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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)
[article]
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 IGN] apprentissage profond
[Termes IGN] Brésil
[Termes IGN] carte de confiance
[Termes IGN] Citrus (genre)
[Termes IGN] détection d'arbres
[Termes IGN] géolocalisation
[Termes IGN] image captée par drone
[Termes IGN] image multibande
[Termes IGN] inventaire de la végétation
[Termes IGN] réseau neuronal convolutif
[Termes IGN] vergerRésumé : (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 Affiliation des auteurs : non IGN 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
in ISPRS Journal of photogrammetry and remote sensing > vol 160 (February 2020) . - pp 97 - 106[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2020021 RAB Revue Centre de documentation En réserve L003 Disponible 081-2020023 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2020022 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt 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)
[article]
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 performanceRésumé : (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
in European journal of remote sensing > vol 53 n° 1 (2020) . - pp 27 - 39[article]Flowering acceleration in native Brazilian tree species for genetic conservation and breeding / Gleidson Guilherme Caldas Mende in Annals of forest research, Vol 63 n° 1 (January - June 2020)
[article]
Titre : Flowering acceleration in native Brazilian tree species for genetic conservation and breeding Type de document : Article/Communication Auteurs : Gleidson Guilherme Caldas Mende, Auteur ; Gleison Augusto dos Santos, Auteur ; Marcos Deon Vilela de Resende, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 39 - 52 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse de variance
[Termes IGN] arbre (flore)
[Termes IGN] Brésil
[Termes IGN] croissance des arbres
[Termes IGN] essence indigène
[Termes IGN] génétique forestière
[Termes IGN] verger à graines
[Vedettes matières IGN] BotaniqueRésumé : (auteur) Grafting and growth retardants are commonly used in breeding programs to stimulate flower production. However, little is known about their effects on Brazilian tree species. The aim of this study was to investigate the vegetative and reproductive development of grafted tree seedlings treated with paclobutrazol (PBZ) and grown under greenhouse or outdoor conditions. Potted seedlings of Jacaranda mimosifolia, Handroanthus heptaphyllus, Swietenia macrophylla, Schinus terebinthifolius, Cariniana legalis, and Hymenaea courbaril were evaluated. Shoot number, length, and circumference as well as flower and fruit numbers were determined at 50 and 90 days after PBZ application. Data were subjected to analysis of variance, and means were compared by Tukey’s test (P ≤ 0.05). Growing conditions influenced the vegetative parameters of seedlings, especially after 90 days. J. mimosifolia and S. terebinthifolius responded positively to flowering induction, and their fruit and flower numbers differed between growing environments. Potted grafts of the six native tree species were successfully grown. Grafting and PBZ application induced early flowering in J. mimosifolia and S. terebinthifolius. Numéro de notice : A2020-515 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : 10.15287/afr.2019.1751 Date de publication en ligne : 16/03/2020 En ligne : https://doi.org/10.15287/afr.2019.1751 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95674
in Annals of forest research > Vol 63 n° 1 (January - June 2020) . - pp 39 - 52[article]Estimating pasture biomass and canopy height in brazilian savanna using UAV photogrammetry / Juliana Batistoti in Remote sensing, Vol 11 n° 20 (October-2 2019)
[article]
Titre : Estimating pasture biomass and canopy height in brazilian savanna using UAV photogrammetry Type de document : Article/Communication Auteurs : Juliana Batistoti, Auteur ; José Marcato, Auteur ; Luis Itavo, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : 12 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] biomasse
[Termes IGN] Brésil
[Termes IGN] canopée
[Termes IGN] couvert végétal
[Termes IGN] hauteur des arbres
[Termes IGN] image à haute résolution
[Termes IGN] image captée par drone
[Termes IGN] image RVB
[Termes IGN] modèle numérique de surface de la canopée
[Termes IGN] modèle numérique de terrain
[Termes IGN] Poaceae
[Termes IGN] point d'appui
[Termes IGN] positionnement cinématique en temps réelRésumé : (auteur) The Brazilian territory contains approximately 160 million hectares of pastures, and it is necessary to develop techniques to automate their management and increase their production. This technical note has two objectives: First, to estimate the canopy height using unmanned aerial vehicle (UAV) photogrammetry; second, to propose an equation for the estimation of biomass of Brazilian savanna (Cerrado) pastures based on UAV canopy height. Four experimental units of Panicum maximum cv. BRS Tamani were evaluated. Herbage mass sampling, height measurements, and UAV image collection were simultaneously performed. The UAVs were flown at a height of 50 m, and images were generated with a mean ground sample distance (GSD) of approximately 1.55 cm. The forage canopy height estimated by UAVs was calculated as the difference between the digital surface model (DSM) and the digital terrain model (DTM). The R2 between ruler height and UAV height was 0.80; between biomass (kg ha−1 GB—green biomass) and ruler height, 0.81; and between biomass (kg ha−1 GB) and UAV height, 0.74. UAV photogrammetry proved to be a potential technique to estimate height and biomass in Brazilian Panicum maximum cv. BRS Tamani pastures located in the endangered Brazilian savanna (Cerrado) biome Numéro de notice : A2019-556 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs11202447 Date de publication en ligne : 22/10/2019 En ligne : https://doi.org/10.3390/rs11202447 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94212
