.org/10.1109/Multi-Temp.2019.8866914 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94538
Titre : Contour lines generation in karstic plateaus for topographic maps Type de document : Article/Communication Auteurs : Guillaume Touya , Auteur ; Hugo Boulze
, Auteur ; Anouk Schleich, Auteur ; Hervé Quinquenel
, Auteur
Editeur : International Cartographic Association ICA - Association cartographique internationale ACI Année de publication : 2019 Autre Editeur : Göttingen : Copernicus publications Collection : Proceedings of the ICA Projets : 1-Pas de projet / Conférence : ICC 2019, 29th International Cartographic Conference ICA, Mapping everything for everyone 15/07/2019 20/07/2019 Tokyo Japon Open Access Proceedings of the ICA Importance : 8 p. Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] carte topographique
[Termes IGN] contour
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] effondrement de terrain
[Termes IGN] grotte
[Termes IGN] Jura, massif du
[Termes IGN] karst
[Termes IGN] lissage de données
[Termes IGN] modèle numérique de terrain
[Termes IGN] QGISRésumé : (auteur) Contour lines are a key features of topographic maps as they make the comprehension of terrain more easy. But they are no longer drawn by cartographers, they are mostly automatically derived from digital terrain models. Despite real progress in this automated derivation, some specific terrain landscapes remain incorrectly depicted with such techniques, and this is the case for karstic plateaus full of sinkholes. This paper proposes a specific automated method to derive better contour lines in plateaus, particularly around sinkholes. The process first detects karstic plateaus with many sinkholes, as well as the individual sinkholes. Then, the DTM is smoothed to better reflect the terrain in the plateau and in its surroundings. As a third step, the contour lines around sinkholes are enhanced to draw legible round features that better reflect the real terrain. The process was implemented in a QGIS plugin and tested on a small area with a karstic plateau in the Jura mountain in France, and the cartographers of IGN, the French national mapping agency assessed the results as a great improvement compared to the generic automated process to derive contour lines. Numéro de notice : C2019-011 Affiliation des auteurs : LASTIG COGIT (2012-2019) Thématique : GEOMATIQUE/IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.5194/ica-proc-2-133-2019 Date de publication en ligne : 10/07/2019 En ligne : http://dx.doi.org/10.5194/ica-proc-2-133-2019 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93259 Voir aussiDocuments numériques
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Contour lines generation - pdf éditeurAdobe Acrobat PDFCorrecting for nondetection in estimating forest characteristics from single-scan terrestrial laser measurements / Mikko Kuronen in Canadian Journal of Forest Research, vol 49 n° 1 (janvier 2019)
PermalinkDétection et localisation d'objets 3D par apprentissage profond en topologie capteur / Pierre Biasutti (2019)
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PermalinkEarth observation, remote sensing and geoscientific ground investigations for archaeological and heritage research / Deodato Tapete (2019)
PermalinkEstimation de profondeur à partir d'images monoculaires par apprentissage profond / Michel Moukari (2019)
PermalinkPermalinkForest inventory sensitivity to UAS-based image processing algorithms / Bonifasius Maturbongs in Annals of forest research, vol 62 n° 1 (January - June 2019)
PermalinkA growth-model-driven technique for tree stem diameter estimation by using airborne LiDAR data / Claudia Paris in IEEE Transactions on geoscience and remote sensing, vol 57 n° 1 (January 2019)
PermalinkIntegration of lidar data and GIS data for point cloud semantic enrichment at the point level / Harith Aljumaily in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 1 (January 2019)
PermalinkIs field-measured tree height as reliable as believed – A comparison study of tree height estimates from field measurement, airborne laser scanning and terrestrial laser scanning in a boreal forest / Yunsheng Wang in ISPRS Journal of photogrammetry and remote sensing, vol 147 (January 2019)
PermalinkLU-Net, An efficient network for 3D LiDAR point cloud semantic segmentation based on end-to-end-learned 3D features and U-Net / Pierre Biasutti (2019)
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