Centre de documentation
scientifique

Accuracy analysis of UAV photogrammetry using RGB and multispectral sensors / Nikola Santrač in Geodetski vestnik, vol 67 n° 4 (December 2023)  

Public [article]  inGeodetski vestnik > vol 67 n° 4 (December 2023) . - pp 459 - 472 Titre : Accuracy analysis of UAV photogrammetry using RGB and multispectral sensors Type de document : Article/Communication Auteurs : Nikola Santrač, Auteur ; Pavel Benka, Auteur ; Mehmed Batilović, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : pp 459 - 472 Note générale : bibliographie Langues : Anglais (eng) Slovène (slv) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] image captée par drone [Termes IGN] image multibande [Termes IGN] image RVB [Termes IGN] modèle géométrique de prise de vue [Termes IGN] point d'appui [Termes IGN] positionnement cinématique en temps réel [Termes IGN] qualité des données Résumé : (auteur) In recent years, unmanned aerial vehicles (UAVs) have become increasingly important as a tool for quickly collecting high-resolution (spatial and spectral) imagery of the Earth's surface. The final products are highly dependent on the choice of values for various parameters in flight planning, the type of sensors, and the processing of the data. In this paper ground control points (GCPs) were first measured using the Global Navigation Satellite System (GNSS) Real-Time Kinematic (RTK) method, and then due to the low height accuracy of the GNSS RTK method all points were measured using a detailed leveling method. This study aims to provide a basic assessment of quality, including four main aspects: (1) the difference between an RGB sensor and a five-band multispectral sensor on accuracy and the amount of data, (2) the impact of the number of GCPs on the accuracy of the final products, (3) the impact of different altitudes and cross flight strips, and (4) the accuracy analysis of multi-altitude models. The results suggest that the type of sensor, flight configuration, and GCP setup strongly affect the quality and quantity of the final product data while creating a multi-altitude model does not result in the expected quality of data. With its unique combination of sensors and parameters, the results and recommendations presented in this paper can assist professionals and researchers in their future work. Numéro de notice : A2023-241 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.15292/geodetski-vestnik.2023.04.459-472 Date de publication en ligne : 01/12/2023 En ligne : https://dx.doi.org/10.15292/geodetski-vestnik.2023.04.459-472 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103604 [article]

Combination of Terrestrial Laser Scanning and Unmanned Aerial Vehicle Photogrammetry for Heritage Building Information Modeling: A Case Study of Tarsus St. Paul Church / Şafak Fidan in Photogrammetric Engineering & Remote Sensing, PERS, vol 89 n° 12 (December 2023)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 89 n° 12 (December 2023) . - pp 753 - 760 Titre : Combination of Terrestrial Laser Scanning and Unmanned Aerial Vehicle Photogrammetry for Heritage Building Information Modeling: A Case Study of Tarsus St. Paul Church Type de document : Article/Communication Auteurs : Şafak Fidan, Auteur ; Ulvi Ali, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : pp 753 - 760 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] données lidar [Termes IGN] église [Termes IGN] image captée par drone [Termes IGN] modèle numérique [Termes IGN] patrimoine archéologique [Termes IGN] patrimoine immobilier Résumé : (auteur) Cultural heritage building information modeling (HBIM) is an emerging process allowing us to reconstruct built heritage virtually. The data of a digitally documented cultural heritage building offers significant advantages as it is accessible and modifiable by all professionals involved in the same or different projects. The most important factor affecting the accuracy and precision of the HBIM model is the ability to collect complete and accurate information about the physical structure. Combining terrestrial laser scanning (TLS) and unmanned aerial vehicle (UAV) photogrammetry point clouds is one of the most efficient ways to capture accurate digital data on the building. This study provides the foundation for creating an HBIM model for cultural heritage the coupling of spatial data with TLS and UAV. This paper aims to generate synergy between TLS and UAV point cloud data and ensure that the spatial database contains sufficient data to model historical objects with HBIM tendencies. Numéro de notice : A2023-238 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.23-00031R2 En ligne : https://doi.org/10.14358/PERS.23-00031R2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103599 [article]

Automated extraction and validation of Stone Pine (Pinus pinea L.) trees from UAV-based digital surface models / Asli Ozdarici-Ok in Geo-spatial Information Science, vol 26 n° inconnu ([01/08/2023])  

