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VD-LAB: A view-decoupled network with local-global aggregation bridge for airborne laser scanning point cloud classification / Jihao Li in ISPRS Journal of photogrammetry and remote sensing, vol 186 (April 2022)
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Titre : VD-LAB: A view-decoupled network with local-global aggregation bridge for airborne laser scanning point cloud classification Type de document : Article/Communication Auteurs : Jihao Li, Auteur ; Martin Weinmann, Auteur ; Xian Sun, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 19 - 33 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] agrégation de détails
[Termes IGN] apprentissage profond
[Termes IGN] précision de la classification
[Termes IGN] qualité du modèle
[Termes IGN] semis de points
[Termes IGN] télémétrie laser aéroportéRésumé : (Auteur) Airborne Laser Scanning (ALS) point cloud classification is a valuable and practical task in the fields of photogrammetry and remote sensing. It takes an extremely important role in many applications of surveying, monitoring, planning, production and living. Recently, driven by the wave of deep learning, the classification of ALS point clouds has also been gradually shifting from traditional feature design to careful deep network architecture construction. Although significant progress has been achieved by leveraging deep learning technology, there are still some matters demanding prompt solution: (1) the coupling phenomenon of high-level semantic features from multiple field-of-views; (2) information propagation without aggregated local–global features in different levels of symmetrical structure; (3) quite serious class-imbalanced distribution problems in large-scale ALS point clouds. In this paper, to tackle these matters, we propose a novel View-Decoupled Network with Local–global Aggregation Bridge (VD-LAB) model. More concretely, a View-Decoupled (VD) grouping method is set at the deepest layer of the network. Then, we establish a Local–global Aggregation Bridge (LAB) between down-sampling path and up-sampling path of the same level. After that, a Self-Amelioration (SA) loss is taken as the optimization objective to train the whole model in an end-to-end manner. Extensive experiments on four challenging ALS point cloud datasets (LASDU, US3D, ISPRS 3D and GML) demonstrate that our VD-LAB is able to achieve state-of-the-art performance in terms of Overall Accuracy (OA) and mean -score (e.g., reaching 88.01% and 78.42% for LASDU dataset, respectively) with very few model parameters and it possesses a strong generalization capability. In addition, the visualization of achieved results also reveals more satisfactory classification for some categories, such as Water in the US3D dataset and Powerline in the ISPRS 3D dataset. Ultimately, the effect of each module in VD-LAB is assessed in detailed ablation analyses as well. Numéro de notice : A2022-067 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2022.01.012 Date de publication en ligne : 10/02/2022 En ligne : https://doi.org/10.1016/j.isprsjprs.2022.01.012 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99789
in ISPRS Journal of photogrammetry and remote sensing > vol 186 (April 2022) . - pp 19 - 33[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2022041 SL Revue Centre de documentation Revues en salle Disponible 081-2022043 DEP-RECP Revue LaSTIG Dépôt en unité Exclu du prêt 081-2022042 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Two-phase forest inventory using very-high-resolution laser scanning / Henrik J. Persson in Remote sensing of environment, vol 271 (March- 2 2022)
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Titre : Two-phase forest inventory using very-high-resolution laser scanning Type de document : Article/Communication Auteurs : Henrik J. Persson, Auteur ; Kenneth Olofsson, Auteur ; Johan Holmgren, Auteur Année de publication : 2022 Article en page(s) : n° 112909 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse comparative
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] échantillonnage
[Termes IGN] forêt boréale
[Termes IGN] hauteur des arbres
[Termes IGN] inférence statistique
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] lasergrammétrie
[Termes IGN] modélisation de la forêt
[Termes IGN] peuplement forestier
[Termes IGN] Suède
[Termes IGN] télémétrie laser terrestre
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) In this study, we compared a two-phase laser-scanning-based forest inventory of stands versus a traditional field inventory using sample plots. The two approaches were used to estimate stem volume (VOL), Lorey's mean height (HL), Lorey's stem diameter (DL), and VOL per tree species in a study area in Sweden. The estimates were compared at the stand level with the harvested reference values obtained using a forest harvester. In the first phase, a helicopter acquired airborne laser scanning (ALS) data with >500 points/m2 along 50-m wide strips across the stands. These strips intersected systematic plots in phase two, where terrestrial laser scanning (TLS) was used to model DL for individual trees. In total, phase two included 99 