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Termes IGN > sciences naturelles > physique > traitement d'image > photogrammétrie > photogrammétrie numérique > modèle numérique de surface
modèle numérique de surfaceSynonyme(s)modèle numérique d'élévation ;modèle numérique d'altitude ;MNE ;MNA ;DEM MNSVoir aussi |
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Assessment of dense image matchers for digital surface model generation using airborne and spaceborne images – an update / Yilong Han in Photogrammetric record, vol 35 n° 169 (March 2020)
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Titre : Assessment of dense image matchers for digital surface model generation using airborne and spaceborne images – an update Type de document : Article/Communication Auteurs : Yilong Han, Auteur ; Rongjun Qin, Auteur ; Xu Huang, Auteur Année de publication : 2020 Article en page(s) : pp 58 - 80 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] appariement d'images
[Termes IGN] estimation de précision
[Termes IGN] image captée par drone
[Termes IGN] image satellite
[Termes IGN] modèle numérique de surfaceRésumé : (Auteur) Digital surface model (DSM) generation is one of the fundamental issues in photogrammetry and the mapping industry. This paper provides a comprehensive assessment of state‐of‐the‐art image matchers using nine open‐source and commercial software packages on aerial and unmanned aerial vehicle (UAV) images and five software packages on spaceborne images. Two datasets provide an update on DSM generation software for both airborne and spaceborne data: a 5 × 5 UAV image block with high‐precision models; and a WorldView‐1 stereopair with lidar reference data. To understand the performance of the image matchers, accuracy analysis is additionally performed on five selected ground objects. The tested image matchers adopting hierarchical semi‐global matching fitted the reference DSM better, thus yielding better accuracy. Numéro de notice : A2020-132 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/phor.12310 Date de publication en ligne : 29/03/2020 En ligne : https://doi.org/10.1111/phor.12310 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94816
in Photogrammetric record > vol 35 n° 169 (March 2020) . - pp 58 - 80[article]Estimation of variance and spatial correlation width for fine-scale measurement error in digital elevation model / Mikhail L. Uss in IEEE Transactions on geoscience and remote sensing, vol 58 n° 3 (March 2020)
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Titre : Estimation of variance and spatial correlation width for fine-scale measurement error in digital elevation model Type de document : Article/Communication Auteurs : Mikhail L. Uss, Auteur ; Benoit Vozel, Auteur ; Vladimir V. Lukin, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 1941 - 1956 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] Advanced Spaceborne Thermal Emission and Reflection Radiometer
[Termes IGN] analyse multivariée
[Termes IGN] corrélation automatique de points homologues
[Termes IGN] courbe épipolaire
[Termes IGN] erreur de mesure
[Termes IGN] image ALOS
[Termes IGN] image TanDEM-X
[Termes IGN] modèle d'erreur
[Termes IGN] modèle numérique de surface
[Termes IGN] mouvement brownien
[Termes IGN] varianceRésumé : (Auteur) In this article, we borrow from the blind noise parameter estimation (BNPE) methodology early developed in the image processing field an original and innovative no-reference approach to estimate digital elevation model (DEM) vertical error parameters without resorting to a reference DEM. The challenges associated with the proposed approach related to the physical nature of the error and its multifactor structure in DEM are discussed in detail. A suitable multivariate method is then developed for estimating the error in gridded DEM. It is built on a recently proposed vectorial BNPE method for estimating spatially correlated noise using noise informative areas and fractal Brownian motion. The new multivariate method is derived to estimate the effect of the stacking procedure and that of the epipolar line error on local (fine-scale) standard deviation and autocorrelation function width of photogrammetric DEM measurement error. Applying the new estimator to Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) GDEM2 and Advanced Land Observing Satellite (ALOS) World 3D DEMs, good agreement of derived estimates with results available in the literature is evidenced. Adopted for TanDEM-X-DEM, estimates obtained agree well with the values provided in the height error map. In future works, the proposed no-reference method for analyzing DEM error can be extended to a larger number of predictors for accounting for other factors influencing remote sensing (RS) DEM accuracy. Numéro de notice : A2020-092 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2951178 Date de publication en ligne : 28/11/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2951178 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94666
in IEEE Transactions on geoscience and remote sensing > vol 58 n° 3 (March 2020) . - pp 1941 - 1956[article]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)
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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)
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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]Variable DEM generalization using local entropy for terrain representation through scale / Paulo Raposo in International journal of cartography, Vol 6 n° 1 (March 2020)
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Titre : Variable DEM generalization using local entropy for terrain representation through scale Type de document : Article/Communication Auteurs : Paulo Raposo, Auteur Année de publication : 2020 Article en page(s) : pp 99 - 120 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] courbe de niveau
[Termes IGN] entropie
[Termes IGN] filtre passe-bas
[Termes IGN] généralisation cartographique
[Termes IGN] lissage de valeur
[Termes IGN] modèle numérique de surface
[Termes IGN] représentation multiple
[Termes IGN] voisinage (relation topologique)
[Vedettes matières IGN] GénéralisationRésumé : (auteur) An automated method of variable digital elevation model (DEM) smoothing is presented. Using variably sized kernels to perform filtering, the method is driven by the entropy of local z-values in the DEM, i.e. the amount of information necessary to convey the elevation variety in the neighborhood of each pixel. This paper presents the method in service of low-pass filtering in order to smooth the raster, though other neighborhood-based filters could be implemented as well. When used in smoothing, the method successfully retains detail in areas of higher relief variation and suppresses it in areas of lower variation, thereby retaining more salient features like ridges, peaks, or incised valleys, while diminishing flatter ones. Varying the neighborhood size with which entropy calculations are made allows for filtering through continuous map scale, enabling multi-scale representation. The method also includes a simple correction for smoothed pixels such that their z-value range reflects that of the input DEM, thereby ensuring that subsequent products such as generated contour lines remain within correct ranges. Several illustrations are given of the method's results. Numéro de notice : A2020-072 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/23729333.2019.1687973 Date de publication en ligne : 16/12/2019 En ligne : https://doi.org/10.1080/23729333.2019.1687973 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94636
in International journal of cartography > Vol 6 n° 1 (March 2020) . - pp 99 - 120[article]A LiDAR–optical data fusion approach for identifying and measuring small stream impoundments and dams / Benjamin Swan in Transactions in GIS, Vol 24 n° 1 (February 2020)
PermalinkSome thoughts on measuring earthquake deformation using optical imagery / Min Huang in IEEE Transactions on geoscience and remote sensing, vol 58 n° 2 (February 2020)
PermalinkStatistical 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)
PermalinkThe "Incense Road" from Petra to Gaza: an analysis using GIS and Cost functions / Motti Zohar in International journal of geographical information science IJGIS, vol 34 n° 2 (February 2020)
PermalinkCombining GF-2 and RapidEye satellite data for mapping mangrove species using ensemble machine-learning methods / Liheng Peng in International Journal of Remote Sensing IJRS, vol 41 n° 3 (15 - 22 janvier 2020)
PermalinkModelling the orthoimage accuracy using DEM accuracy and off-nadir angle / Altan Yilmaz in Geocarto international, Vol 35 n° 1 ([02/01/2020])
PermalinkPermalinkAssessment of ArcGIS based extraction of geoidal undulation compared to National Geospatial Intelligence Agency (NGA) model – A case study / Sher Muhammad in Journal of applied geodesy, vol 14 n° 1 (January 2020)
PermalinkCamera orientation, calibration and inverse perspective with uncertainties: a Bayesian method applied to area estimation from diverse photographs / Grégoire Guillet in ISPRS Journal of photogrammetry and remote sensing, vol 159 (January 2020)
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