Public [article]  inGeo-spatial Information Science > vol 26 n° inconnu [01/08/2023] Titre : Automated extraction and validation of Stone Pine (Pinus pinea L.) trees from UAV-based digital surface models Type de document : Article/Communication Auteurs : Asli Ozdarici-Ok, Auteur ; Ali Ozgun Ok, Auteur ; et al., Auteur Année de publication : 2023 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] image captée par drone [Termes IGN] modèle numérique de surface [Termes IGN] Pinus pinea [Termes IGN] semis de points [Termes IGN] Turquie Résumé : (auteur) Stone Pine (Pinus pinea L.) is currently the pine species with the highest commercial value with edible seeds. In this respect, this study introduces a new methodology for extracting Stone Pine trees from Digital Surface Models (DSMs) generated through an Unmanned Aerial Vehicle (UAV) mission. We developed a novel enhanced probability map of local maxima that facilitates the computation of the orientation symmetry by means of new probabilistic local minima information. Four test sites are used to evaluate our automated framework within one of the most important Stone Pine forest areas in Antalya, Turkey. A Hand-held Mobile Laser Scanner (HMLS) was utilized to collect the reference point cloud dataset. Our findings confirm that the proposed methodology, which uses a single DSM as an input, secures overall pixel-based and object-based F1-scores of 88.3% and 97.7%, respectively. The overall median Euclidean distance revealed between the automatically extracted stem locations and the manually extracted ones is computed to be 36 cm (less than 4 pixels), demonstrating the effectiveness and robustness of the proposed methodology. Finally, the comparison with the state-of-the-art reveals that the outcomes of the proposed methodology outperform the results of six previous studies in this context. Numéro de notice : A2022-620 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10095020.2022.2090864 Date de publication en ligne : 21/07/2022 En ligne : https://doi.org/10.1080/10095020.2022.2090864 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101364 [article]

Multi-sensor airborne lidar requires intercalibration for consistent estimation of light attenuation and plant area density / Grégoire Vincent in Remote sensing of environment, vol 286 (March 2023)  

Public [article]  inRemote sensing of environment > vol 286 (March 2023) . - n° 113442 Titre : Multi-sensor airborne lidar requires intercalibration for consistent estimation of light attenuation and plant area density Type de document : Article/Communication Auteurs : Grégoire Vincent, Auteur ; Philippe Verley, Auteur ; Benjamin Brede, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 113442 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes IGN] canopée [Termes IGN] densité de la végétation [Termes IGN] données lidar [Termes IGN] forêt tropicale [Termes IGN] Guyane (département français) [Termes IGN] image captée par drone [Termes IGN] plan de vol [Termes IGN] rayonnement lumineux [Termes IGN] réflectance végétale [Termes IGN] semis de points [Termes IGN] zone d'intérêt Résumé : (auteur) Leaf area is a key structural characteristic of forest canopies because of the role of leaves in controlling many biological and physical processes occurring at the biosphere-atmosphere transition. High pulse density Airborne Laser Scanning (ALS) holds promise to provide spatially resolved and accurate estimates of plant area density (PAD) in forested landscapes, a key step in understanding forest functioning: phenology, carbon uptake, transpiration, radiative balance etc. Inconsistencies between different ALS sensors is a barrier to generating globally harmonised PAD estimates. The basic assumption on which PAD estimation is based is that light attenuation is proportional to vegetation area density. This study shows that the recorded extinction strongly depends on target detectability which is influenced by laser characteristics (power, sensitivity, wavelength). Three different airborne laser scanners were flown over a wet tropical forest at the Paracou research station in French Guiana. Different sensors, flight heights and transmitted power levels were compared. Light attenuation was retrieved with an open source ray-tracing code (http://amapvox.org). Direct comparison revealed marked differences (up-to 25% difference in profile-averaged light attenuation rate and 50% difference at particular heights) that could only be explained by differences in scanner characteristics. We show how bias which may occur under various acquisition conditions can generally be mitigated by a sensor intercalibration. Alignment of light weight lidar attenuation profiles to ALS reference attenuation profiles is not always satisfactory and we discuss what are the likely sources of discrepancies. Neglecting the dependency of apparent light attenuation on scanner properties may lead to biases in estimated vegetation density commensurate to those affecting light attenuation estimates. Applying intercalibration procedures supports estimation of plant area density independent of acquisition characteristics. Numéro de notice : A2023-169 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2022.113442 Date de publication en ligne : 06/01/2023 En ligne : https://doi.org/10.1016/j.rse.2022.113442 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102928 [article]