plots across 10 boreal forest stands in Sweden (lat 62.9° N, long 16.9° E). The single trees were segmented in both the ALS and TLS data and linked to each other. The very-high-resolution ALS data enabled us to directly measure tree heights and also classify tree species using a convolutional neural network. Stem volume was predicted from the predicted DBH and the estimated height, using national models, and aggregated at the stand level. The study demonstrates a workflow to derive forest variables and stand-level statistics that has potential to replace many manual field inventories thanks to its time efficiency and improved accuracy. To evaluate the inventories, we estimated bias, RMSE, and precision, expressed as standard error. The laser-scanning-based inventory provided estimates with an accuracy considerably higher than the field inventory. The RMSE was 17 m3/ha (7.24%), 0.9 m (5.63%), and 16 mm (5.99%) for VOL, HL, and DL respectively. The tree species classification was generally successful and improved the three species-specific VOL estimates by 9% to 74%, compared to field estimates. In conclusion, the demonstrated laser-scanning-based inventory shows potential to replace some future forest inventories, thanks to the increased accuracy demonstrated empirically in the Swedish forest study area. Numéro de notice : A2022-249 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2022.112909 Date de publication en ligne : 22/01/2022 En ligne : https://doi.org/10.1016/j.rse.2022.112909 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100201
in Remote sensing of environment > vol 271 (March- 2 2022) . - n° 112909[article]Assessing the agreement of ICESat-2 terrain and canopy height with airborne lidar over US ecozones / Lonesome Malambo in Remote sensing of environment, vol 266 (December 2021)
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Titre : Assessing the agreement of ICESat-2 terrain and canopy height with airborne lidar over US ecozones Type de document : Article/Communication Auteurs : Lonesome Malambo, Auteur ; Sorin C. Popescu, Auteur Année de publication : 2021 Article en page(s) : n° 112711 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] biome
[Termes IGN] canopée
[Termes IGN] données altimétriques
[Termes IGN] données ICEsat
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] écorégion
[Termes IGN] Etats-Unis
[Termes IGN] hauteur des arbres
[Termes IGN] photon
[Termes IGN] semis de points
[Termes IGN] télémétrie laser aéroportéRésumé : (auteur) Despite its critical importance to carbon storage modeling, forest vertical structure remains poorly characterized over large areas. Canopy height estimates from current satellite missions such as ICESat-2 (Ice, Cloud, and land Elevation Satellite-2) offer promise to close this knowledge gap, but their validation is critically important to inform their measurement uncertainties and scientific utility. Using existing airborne laser scanning (ALS) data, the agreement of a variety of terrain and aboveground canopy height metrics including summary height statistics and percentiles, from ICESat-2’ Land, Water and Vegetation Elevation product (ATL08) product was assessed in 12 sites across six major biomes in the United States. The agreement between ATL08 and ALS heights was assessed using the mean bias (Bias, ATL08 – ALS), the mean absolute error (MAE) and their percent equivalents, percent bias (pBias) and percent MAE (pMAE), respectively. In general, the agreement between ATL08 and ALS terrain heights was high (Bias 0.18 m, pBias 0.1%) while canopy heights showed lower agreement (Bias −1.71 m, pBias −15.9%). Analyses by biome, time of acquisition and beam strength of the ICESat-2 photon data also showed generally higher agreement for ATL08 terrain than canopy heights. Analyses also showed the performance of ATL08 heights varied with canopy cover with ATL08 terrain heights showing the best agreement when canopy cover was between 40 and 70% while the best performance for ATL08 canopy heights was observed when canopy cover was greater than 80%. This observation, coupled with analyses by biome, indicate that ATL08 canopy heights are more suitable in relatively dense canopy environments such as conifer and broadleaf forests than relatively sparse environments such a temperate grassland and Savannas. Higher level canopy height percentiles (95th and 98th) showed higher agreement (mean Bias −12.5%) with ALS heights than lower percentiles (minimum, 25th, mean pBias ~39.2%). These findings indicate that ATL08 canopy heights show more promise for routine canopy height characterization using the 95th and 98% percentiles but is limited in characterizing intermediate vertical structure. The observed performance differences between ATL08 terrain and canopy heights are attributed to differences in photon sampling rates over terrain and canopy surfaces which, compounded with background noise in ICESat-2 photon data, led to different effectiveness for ATL08 processing routines in filtering terrain and off-terrain points. This assessment of the impact of a variety of factors provides the vegetation community with an understanding of the capabilities and limitations of height estimates from the ICESat-2 ATL08 product. Numéro de notice : A2021-922 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2021.112711 Date de publication en ligne : 24/09/2021 En ligne : https://doi.org/10.1016/j.rse.2021.112711 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99277
