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Transferability and calibration of airborne laser scanning based mixed-effects models to estimate the attributes of sawlog-sized Scots pines / Lauri Korhonen in Silva fennica, vol 53 n° 3 (2019)
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Titre : Transferability and calibration of airborne laser scanning based mixed-effects models to estimate the attributes of sawlog-sized Scots pines Type de document : Article/Communication Auteurs : Lauri Korhonen, Auteur ; Jaakko Repola, Auteur ; Tomi Karjalainen, Auteur ; Petteri Packalen, Auteur ; Matti Maltamo, Auteur Année de publication : 2019 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] détection d'arbres
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] erreur systématique
[Termes IGN] estimation statistique
[Termes IGN] étalonnage de modèle
[Termes IGN] hauteur à la base du houppier
[Termes IGN] houppier
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] lasergrammétrie
[Termes IGN] Pinus sylvestris
[Termes IGN] placette d'échantillonnage
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Airborne laser scanning (ALS) data is nowadays often available for forest inventory purposes, but adequate field data for constructing new forest attribute models for each area may be lacking. Thus there is a need to study the transferability of existing ALS-based models among different inventory areas. The objective of our study was to apply ALS-based mixed models to estimate the diameter, height and crown base height of individual sawlog sized Scots pines (Pinus sylvestrisL.) at three different inventory sites in eastern Finland. Different ALS sensors and acquisition parameters were used at each site. Multivariate mixed-effects models were fitted at one site and the models were validated at two independent test sites. Validation was carried out by applying the fixed parts of the mixed models as such, and by calibrating them using 1–3 sample trees per plot. The results showed that the relative RMSEs of the predictions were 1.2–6.5 percent points larger at the test sites compared to the training site. Systematic errors of 2.4–6.2 percent points also emerged at the test sites. However, both the RMSEs and the systematic errors decreased with calibration. The results showed that mixed-effects models of individual tree attributes can be successfully transferred and calibrated to other ALS inventory areas in a level of accuracy that appears suitable for practical applications. Numéro de notice : A2019-641 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14214/sf.10179 Date de publication en ligne : 31/07/2019 En ligne : https://doi.org/10.14214/sf.10179 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93446
in Silva fennica > vol 53 n° 3 (2019)[article]Burn severity analysis in Mediterranean forests using maximum entropy model trained with EO-1 Hyperion and LiDAR data / Alfonso Fernández-Manso in ISPRS Journal of photogrammetry and remote sensing, vol 155 (September 2019)
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Titre : Burn severity analysis in Mediterranean forests using maximum entropy model trained with EO-1 Hyperion and LiDAR data Type de document : Article/Communication Auteurs : Alfonso Fernández-Manso, Auteur ; Carmen Quintano, Auteur ; Dar A. Roberts, Auteur Année de publication : 2019 Article en page(s) : pp 102 - 118 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse de mélange spectral d’extrémités multiples
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] entropie
[Termes IGN] forêt méditerranéenne
[Termes IGN] image EO1-Hyperion
[Termes IGN] incendie de forêtRésumé : (Auteur) All ecosystems and in particular ecosystems in Mediterranean climates are affected by fires. Knowledge of the drivers that most influence burn severity patterns as well an accurate map of post-fire effects are key tools for forest managers in order to plan an adequate post-fire response. Remote sensing data are becoming an indispensable instrument to reach both objectives. This work explores the relative influence of pre-fire vegetation structure and topography on burn severity compared to the impact of post-fire damage level, and evaluates the utility of the Maximum Entropy (MaxEnt) classifier trained with post-fire EO-1 Hyperion data and pre-fire LiDAR to model three levels of burn severity at high accuracy. We analyzed a large fire in central-eastern Spain, which occurred on 16–19 June 2016 in a maquis shrubland and Pinus halepensis forested area. Post-fire hyperspectral Hyperion data were unmixed using Multiple Endmember Spectral Mixture Analysis (MESMA) and five fraction images were generated: char, green vegetation (GV), non-photosynthetic vegetation, soil (NPVS) and shade. Metrics associated with vegetation structure were calculated from pre-fire LiDAR. Post-fire MESMA char fraction image, pre-fire structural metrics and topographic variables acted as inputs to MaxEnt, which built a model and generated as output a suitability surface for each burn severity level. The percentage of contribution of the different biophysical variables to the MaxEnt model depended on the burn severity level (LiDAR-derived metrics had a greater contribution at the low burn severity level), but MaxEnt identified the char fraction image as the highest contributor to the model for all three burn severity levels. The present study demonstrates the validity of MaxEnt as one-class classifier to model burn severity accurately in Mediterranean countries, when trained with post-fire hyperspectral Hyperion data and pre-fire LiDAR. Numéro de notice : A2019-313 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.isprsjprs.2019.07.003 Date de publication en ligne : 14/07/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.07.003 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93339
