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Improved optical image matching time series inversion approach for monitoring dune migration in North Sinai Sand Sea: Algorithm procedure, application, and validation / Eslam Ali in ISPRS Journal of photogrammetry and remote sensing, vol 164 (June 2020)
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Titre : Improved optical image matching time series inversion approach for monitoring dune migration in North Sinai Sand Sea: Algorithm procedure, application, and validation Type de document : Article/Communication Auteurs : Eslam Ali, Auteur ; Wenbin Xu, Auteur ; Xiao-Li Ding, Auteur Année de publication : 2020 Article en page(s) : pp 106 - 124 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] appariement d'images
[Termes IGN] correction des ombres
[Termes IGN] COSI-Corr
[Termes IGN] déplacement d'objet géographique
[Termes IGN] désert
[Termes IGN] désertification
[Termes IGN] données météorologiques
[Termes IGN] dune
[Termes IGN] image Landsat-8
[Termes IGN] image optique
[Termes IGN] image Sentinel-MSI
[Termes IGN] incertitude des données
[Termes IGN] modèle d'inversion
[Termes IGN] modèle dynamique
[Termes IGN] prévention des risques
[Termes IGN] sable
[Termes IGN] série temporelle
[Termes IGN] Sinai
[Termes IGN] variation saisonnière
[Termes IGN] vent de sableRésumé : (auteur) Sand dune migration poses a potential threat to desert infrastructure, vegetation, and atmospheric conditions. Capturing the patterns of long-term dune migration is useful for predicting probable desertification issues and wind conditions across vast desert areas. In this study, we employed optical image matching and a singular value decomposition approach to estimate the rates of dune migration in the North Sinai Sand Sea using the free Landsat 8 and Sentinel-2 archives. Our optical image matching time-series selection and inversion (OPTSI) algorithm limited the difference in the solar illumination of correlated pairs to decrease shadows and seasonal variability. We found that the maximum annual dune migration rates were 9.4 m/a and 15.9 m/a for Landsat 8 and Sentinel-2 data, respectively, and the results of time-series analysis revealed the existence of seasonal variations in dune migration controlled by wind regimes. The directions of sand movement extracted from the mean velocity solution agreed strongly with each other and with the drift directions estimated using wind data from meteorological stations. We assessed the uncertainty of each solution based on the variance of stable areas. Our results showed that the proposed inversion decreased uncertainty by up to 25% and increased the spatial coverage by up to 20%. This algorithm is also promising for the retrieval of historical time series on the ground displacements of glaciers and slow-moving landslides employing free archives that provide high-frequency images. Numéro de notice : A2020-253 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.04.004 Date de publication en ligne : 27/04/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.04.004 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94997
in ISPRS Journal of photogrammetry and remote sensing > vol 164 (June 2020) . - pp 106 - 124[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2020061 RAB Revue Centre de documentation En réserve L003 Disponible 081-2020063 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2020062 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Indoor positioning using PnP problem on mobile phone images / Hana Kubickova in ISPRS International journal of geo-information, vol 9 n° 6 (June 2020)
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Titre : Indoor positioning using PnP problem on mobile phone images Type de document : Article/Communication Auteurs : Hana Kubickova, Auteur ; Karel Jedlička, Auteur ; Radek Fiala, Auteur ; Daniel Beran, Auteur Année de publication : 2020 Article en page(s) : 19 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] appariement d'images
[Termes IGN] base de données d'images
[Termes IGN] couplage GNSS-INS
[Termes IGN] décomposition d'image
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] géométrie épipolaire
[Termes IGN] point d'appui
[Termes IGN] positionnement en intérieur
[Termes IGN] recherche d'image basée sur le contenu
[Termes IGN] SIFT (algorithme)
[Termes IGN] téléphone intelligent
