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A convolutional neural network approach for counting and geolocating citrus-trees in UAV multispectral imagery / Lucas Prado Osco in ISPRS Journal of photogrammetry and remote sensing, vol 160 (February 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 160 (February 2020) . - pp 97 - 106 Titre : A convolutional neural network approach for counting and geolocating citrus-trees in UAV multispectral imagery Type de document : Article/Communication Auteurs : Lucas Prado Osco, Auteur ; Mauro Dos Santos de Arruda, Auteur ; José Marcato Junior, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 97 - 106 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] agrume [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] Brésil [Termes descripteurs IGN] carte de confiance [Termes descripteurs IGN] détection d'arbres [Termes descripteurs IGN] géolocalisation [Termes descripteurs IGN] image de drone [Termes descripteurs IGN] image multibande [Termes descripteurs IGN] inventaire de la végétation [Termes descripteurs IGN] réseau neuronal convolutif [Termes descripteurs IGN] verger Résumé : (Auteur) Visual inspection has been a common practice to determine the number of plants in orchards, which is a labor-intensive and time-consuming task. Deep learning algorithms have demonstrated great potential for counting plants on unmanned aerial vehicle (UAV)-borne sensor imagery. This paper presents a convolutional neural network (CNN) approach to address the challenge of estimating the number of citrus trees in highly dense orchards from UAV multispectral images. The method estimates a dense map with the confidence that a plant occurs in each pixel. A flight was conducted over an orchard of Valencia-orange trees planted in linear fashion, using a multispectral camera with four bands in green, red, red-edge and near-infrared. The approach was assessed considering the individual bands and their combinations. A total of 37,353 trees were adopted in point feature to evaluate the method. A variation of σ (0.5; 1.0 and 1.5) was used to generate different ground truth confidence maps. Different stages (T) were also used to refine the confidence map predicted. To evaluate the robustness of our method, we compared it with two state-of-the-art object detection CNN methods (Faster R-CNN and RetinaNet). The results show better performance with the combination of green, red and near-infrared bands, achieving a Mean Absolute Error (MAE), Mean Square Error (MSE), R2 and Normalized Root-Mean-Squared Error (NRMSE) of 2.28, 9.82, 0.96 and 0.05, respectively. This band combination, when adopting σ = 1 and a stage (T = 8), resulted in an R2, MAE, Precision, Recall and F1 of 0.97, 2.05, 0.95, 0.96 and 0.95, respectively. Our method outperforms significantly object detection methods for counting and geolocation. It was concluded that our CNN approach developed to estimate the number and geolocation of citrus trees in high-density orchards is satisfactory and is an effective strategy to replace the traditional visual inspection method to determine the number of plants in orchards trees. Numéro de notice : A2020-045 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.12.010 date de publication en ligne : 18/12/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.12.010 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94525 [article]

Optimising drone flight planning for measuring horticultural tree crop structure / Yu-Hsuan Tu in ISPRS Journal of photogrammetry and remote sensing, vol 160 (February 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 160 (February 2020) . - pp 83 - 96 Titre : Optimising drone flight planning for measuring horticultural tree crop structure Type de document : Article/Communication Auteurs : Yu-Hsuan Tu, Auteur ; Stuart Phinn, Auteur ; Kasper Johansen, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 83 - 96 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes descripteurs IGN] correction d'image [Termes descripteurs IGN] détection d'arbres [Termes descripteurs IGN] distorsion d'image [Termes descripteurs IGN] étalonnage de chambre métrique [Termes descripteurs IGN] horticulture [Termes descripteurs IGN] image de drone [Termes descripteurs IGN] MicMac [Termes descripteurs IGN] obturateur [Termes descripteurs IGN] photogrammétrie aérienne [Termes descripteurs IGN] plan de vol [Termes descripteurs IGN] point d'appui [Termes descripteurs IGN] qualité d'image [Termes descripteurs IGN] Queensland (Australie) Résumé : (Auteur) In recent times, multi-spectral drone imagery has proved to be a useful tool for measuring tree crop canopy structure. In this context, establishing the most appropriate flight planning variable settings is an essential consideration due to their controls on the quality of the imagery and derived maps of tree and crop biophysical properties. During flight planning, variables including flight altitude, image overlap, flying direction, flying speed and solar elevation, require careful consideration in order to produce the most suitable drone imagery. Previous studies have assessed the influence of individual variables on image quality, but the interaction of multiple variables has yet to be examined. This study assesses the influence of several flight variables on measures of data quality in each processing step, i.e. photo alignment, point cloud densification, 3D model building, and ortho-mosaicking. The analysis produced a drone flight planning and image processing workflow that delivers accurate measurements of tree crops, including the tie point quality, densified point cloud density, and the measurement accuracy of height and plant projective cover derived from individual trees within a commercial avocado orchard. Results showed that flying along the hedgerow, at high solar elevation and with low image pitch angles improved the data quality. Optimal flying speed needs to be set to achieve the required forward overlap. The impacts of each image acquisition variable are discussed in detail and protocols for flight planning optimisation for three scenarios with different drone settings are suggested. Establishing protocols that deliver optimal image acquisitions for the collection of drone data over horticultural tree crops, will create greater confidence in the accuracy of subsequent algorithms and resultant maps of biophysical properties. Numéro de notice : A2020-044 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.12.006 date de publication en ligne : 18/12/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.12.006 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94524 [article]