Validation of Island 3D-mapping based on UAV spatial point cloud optimization: a case study in Dongluo Island of China / Jian Wu in Photogrammetric Engineering & Remote Sensing, PERS, vol 89 n° 3 (March 2023)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 89 n° 3 (March 2023) . - pp 173 - 182 Titre : Validation of Island 3D-mapping based on UAV spatial point cloud optimization: a case study in Dongluo Island of China Type de document : Article/Communication Auteurs : Jian Wu, Auteur ; Shifeng Fu, Auteur ; Peng Chen, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : pp 173 - 182 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] cartographie 3D [Termes IGN] Chine [Termes IGN] île [Termes IGN] image captée par drone [Termes IGN] modélisation 3D [Termes IGN] semis de points [Termes IGN] télédétection aérienne Résumé : (Auteur) The unmanned aerial vehicle (UAV) remote sensing is of small volume, low cost, fine timeliness, and high spatial resolution, and has the special advantage on island surveying. Focus on the inaccurate elevation of non-ground point cloud without lidar device, this study explored a methodology for island three-dimensional (3D) mapping and modelling based on spatial point clouds optimization with a K-Nearest Neighbors Adaptive Inverse Distance Weighted (K-AIDW) interpolation algorithm. By classifying the UAV point clouds into ground, vegatetation, and structure, the K-AIDW algorithm was applied to optimize the elevations of non-ground point clouds (vegetation and structure) to recalculate Z values. The aerophotogrammetry result was generated based on the optimized spatial point clouds. Finally, the 3D model of Dongluo Island was reconstructed and rendered in Metashape. The accuracy evaluation result shows that the max-errors of ground control points (–0.0154 in X, 0.0305 in Y, and 0.0133 in Z) and the checkpoints (–0.091 in X, –0.176 in Y, and 0.338 in Z) can meet the error-tolerance requirements of the corresponding terrain on the 1:500 scale set by the national standard of GB/T 23236-2009 in China. It is found that the K-AIDW algorithm displayed the best Z accuracy (root-mean-square error of 0.2538) compared with IDW (0.3668) and no-optimized (1.6012), proving it is an effective methodology for improving 3D-modelling accuracy of island. Numéro de notice : A2023-172 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.22-00109R2 Date de publication en ligne : 01/03/2023 En ligne : https://doi.org/10.14358/PERS.22-00109R2 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102923 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
105-2023031	SL	Revue	Centre de documentation	Revues en salle	Disponible

Comparative analysis of different CNN models for building segmentation from satellite and UAV images / Batuhan Sariturk in Photogrammetric Engineering & Remote Sensing, PERS, vol 89 n° 2 (February 2023)  

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Detection of growth change of young forest based on UAV RGB images at single-tree level / Xiaocheng Zhou in Forests, vol 14 n° 1 (January 2023)  

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Geospatial-based machine learning techniques for land use and land cover mapping using a high-resolution unmanned aerial vehicle image / Taposh Mollick in Remote Sensing Applications: Society and Environment, RSASE, vol 29 (January 2023)  

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How to optimize the 2D/3D urban thermal environment: Insights derived from UAV LiDAR/multispectral data and multi-source remote sensing data / Rongfang Lyu in Sustainable Cities and Society, vol 88 (January 2023)  

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Des relevés sur mesure pour la sentinelle des Pyrénées / Marielle Mayo in Géomètre, n° 2209 (janvier 2023)

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Tree height-growth trajectory estimation using uni-temporal UAV laser scanning data and deep learning / Stefano Puliti in Forestry, an international journal of forest research, vol 96 n° 1 (January 2023)  

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Tree species classification in a typical natural secondary forest using UAV-borne LiDAR and hyperspectral data / Ying Quan in GIScience and remote sensing, vol 60 n° 1 (2023)  

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UAV DTM acquisition in a forested area – comparison of low-cost photogrammetry (DJI Zenmuse P1) and LiDAR solutions (DJI Zenmuse L1) / Martin Štroner in European journal of remote sensing, vol 56 n° 1 (2023)  

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Above ground biomass estimation from UAV high resolution RGB images and LiDAR data in a pine forest in Southern Italy / Mauro Maesano in iForest, biogeosciences and forestry, vol 15 n° 6 (December 2022)  

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Assessment of camera focal length influence on canopy reconstruction quality / Martin Denter in ISPRS Open Journal of Photogrammetry and Remote Sensing, vol 6 (December 2022)  

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