[Termes IGN] vision par ordinateurRésumé : (auteur) As people grow accustomed to effortless outdoor navigation, there is a rising demand for similar possibilities indoors as well. Unfortunately, indoor localization, being one of the requirements for navigation, continues to be a problem without a clear solution. In this article, we are proposing a method for an indoor positioning system using a single image. This is made possible using a small preprocessed database of images with known control points as the only preprocessing needed. Using feature detection with the SIFT (Scale Invariant Feature Transform) algorithm, we can look through the database and find an image that is the most similar to the image taken by a user. Such a pair of images is then used to find coordinates of a database of images using the PnP problem. Furthermore, projection and essential matrices are determined to calculate the user image localization—determining the position of the user in the indoor environment. The benefits of this approach lie in the single image being the only input from a user and the lack of requirements for new onsite infrastructure. Thus, our approach enables a more straightforward realization for building management. Numéro de notice : A2020-309 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9060368 Date de publication en ligne : 02/06/2020 En ligne : https://doi.org/10.3390/ijgi9060368 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95156
in ISPRS International journal of geo-information > vol 9 n° 6 (June 2020) . - 19 p.[article]Object-based automatic multi-index built-up areas extraction method for WorldView-2 satellite imagery / Zhenhui Sun in Geocarto international, Vol 35 n° 8 ([01/06/2020])
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Titre : Object-based automatic multi-index built-up areas extraction method for WorldView-2 satellite imagery Type de document : Article/Communication Auteurs : Zhenhui Sun, Auteur ; Qingyan Meng, Auteur Année de publication : 2020 Article en page(s) : pp 801 - 817 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse d'image orientée objet
[Termes IGN] détection du bâti
[Termes IGN] extraction automatique
[Termes IGN] image à haute résolution
[Termes IGN] image multibande
[Termes IGN] image Worldview
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] Normalized Difference Water Index
[Termes IGN] optimisation par essaim de particules
[Termes IGN] segmentation d'imageRésumé : (auteur) The WorldView-2 high spatial resolution satellite with eight multispectral imaging bands is ideally suited for extracting built-up areas (BUs) from remote sensing images. In this study, an object-based automatic multi-index BUs extraction method was developed. First, several indices, including BUs extraction index (NBEIr-c), vegetation extraction index(NDVInir2-r) and water extraction index (NDWI b-nir1), were developed to obtain the BUs, vegetation and water maps, and then the fractional-order Darwinian particle swarm optimization (FODPSO) algorithm was employed to automatically segment the multi-index images and obtained BUs, water, vegetation and bare soil (BS) information. Finally, the extracted BUs results were optimized via an object-based analysis method and the results were compared with those of two other relevant indices, which confirmed the proposed method had a higher accuracy and exhibited higher performance when separating the BS from the BUs. Numéro de notice : A2020-273 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1544290 Date de publication en ligne : 07/02/2019 En ligne : https://doi.org/10.1080/10106049.2018.1544290 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95058
in Geocarto international > Vol 35 n° 8 [01/06/2020] . - pp 801 - 817[article]The geometric imaging model for high-resolution optical remote sensing satellites considering light aberration and atmospheric refraction errors / Mi Wang in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 6 (June 2020)
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Titre : The geometric imaging model for high-resolution optical remote sensing satellites considering light aberration and atmospheric refraction errors Type de document : Article/Communication Auteurs : Mi Wang, Auteur ; Ying Zhu, Auteur ; Yanli Wang, Auteur ; Yufeng Cheng, Auteur Année de publication : 2020 Article en page(s) : pp 373 -382 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] aberration chromatique
[Termes IGN] aberration géométrique
[Termes IGN] correction atmosphérique
[Termes IGN] image optique
[Termes IGN] réfraction atmosphérique
[Termes IGN] satellite d'observation de la Terre
[Termes IGN] télédétection spatialeRésumé : (Auteur) With advances in satellite maneuvering imaging capability, stereoscopic images with large roll and pitch angles can be captured to improve the efficiency of observations. At the same time, the influences of light aberration and atmospheric refraction on image positioning accuracy will be more significant. However, these errors are not accounted for in the traditional imaging and calibration model for optical agile satellites. In this study, the formation mechanisms of the aberration and atmospheric refraction errors in optical remote sensing satellite Earth observation imaging were analyzed quantitatively, and correction models were constructed. From this, the traditional geometric imaging model was refined by introducing a correction model for aberration and atmospheric refraction errors to create a more comprehensive geometric imaging model. The feasibility of an extended rational function model, based on the constructed more comprehensive geometric imaging model, was verified quantitatively. Numéro de notice : A2020-242 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.86.6.373 Date de publication en ligne : 01/06/2020 En ligne : https://doi.org/10.14358/PERS.86.6.373 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95204