in Remote sensing of environment > vol 266 (December 2021) . - n° 112711[article]
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Titre : Atelier LiDAR mobile & aéroporté Type de document : Article/Communication Auteurs : Pierre Assali, Auteur Année de publication : 2021 Article en page(s) : pp 8 - 9 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] lidar mobile
[Termes IGN] semis de points
[Termes IGN] télémétrie laser aéroporté
[Termes IGN] traitement de données localiséesRésumé : (Auteur) Les 19 et 20 octobre 2021 s’est tenue la troisième édition de l’atelier LiDAR organisée et cofinancée par la CNR1, EDF, SNCF Réseau et MDINFINITY. Après une première édition organisée à l’aéroport Lyon Saint-Exupéry, les participants ont été, comme en 2020, accueillis dans un cadre chaleureux et dynamique à l’hôtel “Globe et Cecil” situé en plein cœur de la presqu’île lyonnaise. L’évènement a réuni environ 45 personnes, soit une augmentation de l’affluence approchant les 50 % vis-à-vis de l’édition 2020, témoignant ainsi d’un engouement certain de la communauté pour cette rencontre annuelle. Numéro de notice : A2021-845 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99164
in XYZ > n° 169 (décembre 2021) . - pp 8 - 9[article]Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité 112-2021041 SL Revue Centre de documentation Revues en salle En circulation
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Titre : Le Mont-Blanc mesuré au LiDAR héliporté Type de document : Article/Communication Auteurs : Mathieu Peyréga, Auteur Année de publication : 2021 Article en page(s) : pp 33 - 40 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] calotte glaciaire
[Termes IGN] données altimétriques
[Termes IGN] données GNSS
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] hélicoptère
[Termes IGN] modèle numérique de terrain
[Termes IGN] Mont-Blanc, massif du
[Termes IGN] précision des données
[Termes IGN] sommet (relief)
[Termes IGN] télémétrie laser aéroportéRésumé : (Auteur) Nous présentons une mesure de l’altitude du sommet du mont Blanc et du volume de sa calotte par méthode LiDAR héliporté de très haute densité. Cette méthode alternative aux expéditions d’alpinistes et aux techniques topographiques classiques permet une mesure de précision équivalente. Le bilan d’incertitude est présenté et rappelle que la source d’erreur principale est la propagation troposphérique, commune à la méthode GNSS terrestre mise en œuvre depuis une vingtaine d’années pour le suivi de ce sommet emblématique. Cette mesure réalisée à une quinzaine de jours d’intervalle de l’expédition traditionnelle permet également de donner une indication sur la stabilité à court terme des valeurs calculées. Numéro de notice : A2021-849 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99179
in XYZ > n° 169 (décembre 2021) . - pp 33 - 40[article]Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité 112-2021041 SL Revue Centre de documentation Revues en salle En circulation
Exclu du prêtIonospheric tomographic common clock model of undifferenced uncombined GNSS measurements / German Olivares-Pulido in Journal of geodesy, vol 95 n° 11 (November 2021)
PermalinkA method of extracting high-accuracy elevation control points from ICESat-2 altimetry data / Binbin Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 11 (November 2021)
PermalinkTowards the empirical determination of correlations in terrestrial laser scanner range observations and the comparison of the correlation structure of different scanners / Berit Schmitz in ISPRS Journal of photogrammetry and remote sensing, Vol 182 (December 2021)
PermalinkImpact of beam diameter and scanning approach on point cloud quality of terrestrial laser scanning in forests / Meinrad Abegg in IEEE Transactions on geoscience and remote sensing, vol 59 n° 10 (October 2021)
PermalinkThree-dimensional reconstruction of single input image based on point cloud / Yu Hou in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 7 (July 2021)
PermalinkAn innovative and automated method for characterizing wood defects on trunk surfaces using high-density 3D terrestrial LiDAR data / Van-Tho Nguyen in Annals of Forest Science [en ligne], vol 78 n° 2 (June 2021)
PermalinkGeometric calibration of satellite laser altimeters based on waveform matching / Shaoning Li in Photogrammetric record, vol 36 n° 174 (June 2021)
PermalinkValidating geoid models with marine GNSS measurements, sea surface models, and additional gravity observations in the Gulf of Finland / Timo Saari in Marine geodesy, vol 44 n° 3 (May 2021)
PermalinkHorizontal calibration of vessels with UASs / Casey O'Heran in Marine geodesy, vol 44 n° 2 (March 2021)
PermalinkDevelopment of German-Ukrainian cooperations for education and research in photogrammetry and laser scanning / Thomas Luhmann in Geo-spatial Information Science, vol 24 n° 1 (March 2021)
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