in Remote sensing > Vol 11 n° 20 (October-2 2019) . - 12 p.[article]Multi-sensor prediction of Eucalyptus stand volume: A support vector approach / Guilherme Silverio Aquino de Souza in ISPRS Journal of photogrammetry and remote sensing, vol 156 (October 2019)
[article]
Titre : Multi-sensor prediction of Eucalyptus stand volume: A support vector approach Type de document : Article/Communication Auteurs : Guilherme Silverio Aquino de Souza, Auteur ; Vicente Paulo Soares, Auteur ; Helio Garcia Leite, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 135 - 146 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] analyse comparative
[Termes IGN] apprentissage automatique
[Termes IGN] bande L
[Termes IGN] Brésil
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par réseau neuronal
[Termes IGN] Eucalyptus (genre)
[Termes IGN] image ALOS-AVNIR2
[Termes IGN] image ALOS-PALSAR
[Termes IGN] image radar moirée
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] régression multiple
[Termes IGN] taux d'échantillonnage
[Termes IGN] volume en boisRésumé : (Auteur) Stem volume is a key attribute of Eucalyptus forest plantations upon which decision-making is based at diverse levels of planning. Quantifying volume through remote sensing can support a proper management of forests. Because of limitations on spaceborne optical and synthetic aperture radar sensors, this study integrated both types of datasets assembled using support vector regression (SVR) to retrieve the stand volume of Eucalyptus plantations. We assessed different combinations of sensors and a minimum number of plots to develop an SVR model. Finally, the best SVR performance was compared with other analytical methods already tested and in the literature: multilinear regression, artificial neural networks (ANN), and random forest (RF). Here, we introduce a test for comparative analysis of the performance of different methods. We found that SVR accurately predicted stem volume of Brazilian fast-growing Eucalyptus forest plantations. Gaussian radial basis was the most suitable kernel function. Integrating the optical and L-band backscatter data increased the predictive accuracy compared to a single sensor model. Combining NIR-band data from ALOS AVNIR-2 and backscatter of L-band horizontal emitted and vertical received (HV) electric fields from ALOS PALSAR produced the most accurate SVR model (with an R2 of 0.926 and root mean square error of 11.007 m3/ha). The number of field plots sufficient for model development with non-redundant explanatory variables was 77. Under this condition, SVR performed similarly to ANN and outperformed the multiple linear regression and random forest methods. Numéro de notice : A2019-319 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : doi.org/10.1016/j.isprsjprs.2019.08.002 Date de publication en ligne : 20/08/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.08.002 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93357
in ISPRS Journal of photogrammetry and remote sensing > vol 156 (October 2019) . - pp 135 - 146[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2019101 RAB Revue Centre de documentation En réserve L003 Disponible 081-2019103 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2019102 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Spatially-explicit sensitivity and uncertainty analysis in a MCDA-based flood vulnerability model / Mariana Madruga de bruto in International journal of geographical information science IJGIS, vol 33 n° 9 (September 2019)PermalinkA generalized space-time OBIA classification scheme to map sugarcane areas at regional scale, using Landsat images time-series and the random forest algorithm / Ana Claudia Dos Santos Luciano in International journal of applied Earth observation and geoinformation, vol 80 (August 2019)PermalinkMonitoring the structure of forest restoration plantations with a drone-lidar system / D.R.A. Almeida in International journal of applied Earth observation and geoinformation, vol 79 (July 2019)PermalinkObject-based random forest modelling of aboveground forest biomass outperforms a pixel-based approach in a heterogeneous and mountain tropical environment / Eduarda M.O. Silveira in International journal of applied Earth observation and geoinformation, vol 78 (June 2019)PermalinkMulti‐temporal transport network models for accessibility studies / Diego Bogado Tomasiello in Transactions in GIS, vol 23 n° 2 (April 2019)PermalinkTree species classification in tropical forests using visible to shortwave infrared WorldView-3 images and texture analysis / Matheus Pinheiro Ferreira in ISPRS Journal of photogrammetry and remote sensing, vol 149 (March 2019)PermalinkEucalyptus growth and yield system: Linking individual-tree and stand-level growth models in clonal Eucalypt plantations in Brazil / Henrique Ferraco Scolforo in Forest ecology and management, vol 432 (15 January 2019)PermalinkEvaluating SAR-optical sensor fusion for aboveground biomass estimation in a Brazilian tropical forest / Aline Bernarda Debastiani in Annals of forest research, vol 62 n° 1 (January - June 2019)PermalinkA spatiotemporal calculus for reasoning about land-use trajectories / Adeline Marinho Maciel in International journal of geographical information science IJGIS, Vol 33 n° 1-2 (January - February 2019)PermalinkIndividual tree crown delineation in a highly diverse tropical forest using very high resolution satellite images / Fabien Hubert Wagner in ISPRS Journal of photogrammetry and remote sensing, vol 145 - part B (November 2018)Permalink