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Integrated edge detection and terrain analysis for agricultural terrace delineation from remote sensing images / Wen Dai in International journal of geographical information science IJGIS, vol 34 n° 3 (March 2020)
[article]
Titre : Integrated edge detection and terrain analysis for agricultural terrace delineation from remote sensing images Type de document : Article/Communication Auteurs : Wen Dai, Auteur ; Jiaming Na, Auteur ; Nan Huang, Auteur Année de publication : 2020 Article en page(s) : pp 484 - 503 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] analyse des risques
[Termes IGN] cartographie automatique
[Termes IGN] Chine
[Termes IGN] délimitation
[Termes IGN] détection de contours
[Termes IGN] effet d'ombre
[Termes IGN] érosion
[Termes IGN] Google Earth
[Termes IGN] humidité du sol
[Termes IGN] image satellite
[Termes IGN] image Worldview
[Termes IGN] méthode robuste
[Termes IGN] MNS ASTER
[Termes IGN] modèle numérique de surface
[Termes IGN] modèle numérique de terrain
[Termes IGN] production agricole
[Termes IGN] superposition d'images
[Termes IGN] terrasseRésumé : (auteur) Agricultural terraces are important for agricultural production and soil-and-water conservation. They comprise treads and risers that require manual construction and maintenance. If managed improperly, risers will collapse, causing soil loss, gully erosion, and cultivation threats. However, mapping terrace risers remains a challenge. This study presents a novel approach to automatically map terrace risers by combining remote sensing images and digital elevation models (DEMs). First, a terraced hillslope was extracted via a hill-shading method and edges in the image were detected using a Canny edge detector. Next, the DEM was used to generate the contour direction, and edges along this direction were searched and coded as candidate terrace risers via directional detection. Finally, the results of directional detection and the edge image obtained from the Canny detector were overlaid to backtrack complete terrace risers. The approach was validated using four study areas with different topographic characteristics in the Loess Plateau, China. The results verify that the approach achieves outstanding performance and robustness in mapping terrace risers. The precision, recall, and F-measure were 90.81%–97.57%, 88.53%–94.10%, and 90.13%–95.80%, respectively. This approach is flexible and applicable with freely available images and DEM sources. Numéro de notice : A2020-105 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1650363 Date de publication en ligne : 22/08/2019 En ligne : https://doi.org/10.1080/13658816.2019.1650363 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94701
in International journal of geographical information science IJGIS > vol 34 n° 3 (March 2020) . - pp 484 - 503[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2020031 RAB Revue Centre de documentation En réserve L003 Disponible Integration of remote sensing and GIS to extract plantation rows from a drone-based image point cloud digital surface model / Nadeem Fareed in ISPRS International journal of geo-information, vol 9 n° 3 (March 2020)
[article]
Titre : Integration of remote sensing and GIS to extract plantation rows from a drone-based image point cloud digital surface model Type de document : Article/Communication Auteurs : Nadeem Fareed, Auteur ; Khushbakht Rehman, Auteur Année de publication : 2020 Article en page(s) : 26 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] agriculture de précision
[Termes IGN] données GNSS
[Termes IGN] données lidar
[Termes IGN] extraction automatique
[Termes IGN] extraction de la végétation
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] image à très haute résolution
[Termes IGN] image captée par drone
[Termes IGN] image RVB
[Termes IGN] modèle dynamique
[Termes IGN] modèle numérique de surface
[Termes IGN] semis de points
[Termes IGN] structure-from-motion
[Termes IGN] système d'information géographique
