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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 descripteurs IGN] analyse d'image orientée objet [Termes descripteurs IGN] biomasse [Termes descripteurs IGN] canopée [Termes descripteurs IGN] données spatiotemporelles [Termes descripteurs IGN] hauteur de la végétation [Termes descripteurs IGN] image à haute résolution [Termes descripteurs IGN] indice foliaire [Termes descripteurs IGN] orthophotoplan numérique [Termes descripteurs IGN] phénologie [Termes descripteurs IGN] semis de points [Termes descripteurs 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 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 descripteurs IGN] Brésil [Termes descripteurs IGN] cartographie topographique [Termes descripteurs IGN] centrale hydroélectrique [Termes descripteurs IGN] données GNSS [Termes descripteurs IGN] image à haute résolution [Termes descripteurs IGN] image de drone [Termes descripteurs IGN] khi carré [Termes descripteurs IGN] modèle numérique de surface [Termes descripteurs IGN] norme cartographique [Termes descripteurs IGN] orthophotoplan numérique [Termes descripteurs IGN] positionnement cinématique en temps réel [Termes descripteurs IGN] précision géométrique (imagerie) [Termes descripteurs IGN] produit cartographique [Termes descripteurs 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 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 descripteurs IGN] algorithme de superpixels [Termes descripteurs IGN] classification par nuées dynamiques [Termes descripteurs IGN] classification pixellaire [Termes descripteurs IGN] écosystème [Termes descripteurs IGN] Fidji [Termes descripteurs IGN] image de drone [Termes descripteurs IGN] mangrove [Termes descripteurs IGN] modèle numérique de surface [Termes descripteurs IGN] orthophotoplan numérique [Termes descripteurs IGN] segmentation d'image [Termes descripteurs 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 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 descripteurs IGN] algue [Termes descripteurs IGN] biodiversité [Termes descripteurs IGN] changement climatique [Termes descripteurs IGN] estran [Termes descripteurs IGN] habitat (nature) [Termes descripteurs IGN] image de drone [Termes descripteurs IGN] image multibande [Termes descripteurs IGN] image RVB [Termes descripteurs IGN] Kappa de Cohen [Termes descripteurs IGN] Nouvelle-Zélande [Termes descripteurs IGN] orthophotoplan numérique [Termes descripteurs IGN] réflectance spectrale [Termes descripteurs 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 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)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 85 n° 7 (July 2019) . - pp 481 - 491 Titre : High-resolution large-area digital orthophoto map generation using LROC NAC images Type de document : Article/Communication Auteurs : Kaichang Di, Auteur ; Jia Mengna, Auteur ; Xin Xin, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 481 - 491 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Orthophotographie, orthoimage [Termes descripteurs IGN] Chine [Termes descripteurs IGN] compensation par bloc [Termes descripteurs IGN] erreur de positionnement [Termes descripteurs IGN] image à haute résolution [Termes descripteurs IGN] Lune [Termes descripteurs IGN] modèle géométrique de prise de vue [Termes descripteurs IGN] modèle numérique de terrain [Termes descripteurs IGN] orthoimage [Termes descripteurs IGN] orthophotoplan numérique [Termes descripteurs IGN] zone homogène Résumé : (auteur) The Chang'e-5 mission of China is planned to be launched in 2019 to the landing area near Mons Rümker located in Oceanus Procellarum. Aiming to generate a high-resolution and high-quality digital orthophoto map (DOM) of the planned landing area for supporting the mission and various scientific analyses, this study developed a systematic and effective method for large-area seamless DOM production. The mapping results of the Chang'e-5 landing area using over 700 Lunar Reconnaissance Orbiter Camera (LROC) Narrow Angle Camera (NAC) images are presented. The resultant seamless DOM has a resolution of 1.5 m, covers a large area of 20° in longitude and 4° in latitude, and is tied to SLDEM2015. The results demonstrate that the proposed method can reduce the geometric inconsistencies among the LROC NAC images to the subpixel level and the positional errors with respect to the reference digital elevation model to about one grid cell size. Numéro de notice : A2019-257 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.85.7.481 date de publication en ligne : 01/07/2019 En ligne : https://doi.org/10.14358/PERS.85.7.481 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93052 [article]

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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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An (almost) automated process to track the Martians dunes : ac.GetPreciseShifts / Arthur Coqué (2018) 

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