in Photogrammetric Engineering & Remote Sensing, PERS > vol 86 n° 6 (June 2020) . - pp 373 -382[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 105-2020061 SL Revue Centre de documentation Revues en salle Disponible Above-ground biomass estimation of arable crops using UAV-based SfM photogrammetry / Maria Luz Gil-Docampo in Geocarto international, vol 35 n° 7 ([15/05/2020])
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Titre : Above-ground biomass estimation of arable crops using UAV-based SfM photogrammetry Type de document : Article/Communication Auteurs : Maria Luz Gil-Docampo, Auteur ; Marcos Arza-García, Auteur ; Juan Ortiz-Sanz, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 687 - 699 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] acquisition d'images
[Termes IGN] agronomie
[Termes IGN] biomasse
[Termes IGN] image à très haute résolution
[Termes IGN] image captée par drone
[Termes IGN] modèle numérique de surface
[Termes IGN] modèle numérique de terrain
[Termes IGN] photogrammétrie aérienne
[Termes IGN] sol arable
[Termes IGN] structure-from-motionRésumé : (Auteur) Methods of estimating the total amount of above-ground biomass (AGB) in crop fields are generally based on labourious, random, and destructive in situ sampling. This study proposes a methodology for estimating herbaceous crop biomass using conventional optical cameras and structure from motion (SfM) photogrammetry. The proposed method is based on the determination of volumes according to the difference between a digital terrain model (DTM) and digital surface model (DSM) of vegetative cover. A density factor was calibrated based on a subset of destructive random samples to relate the volume and biomass and efficiently quantify the total AGB. In all cases, RMSE Z values less than 0.23 m were obtained for the DTM-DSM coupling. Biomass field data confirmed the goodness of fit of the yield-biomass estimation (R2=0.88 and 1.12 kg/ha) mainly in plots with uniform vegetation coverage. Furthermore, the method was demonstrated to be scalable to multiple platform types and sensors. Numéro de notice : A2020-186 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1552322 Date de publication en ligne : 07/02/2019 En ligne : https://doi.org/10.1080/10106049.2018.1552322 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94993
in Geocarto international > vol 35 n° 7 [15/05/2020] . - pp 687 - 699[article]Assessing alternative methods for unsupervised segmentation of urban vegetation in very high-resolution multispectral aerial imagery / Allison Lassiter in Plos one, vol 15 n° 5 (May 2020)
PermalinkA convolutional neural network with mapping layers for hyperspectral image classification / Rui Li in IEEE Transactions on geoscience and remote sensing, vol 58 n° 5 (May 2020)
PermalinkHyperspectral image clustering with Albedo recovery Fuzzy C-Means / Peyman Azimpour in International Journal of Remote Sensing IJRS, vol 41 n° 16 (01-10 May 2020)
PermalinkBuilding Extraction from High-Resolution Remote Sensing Images Based on GrabCut with Automatic Selection of Foreground and Background Samples / Ka Zhang in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 4 (April 2020)
PermalinkMultichannel Pulse-Coupled Neural Network-Based Hyperspectral Image Visualization / Puhong Duan in IEEE Transactions on geoscience and remote sensing, vol 58 n° 4 (April 2020)
PermalinkMultiscale Intensity Propagation to Remove Multiplicative Stripe Noise From Remote Sensing Images / Hao Cui in IEEE Transactions on geoscience and remote sensing, vol 58 n° 4 (April 2020)
PermalinkA Single Model CNN for Hyperspectral Image Denoising / Alessandro Maffei in IEEE Transactions on geoscience and remote sensing, vol 58 n° 4 (April 2020)
PermalinkStreet-Frontage-Net: urban image classification using deep convolutional neural networks / Stephen Law in International journal of geographical information science IJGIS, vol 34 n° 4 (April 2020)
PermalinkA novel nonlinear hyperspectral unmixing approach for images of oil spills at sea / Ying Li in International Journal of Remote Sensing IJRS, vol 41 n° 12 (20 - 30 March 2020)
PermalinkDimension reduction methods applied to coastline extraction on hyperspectral imagery / Ozan Arslan in Geocarto international, vol 35 n° 4 ([15/03/2020])
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