[Termes IGN] télédétectionRésumé : (auteur) Automated feature extraction from drone-based image point clouds (DIPC) is of paramount importance in precision agriculture (PA). PA is blessed with mechanized row seedlings to attain maximum yield and best management practices. Therefore, automated plantation rows extraction is essential in crop harvesting, pest management, and plant grow-rate predictions. Most of the existing research is consists on red, green, and blue (RGB) image-based solutions to extract plantation rows with the minimal background noise of test study sites. DIPC-based DSM row extraction solutions have not been tested frequently. In this research work, an automated method is designed to extract plantation row from DIPC-based DSM. The chosen plantation compartments have three different levels of background noise in UAVs images, therefore, methodology was tested under different background noises. The extraction results were quantified in terms of completeness, correctness, quality, and F1-score values. The case study revealed the potential of DIPC-based solution to extraction the plantation rows with an F1-score value of 0.94 for a plantation compartment with minimal background noises, 0.91 value for a highly noised compartment, and 0.85 for a compartment where DIPC was compromised. The evaluation suggests that DSM-based solutions are robust as compared to RGB image-based solutions to extract plantation-rows. Additionally, DSM-based solutions can be further extended to assess the plantation rows surface deformation caused by humans and machines and state-of-the-art is redefined. Numéro de notice : A2020-260 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9030151 Date de publication en ligne : 06/03/2020 En ligne : https://doi.org/10.3390/ijgi9030151 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95020
in ISPRS International journal of geo-information > vol 9 n° 3 (March 2020) . - 26 p.[article]Three-dimensional photogrammetric mapping of cotton bolls in situ based on point cloud segmentation and clustering / Shangpeng Sun in ISPRS Journal of photogrammetry and remote sensing, vol 160 (February 2020)
[article]
Titre : Three-dimensional photogrammetric mapping of cotton bolls in situ based on point cloud segmentation and clustering Type de document : Article/Communication Auteurs : Shangpeng Sun, Auteur ; Changying Li, Auteur ; Peng Wah Chee, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 195 - 207 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] cartographie 3D
[Termes IGN] classification basée sur les régions
[Termes IGN] distribution spatiale
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] extraction de la végétation
[Termes IGN] gestion de production
[Termes IGN] Gossypium (genre)
[Termes IGN] phénologie
[Termes IGN] rendement agricole
[Termes IGN] segmentation d'image
[Termes IGN] semis de points
[Termes IGN] structure-from-motion
[Termes IGN] surveillance de la végétationRésumé : (Auteur) Three-dimensional high throughput plant phenotyping techniques provide an opportunity to measure plant organ-level traits which can be highly useful to plant breeders. The number and locations of cotton bolls, which are the fruit of cotton plants and an important component of fiber yield, are arguably among the most important phenotypic traits but are complex to quantify manually. Hence, there is a need for effective and efficient cotton boll phenotyping solutions to support breeding research and monitor the crop yield leading to better production management systems. We developed a novel methodology for 3D cotton boll mapping within a plot in situ. Point clouds were reconstructed from multi-view images using the structure from motion algorithm. The method used a region-based classification algorithm that successfully accounted for noise due to sunlight. The developed density-based clustering method could estimate boll counts for this situation, in which bolls were in direct contact with other bolls. By applying the method to point clouds from 30 plots of cotton plants, boll counts, boll volume and position data were derived. The average accuracy of boll counting was up to 90% and the R2 values between fiber yield and boll number, as well as fiber yield and boll volume were 0.87 and 0.66, respectively. The 3D boll spatial distribution could also be analyzed using this method. This method, which was low-cost and provided improved site-specific data on cotton bolls, can also be applied to other plant/fruit mapping analysis after some modification. Numéro de notice : A2020-048 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.12.011 Date de publication en ligne : 25/12/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.12.011 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94561
in ISPRS Journal of photogrammetry and remote sensing > vol 160 (February 2020) . - pp 195 - 207[article]Réservation
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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 Modelling the orthoimage accuracy using DEM accuracy and off-nadir angle / Altan Yilmaz in Geocarto international, Vol 35 n° 1 ([02/01/2020])
[article]
