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Quality assessment of photogrammetric methods - A workflow for reproducible UAS orthomosaics / Marvin Ludwig in Remote sensing, vol 12 n° 22 (December 2020)  

Public [article]  inRemote sensing > vol 12 n° 22 (December 2020) . - n° 3831 Titre : Quality assessment of photogrammetric methods - A workflow for reproducible UAS orthomosaics Type de document : Article/Communication Auteurs : Marvin Ludwig, Auteur ; Christian M. Runge, Auteur ; Nicolas Friess, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : n° 3831 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] analyse diachronique [Termes IGN] capteur optique [Termes IGN] chaîne de traitement [Termes IGN] image à très haute résolution [Termes IGN] image captée par drone [Termes IGN] orthoimage [Termes IGN] orthoimage géoréférencée [Termes IGN] orthophotoplan numérique [Termes IGN] photogrammétrie aérienne [Termes IGN] point de vérification [Termes IGN] reproductibilité [Termes IGN] série temporelle Résumé : (auteur) Unmanned aerial systems (UAS) are cost-effective, flexible and offer a wide range of applications. If equipped with optical sensors, orthophotos with very high spatial resolution can be retrieved using photogrammetric processing. The use of these images in multi-temporal analysis and the combination with spatial data imposes high demands on their spatial accuracy. This georeferencing accuracy of UAS orthomosaics is generally expressed as the checkpoint error. However, the checkpoint error alone gives no information about the reproducibility of the photogrammetrical compilation of orthomosaics. This study optimizes the geolocation of UAS orthomosaics time series and evaluates their reproducibility. A correlation analysis of repeatedly computed orthomosaics with identical parameters revealed a reproducibility of 99% in a grassland and 75% in a forest area. Between time steps, the corresponding positional errors of digitized objects lie between 0.07 m in the grassland and 0.3 m in the forest canopy. The novel methods were integrated into a processing workflow to enhance the traceability and increase the quality of UAS remote sensing. Numéro de notice : A2020-794 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs12223831 date de publication en ligne : 22/11/2020 En ligne : https://doi.org/10.3390/rs12223831 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96573 [article]

Modeling strawberry biomass and leaf area using object-based analysis of high-resolution images / Zhen Guan in ISPRS Journal of photogrammetry and remote sensing, vol 163 (May 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 163 (May 2020) . - pp 171 - 186 Titre : Modeling strawberry biomass and leaf area using object-based analysis of high-resolution images Type de document : Article/Communication Auteurs : Zhen Guan, Auteur ; Amr Abd-Elrahman, Auteur ; Zhen Fan, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 171 - 186 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse d'image orientée objet [Termes IGN] biomasse [Termes IGN] canopée [Termes IGN] données spatiotemporelles [Termes IGN] hauteur de la végétation [Termes IGN] image à haute résolution [Termes IGN] indice foliaire [Termes IGN] orthophotoplan numérique [Termes IGN] phénologie [Termes IGN] semis de points [Termes IGN] structure-from-motion Résumé : (auteur) Quantifying canopy biophysical parameters is critical to agricultural research and farm management. In this study, strawberry dry biomass and leaf area were modeled statistically using high spatial and temporal resolution imagery. A mobile field data acquisition system was used to acquire thousands of very high resolution (~0.5 mm) close-range images seven times throughout the strawberry growing season. Ortho-mosaics and dense point clouds were generated through Structure from Motion (SfM) and used in Object-Based Image Analysis (OBIA) at the sub-leaf level to extract canopy structure variables such as planimetric canopy area, canopy average height, and canopy smoothness metric. Regression analysis was carried out using these image-derived canopy variables as predictors to model leaf area ( = 0.79; ten-fold cross-validation RMSE = 0.056 m2) and dry biomass ( = 0.84; ten-fold cross-validation RMSE = 7.72 g) obtained through destructive measurements. Results indicate consistent predictive power through the season and across 17 strawberry genotypes. The study showed that the canopy smoothness metric developed in this study as an indicator of canopy density could complement other variables (planimetric canopy area, canopy average height) that describe canopy geometric properties. Numéro de notice : A2020-139 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.02.021 date de publication en ligne : 18/03/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.02.021 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94757 [article]