in ISPRS Journal of photogrammetry and remote sensing > vol 155 (September 2019) . - pp 102 - 118[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2019091 RAB Revue Centre de documentation En réserve L003 Disponible 081-2019093 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2019092 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Comparison of filtering algorithms used for DTM production from airborne lidar data: a case study in Bergama, Turkey / Baris Suleymanoglu in Geodetski vestnik, vol 63 n° 3 (September - November 2019)
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Titre : Comparison of filtering algorithms used for DTM production from airborne lidar data: a case study in Bergama, Turkey Type de document : Article/Communication Auteurs : Baris Suleymanoglu, Auteur ; Metin Soycan, Auteur Année de publication : 2019 Article en page(s) : pp 395 - 414 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] algorithme de filtrage
[Termes IGN] analyse comparative
[Termes IGN] convolution (signal)
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] modèle numérique de surface
[Termes IGN] modèle numérique de terrain
[Termes IGN] semis de points
[Termes IGN] test de performance
[Termes IGN] TurquieRésumé : (Auteur) A light detection and ranging (lidar) system is one of the most important technologies used for generating digital terrain models (DTMs). The point cloud data obtained by these systems consist of data gathered from ground and nonground features. To create a DTM with high resolution and accuracy, ground and nonground data must be separated. Numerous filtering algorithms have been developed for this purpose. The aim of this study was testing the filtering performance of six different filtering algorithms in four different test areas with different land cover were selected that had topographical features and characteristics. The algorithms were adaptive triangulated irregular network (ATIN), elevation threshold with an expand window (ETEW), maximum local slope (MLS), progressive morphology (PM), iterative polynomial fitting (IPF), and multiscale curvature classification (MCC) algorithms. In the results, all the filters performed well on a smooth surface and produced more errors in complex urban areas and rough terrain with dense vegetation. The IPF filtering algorithm generated the best results for the first three test areas (smooth landscape, urban areas and agricultural areas), while ETEW performed best in the fourth test area (steep areas with dense vegetation and infrastructure). Numéro de notice : A2019-502 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.15292/geodetski-vestnik.2019.03.395-414 En ligne : http://dx.doi.org/10.15292/geodetski-vestnik.2019.03.395-414 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93784
in Geodetski vestnik > vol 63 n° 3 (September - November 2019) . - pp 395 - 414[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 139-2019031 RAB Revue Centre de documentation En réserve L003 Disponible Delineation of vacant building land using orthophoto and lidar data object classification / Dejan Jenko in Geodetski vestnik, vol 63 n° 3 (September - November 2019)
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Titre : Delineation of vacant building land using orthophoto and lidar data object classification Type de document : Article/Communication Auteurs : Dejan Jenko, Auteur ; Mojca Foški, Auteur ; Krištof Oštir, Auteur ; Žiga Kokalj, Auteur Année de publication : 2019 Article en page(s) : pp 344 - 378 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] classification orientée objet
[Termes IGN] couche thématique
[Termes IGN] détection du bâti
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] logement
[Termes IGN] orthoimage
[Termes IGN] SlovénieRésumé : (Auteur) Exact data about the location and area of vacant building land have been a major issue in several Slovene municipalities. This article deals with automatic vacant building land delineation. The presented methodology is based on the object-based classification that derives the land cover layer from orthophoto and laser scanning data. With post-processing and data cleaning in GIS, we create the vacant building land layer. The methodology was tested in study areas in the Municipality of Trebnje. The results were compared to the vacant building land layer generated by visual interpretation (manual vectorisation). We found that the presented methodology of automatic delineation of vacant buildings can speed up the processing and lower the cost of manual vectorisation and, in particular, data updating but we cannot completely replace manual work. Numéro de notice : A2019-500 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.15292/geodetski-vestnik.2019.03.344-378 En ligne : http://dx.doi.org/10.15292/geodetski-vestnik.2019.03.344-378 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93782