Plant survival monitoring with UAVs and multispectral data in difficult access afforested areas / Maria Luz Gil-Docampo in Geocarto international, vol 35 n° 2 ([01/02/2020])  

Public [article]  inGeocarto international > vol 35 n° 2 [01/02/2020] . - pp 128 - 140 Titre : Plant survival monitoring with UAVs and multispectral data in difficult access afforested areas Type de document : Article/Communication Auteurs : Maria Luz Gil-Docampo, Auteur ; Juan Ortiz-Sanz, Auteur ; S. Martínez-Rodríguez, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 128 - 140 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] aire protégée [Termes descripteurs IGN] analyse de survie [Termes descripteurs IGN] analyse en composantes principales [Termes descripteurs IGN] climat aride [Termes descripteurs IGN] image de drone [Termes descripteurs IGN] image multibande [Termes descripteurs IGN] image proche infrarouge [Termes descripteurs IGN] image RVB [Termes descripteurs IGN] indice de végétation [Termes descripteurs IGN] mortalité [Termes descripteurs IGN] reboisement [Termes descripteurs IGN] ressources en eau [Termes descripteurs IGN] surveillance de la végétation [Termes descripteurs IGN] télédétection aérienne Résumé : (Auteur) Water supply devices enable afforestation in dry climates and on poor lands with generally high success rates. Previous survival analyses have been based on the direct observation of each individual plant in the field, which entails considerable effort and costs. This study provides a low-cost method to discriminate between live and dead plants in afforestation that can efficiently replace traditional field inspections through the use of unmanned aerial vehicles (UAVs) equipped with RGB and NIR sensors. The method combines the use of a conventional camera with an identical camera modified to record the NIR channel. Survival analysis was performed with digital image processing techniques based on calculated indices associated with plant vigour and PCA-based decorrelation. The method yielded results with high global accuracy rates (∼96.2%) with a minimum percentage of doubtful plants, even in young plantations (seedlings Numéro de notice : A2020-035 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1508312 date de publication en ligne : 02/10/2018 En ligne : https://doi.org/10.1080/10106049.2018.1508312 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94517 [article]

A two-step approach for the correction of rolling shutter distortion in UAV photogrammetry / Yilin Zhou in ISPRS Journal of photogrammetry and remote sensing, vol 160 (February 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 160 (February 2020) . - pp 51 - 66 Titre : A two-step approach for the correction of rolling shutter distortion in UAV photogrammetry Type de document : Article/Communication Auteurs : Yilin Zhou, Auteur ; Mehdi Daakir, Auteur ; Ewelina Rupnik , Auteur ; Marc Pierrot-Deseilligny , Auteur Année de publication : 2020 Article en page(s) : pp 51 - 66 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes descripteurs IGN] capteur aérien [Termes descripteurs IGN] compensation par faisceaux [Termes descripteurs IGN] correction [Termes descripteurs IGN] création de zone intermédiaire [Termes descripteurs IGN] distorsion d'image [Termes descripteurs IGN] étalonnage en vol [Termes descripteurs IGN] image de drone [Termes descripteurs IGN] MicMac [Termes descripteurs IGN] obturateur [Termes descripteurs IGN] photogrammétrie aérienne Résumé : (Auteur) The use of consumer grade unmanned aerial vehicles (UAV) is becoming more and more ubiquitous in photogrammetric applications. A large proportion of consumer grade UAVs are equipped with CMOS image sensor and rolling shutter. When imaging with a rolling shutter camera, the image sensor is exposed line by line, which can introduce additional distortions in image space since the UAV navigates at a relatively high speed during aerial acquisitions. In this paper, we propose (1) an approach to calibrate the readout time of rolling shutter camera, (2) a two-step method to correct the image distortion introduced by this effect. The two-step method makes assumption that during exposure, the change of camera orientation is negligible with respect to the change of camera position, which is often the case when camera is fixed on a stabilized mount. Firstly, the camera velocity is estimated from the results of an initial bundle block adjustment; then, one camera pose per scan-line of the image sensor is recovered and image observations are corrected. To evaluate the performance of the proposed method, four datasets of block and corridor configurations are acquired with the DJI Mavic 2 Pro and its original Hasselbald L1D-20c camera. The proposed method is implemented in MicMac, a free, open-source photogrammetric software; comparisons are carried out with other two mainstream software, AgiSoft MetaShape and Pix4D, which also have the functionality of rolling shutter effect correction. For block configuration datasets, the three software give comparable results. AgiSoft Metashape and Pix4D are sensitive to the flight configuration and encounter difficulties when processing datasets in corridor configurations. The proposed method shows good robustness both in block and corridor configurations, and is the only method that works in corridor configuration. After the application of the rolling shutter effect correction, the 3D accuracy is improved by 30–60% in block configuration and 15–25% in corridor configuration. A further improvement can be expected if a precise dating of image is available or if the camera positions can be directly extracted from GNSS data. Numéro de notice : A2020-018 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.11.020 date de publication en ligne : 16/12/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.11.020 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94456 [article]