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Statistical assessment of cartographic product from photogrammetry and fixed-wing UAV acquisition / Ademir Marques Junior in European journal of remote sensing, vol 53 n° 1 (2020)  

Public [article]  inEuropean journal of remote sensing > vol 53 n° 1 (2020) . - pp 27 - 39 Titre : Statistical assessment of cartographic product from photogrammetry and fixed-wing UAV acquisition Type de document : Article/Communication Auteurs : Ademir Marques Junior, Auteur ; Dalva Maria De Castro, Auteur ; Taina Thomassin Guimarães, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 27 - 39 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] Brésil [Termes IGN] cartographie topographique [Termes IGN] centrale hydroélectrique [Termes IGN] données GNSS [Termes IGN] image à haute résolution [Termes IGN] image captée par drone [Termes IGN] khi carré [Termes IGN] modèle numérique de surface [Termes IGN] norme cartographique [Termes IGN] orthophotoplan numérique [Termes IGN] positionnement cinématique en temps réel [Termes IGN] précision géométrique (imagerie) [Termes IGN] produit cartographique [Termes IGN] test de performance Résumé : (auteur) Geometric accuracy is an important attribute of cartographic products and UAV photogrammetry has been gaining market in topographic mapping thanks to high spatial and temporal resolution, however, they need proper evaluation following accuracy standards and protocols. Regarding this, this work evaluates products from digital photogrammetry from images acquired with a fixed-wing UAV (18Mpixel camera) in a 300-380m height flight over a Hydroelectric Power Plant (HPP) in Brazil. A dataset of 23 ground control points assessed with an RTK-GNSS (using natural targets) was validated with its homologous in the Digital Surface Model (DSM) and the orthomosaic, following a workflow in which the appropriate statistics were applied. Following parametric tests like the Students t-test and the Chi-square, we compared the results with the Brazilian Cartographic Standard for digital cartography, achieving minimum scale of 1: 20,000 (RMSE of 1.04 m) for the orthomosaic, and minimum scale of 1: 10,000 (RMSE of 1.31 m) for the elevation in the DSM, although, no special targets were used. As the 3D mapping generated using the photogrammetry still needs a protocol to evaluate the accuracy, this work applied a proposed workflow respecting the quality of the data to meet the requirements of the cartographic standard. Numéro de notice : A2020-165 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/22797254.2020.17179 date de publication en ligne : 28/01/2020 En ligne : https://doi.org/10.1080/22797254.2020.1717998 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94833 [article]

Segmenting mangrove ecosystems drone images using SLIC superpixels / Edward Zimudzi in Geocarto international, vol 34 n° 14 ([30/10/2019])  

Public [article]  inGeocarto international > vol 34 n° 14 [30/10/2019] . - pp 1648 - 1662 Titre : Segmenting mangrove ecosystems drone images using SLIC superpixels Type de document : Article/Communication Auteurs : Edward Zimudzi, Auteur ; Ian Sanders, Auteur ; Nicholas Rollings, Auteur ; Christian Omlin, Auteur Année de publication : 2019 Article en page(s) : pp 1648 - 1662 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] algorithme de superpixels [Termes IGN] classification par nuées dynamiques [Termes IGN] classification pixellaire [Termes IGN] écosystème [Termes IGN] Fidji [Termes IGN] image captée par drone [Termes IGN] mangrove [Termes IGN] modèle numérique de surface [Termes IGN] orthophotoplan numérique [Termes IGN] segmentation d'image [Termes IGN] SLIC algorithm Résumé : (auteur) Mangrove ecosystems play a very important ecological role on land–ocean interfaces in tropical regions. These ecosystems comprise of various tree species and aquatic animals, protecting the environment and providing a habitat that supports many living organisms including humans. The identification of image regions in mangrove ecosystems plays a significant role in ecosystem monitoring and conservation. Recent studies have suggested oversegmentation of colour images using superpixels as a solution to the segmentation of image regions. This study used the SLIC superpixel algorithm and k-means clustering to segment images taken from a camera mounted on a drone from a mangrove ecosystem in Fiji. The SLIC superpixel algorithm performed well to demarcate image regions with similar colour and texture information into patches and to use k-means for the segmentation of the whole image. These results lend support to the use of superpixel algorithms for the segmentation of mangrove ecosystems. Understanding how superpixels can be used for the segmentation of drone images will assist conservation efforts in mangrove ecosystems. Numéro de notice : A2019-539 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1497093 date de publication en ligne : 22/10/2018 En ligne : https://doi.org/10.1080/10106049.2018.1497093 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94114 [article]