in Geodetski vestnik > vol 63 n° 3 (September - November 2019) . - pp 344 - 378[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 139-2019031 RAB Revue Centre de documentation En réserve L003 Disponible Enhanced 3D mapping with an RGB-D sensor via integration of depth measurements and image sequences / Bo Wu in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 9 (September 2019)
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Titre : Enhanced 3D mapping with an RGB-D sensor via integration of depth measurements and image sequences Type de document : Article/Communication Auteurs : Bo Wu, Auteur ; Xuming Ge, Auteur ; Linfu Xie, Auteur ; Wu Chen, Auteur Année de publication : 2019 Article en page(s) : pp 633 - 642 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] carte d'intérieur
[Termes IGN] carte de profondeur
[Termes IGN] cartographie 3D
[Termes IGN] cartographie et localisation simultanées
[Termes IGN] données localisées 3D
[Termes IGN] état de l'art
[Termes IGN] image RVB
[Termes IGN] intégration de données
[Termes IGN] modélisation 3D
[Termes IGN] semis de points
[Termes IGN] séquence d'images
[Termes IGN] structure-from-motionRésumé : (Auteur) State-of-the-art visual simultaneous localization and mapping (SLAM) techniques greatly facilitate three-dimensional (3D) mapping and modeling with the use of low-cost red-green-blue-depth (RGB-D) sensors. However, the effective range of such sensors is limited due to the working range of the infra-red (IR) camera, which provides depth information, and thus the practicability of such sensors in 3D mapping and modeling is limited. To address this limitation, we present a novel solution for enhanced 3D mapping using a low-cost RGB-D sensor. We carry out state-of-the-art visual SLAM to obtain 3D point clouds within the mapping range of the RGB-D sensor and implement an improved structure-from-motion (SfM) on the collected RGB image sequences with additional constraints from the depth information to produce image-based 3D point clouds. We then develop a feature-based scale-adaptive registration to merge the gained point clouds to further generate enhanced and extended 3D mapping results. We use two challenging test sites to examine the proposed method. At these two sites, the coverage of both generated 3D models increases by more than 50% with the proposed solution. Moreover, the proposed solution achieves a geometric accuracy of about 1% in a measurement range of about 20 m. These positive experimental results not only demonstrate the feasibility and practicality of the proposed solution but also its potential. Numéro de notice : A2019-415 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.85.9.633 Date de publication en ligne : 01/09/2019 En ligne : https://doi.org/10.14358/PERS.85.9.633 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93542
in Photogrammetric Engineering & Remote Sensing, PERS > vol 85 n° 9 (September 2019) . - pp 633 - 642[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 105-2019091 SL Revue Centre de documentation Revues en salle Disponible Integration of LiDAR and multispectral images for rapid exposure and earthquake vulnerability estimation. Application in Lorca, Spain / Yolanda Torres in International journal of applied Earth observation and geoinformation, vol 81 (September 2019)
PermalinkPpC: a new method to reduce the density of lidar data. Does it affect the DEM accuracy? / Sandra Bujan in Photogrammetric record, vol 34 n° 167 (September 2019)
PermalinkReduction of measurement data before Digital Terrain Model generation vs. DTM generalisation / Wioleta Błaszczak-Bąk in Survey review, vol 51 n° 368 (September 2019)
PermalinkTopographie et archéologie, du cordeau au tout numérique : plus de 40 ans d'interactions / Bertrand Chazaly in XYZ, n° 160 (septembre 2019)
PermalinkValidating the use of object-based image analysis to map commonly recognized landform features in the United States / Samantha T. Arundel in Cartography and Geographic Information Science, Vol 46 n° 5 (September 2019)
PermalinkQuantifying the impact of trees on land surface temperature: a downscaling algorithm at city-scale / Elena Barbierato in European journal of remote sensing, vol 52 n° 4 (2019)
PermalinkAutomatic extraction of accurate 3D tie points for trajectory adjustment of mobile laser scanners using aerial imagery / Zille Hussnain in ISPRS Journal of photogrammetry and remote sensing, vol 154 (August 2019)
PermalinkExplanation for the seam line discontinuity in terrestrial laser scanner point clouds / Derek D. Lichti in ISPRS Journal of photogrammetry and remote sensing, vol 154 (August 2019)
PermalinkImproving public data for building segmentation from Convolutional Neural Networks (CNNs) for fused airborne lidar and image data using active contours / David Griffiths in ISPRS Journal of photogrammetry and remote sensing, vol 154 (August 2019)
PermalinkModelling of buildings from aerial LiDAR point clouds using TINs and label maps / Minglei Li in ISPRS Journal of photogrammetry and remote sensing, vol 154 (August 2019)
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