Titre : Modelling the orthoimage accuracy using DEM accuracy and off-nadir angle Type de document : Article/Communication Auteurs : Altan Yilmaz, Auteur ; Mustafa Erdogan, Auteur Année de publication : 2020 Article en page(s) : pp 1 - 16 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] angle nadiral
[Termes IGN] centrale inertielle
[Termes IGN] erreur
[Termes IGN] erreur moyenne quadratique
[Termes IGN] modèle empirique
[Termes IGN] modèle numérique de surface
[Termes IGN] orthoimage
[Termes IGN] planimétrie
[Termes IGN] point d'appuiRésumé : (auteur) Orthoimages are differentially rectified images that are corrected for the distortions caused especially by image tilt and topographic relief. The orientation, digital elevation model (DEM) and off-nadir angle plays an important role in orthoimage accuracy. The orientation error mostly occurs due to the quality and distribution of the ground control points. In this study, an attempt has been made to model the remaining errors by keeping the orientation error constant. To model the accuracy, orthoimages are produced with eight DEMs having different accuracies and are assessed using 50 check points. As the theoretical model cannot reflect the real world exactly, an empirical model is used for estimating the orthoimage accuracy. This proposed model was validated by another dataset. It is concluded that statistically there is no significant difference between the calculated model and real planimetric errors. The proposed model can be used in predicting orthoimage accuracy provided that the DEM accuracy and off-nadir angles of the points are known. Numéro de notice : A2020-016 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1493157 Date de publication en ligne : 12/09/2018 En ligne : https://doi.org/10.1080/10106049.2018.1493157 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94409
in Geocarto international > Vol 35 n° 1 [02/01/2020] . - pp 1 - 16[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2020011 RAB Livre Centre de documentation En réserve L003 Disponible
Titre : Applications of photogrammetry for environmental research Type de document : Monographie Auteurs : Francesco Mancini, Éditeur scientifique ; Riccardo Salvini, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2020 Importance : 154 p. ISBN/ISSN/EAN : 978-3-03928-181-7 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] hauteur des arbres
[Termes IGN] image satellite
[Termes IGN] photographie aérienne
[Termes IGN] Populus (genre)
[Termes IGN] risque environnementalRésumé : (Editeur) The book presents a collection of papers focused on recent progress in key areas of photogrammetry for environmental research. Applications oriented to the understanding of natural phenomena and quantitative processes using dataset from photogrammetry (from satellite to unmanned aerial vehicle images) and terrestrial laser scanning, also by a diachronic approach, are reported. The book covers topics of interest of many disciplines from geography, geomorphology, engineering geology, geotechnology, including landscape description and coastal studies. Mains issues faced by the book are related to applications on coastal monitoring, using multitemporal aerial images, and investigations on geomorphological hazard by the joint use of proximal photogrammetry, terrestrial and aerial laser scanning aimed to the reconstruction of detailed surface topography and successive 2D/3D numerical simulations for rock slope stability analyses. Results reported in the book bring into evidence the fundamental role of multitemporal surveys and reliable reconstruction of morphologies from photogrammetry and laser scanning as support to environmental researches. Numéro de notice : 26302 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Monographie DOI : 10.3390/books978-3-03928-181-7 Date de publication en ligne : 30/01/2020 En ligne : https://doi.org/10.3390/books978-3-03928-181-7 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95035 PermalinkCartographie sémantique hybride de scènes urbaines à partir de données image et Lidar / Mohamed Boussaha (2020)PermalinkPermalinkPermalinkFusion of 3D point clouds and hyperspectral data for the extraction of geometric and radiometric features of trees / Eduardo Alejandro Tusa Jumbo (2020)PermalinkPermalinkDe l’image optique "multi-stéréo" à la topographie très haute résolution et la cartographie automatique des failles par apprentissage profond / Lionel Matteo (2020)PermalinkPermalinkNew quantitative indices from 3D modeling by photogrammetry to monitor coral reef environments / Isabel Urbina-Barreto (2020)PermalinkProbabilistic pose estimation and 3D reconstruction of vehicles from stereo images / Maximilian Alexander Coenen (2020)Permalink