Unmanned aerial vehicles (UAVs) for monitoring macroalgal biodiversity: comparison of RGB and multispectral imaging sensors for biodiversity assessments / Leigh Tait in Remote sensing, vol 11 n° 19 (October 2019)  

Public [article]  inRemote sensing > vol 11 n° 19 (October 2019) . - 18 p. Titre : Unmanned aerial vehicles (UAVs) for monitoring macroalgal biodiversity: comparison of RGB and multispectral imaging sensors for biodiversity assessments Type de document : Article/Communication Auteurs : Leigh Tait, Auteur ; Jochen Bind, Auteur ; Hannah Charan-Dixon, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : 18 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] algue [Termes IGN] biodiversité [Termes IGN] changement climatique [Termes IGN] estran [Termes IGN] habitat (nature) [Termes IGN] image captée par drone [Termes IGN] image multibande [Termes IGN] image RVB [Termes IGN] Kappa de Cohen [Termes IGN] Nouvelle-Zélande [Termes IGN] orthophotoplan numérique [Termes IGN] réflectance spectrale [Termes IGN] surveillance du littoral Résumé : (auteur) Developments in the capabilities and affordability of unmanned aerial vehicles (UAVs) have led to an explosion in their use for a range of ecological and agricultural remote sensing applications. However, the ubiquity of visible light cameras aboard readily available UAVs may be limiting the application of these devices for fine-scale, high taxonomic resolution monitoring. Here we compare the use of RGB and multispectral cameras deployed aboard UAVs for assessing intertidal and shallow subtidal marine macroalgae to a high taxonomic resolution. Our results show that the diverse spectral profiles of marine macroalgae naturally lend themselves to remote sensing and habitat classification. Furthermore, we show that biodiversity assessments, particularly in shallow subtidal habitats, are enhanced using six-band discrete wavelength multispectral sensors (81% accuracy, Cohen’s Kappa) compared to three-band broad channel RGB sensors (79% accuracy, Cohen’s Kappa) for 10 habitat classes. Combining broad band RGB signals and narrow band multispectral sensing further improved the accuracy of classification with a combined accuracy of 90% (Cohen’s Kappa). Despite notable improvements in accuracy with multispectral imaging, RGB sensors were highly capable of broad habitat classification and rivaled multispectral sensors for classifying intertidal habitats. High spatial scale monitoring of turbid exposed rocky reefs presents a unique set of challenges, but the limitations of more traditional methods can be overcome by targeting ideal conditions with UAVs. Numéro de notice : A2019-553 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs11192332 date de publication en ligne : 08/10/2019 En ligne : https://doi.org/10.3390/rs11192332 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94206 [article]

High-resolution large-area digital orthophoto map generation using LROC NAC images / Kaichang Di in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 7 (July 2019)  

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Orléans monte sa maquette virtuelle / Anonyme in Géomatique expert, n° 127 (avril - mai 2019)

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An evaluation of reflectance calibration methods for UAV spectral imagery / Jarrod Edwards in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 3 (March 2019)  

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Seamline network generation based on foreground segmentation for orthoimage mosaicking / Li Li in ISPRS Journal of photogrammetry and remote sensing, vol 148 (February 2019)  

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Altamétris : des drones et des rails / Anonyme in Géomatique expert, n° 122 (mai-juin 2018)

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Using UAVs for map creation and updating: A case study in Rwanda / Mila Koeva in Survey review, vol 50 n° 361 (July 2018)  

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A novel orthoimage mosaic method using a weighted A∗ algorithm : Implementation and evaluation / Maoteng Zheng in ISPRS Journal of photogrammetry and remote sensing, vol 138 (April 2018)  

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Saint-Quentin-en-Yvelines à 2,5 cm / Anonyme in Géomatique expert, n° 121 (mars - avril 2018)

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Active 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])  

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Seamline optimisation for urban aerial ortho‐image mosaicking using graph cuts / Yunsheng Zhang in Photogrammetric record, vol 33 n° 161 (March 2018)  

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