Application of photogrammetry to generate quantitative geobody data in ephemeral fluvial systems / Charlotte L. Priddy in Photogrammetric record, vol 34 n° 168 (December 2019)  

Public [article]  inPhotogrammetric record > vol 34 n° 168 (December 2019) . - pp 428 - 444 Titre : Application of photogrammetry to generate quantitative geobody data in ephemeral fluvial systems Type de document : Article/Communication Auteurs : Charlotte L. Priddy, Auteur ; Jamie A. Pringle, Auteur ; Stuart M. Clarke, Auteur ; Ross P. Pettigrew, Auteur Année de publication : 2019 Article en page(s) : pp 428 - 444 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes descripteurs IGN] Agisoft Photoscan [Termes descripteurs IGN] Etats-Unis [Termes descripteurs IGN] image de drone [Termes descripteurs IGN] modèle de simulation [Termes descripteurs IGN] modèle géologique [Termes descripteurs IGN] modélisation 3D [Termes descripteurs IGN] photogrammétrie numérique [Termes descripteurs IGN] réalité virtuelle [Termes descripteurs IGN] réseau fluvial [Termes descripteurs IGN] sédiment [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] structure-from-motion Résumé : (auteur) Outcrop studies are often used as analogues to subsurface sedimentaryreservoirs, with photogrammetry representing a useful technique to obtain quanti-tative geometrical data of sedimentary architectures. Digital photogrammetrictechniques were used to studyfluvial sediments of the Lower Jurassic KayentaFormation of the western USA. Model-extracted statistics for channel andsheetflood elements, relevant to reservoir modelling, were compared with 1D and2D datasets from the same outcrops. Results suggest that the 1D/2D datasignificantly underestimated element dimensions and ranges in ephemeralfluvialsystems. Consequently, this study demonstrates the value of photogrammetrictechniques for obtaining statistically relevant and more accurate reservoirmodelling input data from outcrops. Numéro de notice : A2019-577 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/phor.12299 date de publication en ligne : 13/11/2019 En ligne : https://doi.org/10.1111/phor.12299 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94461 [article]

Combining thermal imaging with photogrammetry of an active volcano using UAV: an example from Stromboli, Italy / Zoë E. Wakeford in Photogrammetric record, vol 34 n° 168 (December 2019)  

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A low‐cost open‐source workflow to generate georeferenced 3D SfM photogrammetric models of rocky outcrops / Laurent Froideval in Photogrammetric record, vol 34 n° 168 (December 2019)  

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Numérisation, restitution et visualisation en 3D de sites patrimoniaux / Jonathan Chemla in XYZ, n° 161 (décembre 2019)

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

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Estimating pasture biomass and canopy height in brazilian savanna using UAV photogrammetry / Juliana Batistoti in Remote sensing, Vol 11 n° 20 (2 October 2019)  

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Postprocessing synchronization of a laser scanning system aboard a UAV / Marcela do Valle Machado in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 10 (October 2019)  

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sUAS-based remote rensing of river discharge using thermal particle image velocimetry and bathymetric lidar / Paul J. Kinzel in Remote sensing, vol 11 n° 19 (October 2019)  

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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)  

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Development and evaluation of a deep learning model for real-time ground vehicle semantic segmentation from UAV-based thermal infrared imagery / Mehdi Khoshboresh Masouleh in ISPRS Journal of photogrammetry and remote sensing, vol 155 (September 2019)  

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Evolution des techniques topographiques à EDF depuis les 40 dernières années / Rémy Boudon in XYZ, n° 160 (septembre 2019)

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