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Incorporation of digital elevation model, normalized difference vegetation index, and Landsat-8 data for land use land cover mapping / Jwan Al-Doski in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 8 (August 2022)
[article]
Titre : Incorporation of digital elevation model, normalized difference vegetation index, and Landsat-8 data for land use land cover mapping Type de document : Article/Communication Auteurs : Jwan Al-Doski, Auteur ; Faez M. Hassan, Auteur ; Hussein Abdelwahab Mossa, Auteur ; Aus A. Najim, Auteur Année de publication : 2022 Article en page(s) : pp 507 - 516 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] carte d'occupation du sol
[Termes IGN] carte d'utilisation du sol
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] données auxiliaires
[Termes IGN] image Landsat-8
[Termes IGN] Malaisie
[Termes IGN] MNS ASTER
[Termes IGN] modèle numérique de surface
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] ombre
[Termes IGN] précision de la classificationRésumé : (Auteur) Ancillary data are crucial in land use land cover (LULC) mapping process. This study goal is to investigate if adding Normalized Difference Vegetation Index (NDVI) and digital elevation model (DEM) data as ancillary data to the Landsat-8 spectral imagery (acquired on 14 April 2016) in the support vector machine (SVM ) classification process improves LULC mapping accuracy in GuaMusang, Malaysia. ENVI software was used to preprocess a single Landsat-8 image, convert it to reflectance, and calculate NDVI. ASTER-GDEM data were used to generate the DEM. The logical channel method was used to combine NDVI and DEM with Landsat-8 bands and limit the impact of shadows during SVM classification. The SVM accuracy was tested and evaluated on ancillary data and Landsat-8 spectral-based collection. The results revealed that the user's accuracy and producer's accuracy improved by 15.1% and 2.1%, for primary forest and by 17.93% and 28.86% for secondary forest, respectively. The classification reliability of the majority of LULC categories has increased significantly. Compared to SVM spectral-based set, the overall accuracy and kappa coefficient of the SVM ancillary-based set improved by 8.77% and 0.12, respectively. In conclusion, this article demonstrated that integrating DEM and NDVI data improves Landsat-8 image classification precision. Numéro de notice : A2022-805 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.21-00082R2 Date de publication en ligne : 01/08/2022 En ligne : https://doi.org/10.14358/PERS.21-00082R2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102132
in Photogrammetric Engineering & Remote Sensing, PERS > vol 88 n° 8 (August 2022) . - pp 507 - 516[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 105-2022081 SL Revue Centre de documentation Revues en salle Disponible Integrating post-processing kinematic (PPK) structure-from-motion (SfM) with unmanned aerial vehicle (UAV) photogrammetry and digital field mapping for structural geological analysis / Daniele Cirillo in ISPRS International journal of geo-information, vol 11 n° 8 (August 2022)
[article]
Titre : Integrating post-processing kinematic (PPK) structure-from-motion (SfM) with unmanned aerial vehicle (UAV) photogrammetry and digital field mapping for structural geological analysis Type de document : Article/Communication Auteurs : Daniele Cirillo, Auteur ; Francesca Cerritelli, Auteur ; Silvano Agostini, Auteur Année de publication : 2022 Article en page(s) : n° 437 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] Apennins
[Termes IGN] carte géologique
[Termes IGN] déformation de la croute terrestre
[Termes IGN] géologie
[Termes IGN] image captée par drone
[Termes IGN] Italie
[Termes IGN] modèle numérique de surface
[Termes IGN] modélisation 3D
[Termes IGN] point d'appui
[Termes IGN] positionnement cinématique en temps réel
[Termes IGN] post-traitement
[Termes IGN] structure-from-motionRésumé : (auteur) We studied some exposures of the Roccacaramanico Conglomerate (RCC), a calcareous-clastic mega-bed intercalated within the Late Messinian–Early Pliocene pelitic succession of the La Queglia and Maiella tectonic units (central Apennines). The outcrops, localized in the overturned limb of a kilometric-scale syncline, show a complex array of fractures, including multiple systems of closely spaced cleavages, joints, and mesoscopic faults, which record the progressive deformation associated with the Late Pliocene thrusting. Due to the extent of the investigated sites and a large amount of data to collect, we applied a multi-methodology survey technique integrating unmanned aerial vehicle (UAV) technologies and digital mapping in the field. We reconstructed the 3D digital outcrop model of the RCC in the type area and defined the 3D pattern of fractures and their time–space relationships. The field survey played a pivotal role in determining the various sets of structures, their kinematics, the associated displacements, and relative chronology. The results unveiled the investigated area’s tectonic evolution and provide a deformation model that could be generalized in similar tectonic contexts. Furthermore, the methodology allows for evaluating the reliability of the applied remote survey techniques (i.e., using UAV) compared to those based on the direct measurements of structures using classic devices. Our purpose was to demonstrate that our multi-methodology approach can describe the tectonic evolution of the study area, providing consistent 3D data and using a few ground control points. Finally, we propose two alternative working methods and discuss their different fields of application. Numéro de notice : A2022-648 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi11080437 Date de publication en ligne : 02/08/2022 En ligne : https://doi.org/10.3390/ijgi11080437 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101464
in ISPRS International journal of geo-information > vol 11 n° 8 (August 2022) . - n° 437[article]A pipeline for automated processing of Corona KH-4 (1962-1972) stereo imagery / Sajid Ghuffar in IEEE Transactions on geoscience and remote sensing, vol 60 n° 8 (August 2022)
[article]
Titre : A pipeline for automated processing of Corona KH-4 (1962-1972) stereo imagery Type de document : Article/Communication Auteurs : Sajid Ghuffar, Auteur ; Tobias Bolch, Auteur ; Ewelina Rupnik , Auteur ; Atanu Bhattacharya, Auteur Année de publication : 2022 Article en page(s) : pp Note générale : bibliographie
voir aussi https://research-repository.st-andrews.ac.uk/bitstream/10023/26124/1/Ghuffar_2022_IEEE_TGRS_Pipeline_automated_processing_AAM.pdfLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] appariement d'images
[Termes IGN] apprentissage profond
[Termes IGN] chaîne de traitement
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] compensation par faisceaux
[Termes IGN] géométrie de l'image
[Termes IGN] géométrie épipolaire
[Termes IGN] glacier
[Termes IGN] Himalaya
[Termes IGN] image Corona
[Termes IGN] image panoramique
[Termes IGN] MNS SRTM
[Termes IGN] modèle numérique de surface
[Termes IGN] modèle stéréoscopique
[Termes IGN] point d'appuiRésumé : (auteur) The Corona KH-4 reconnaissance satellite missions from 1962-1972 acquired panoramic stereo imagery with high spatial resolution of 1.8-7.5 m. The potential of 800,000+ declassified Corona images has not been leveraged due to the complexities arising from handling of panoramic imaging geometry, film distortions and limited availability of the metadata required for georeferencing of the Corona imagery. This paper presents Corona Stereo Pipeline (CoSP): A pipeline for processing of Corona KH-4 stereo panoramic imagery. CoSP utlizes a deep learning based feature matcher SuperGlue to automatically match features point between Corona KH-4 images and recent satellite imagery to generate Ground Control Points (GCPs). To model the imaging geometry and the scanning motion of the panoramic KH-4 cameras, a rigorous camera model consisting of modified collinearity equations with time dependent exterior orientation parameters is employed. The results show that using the entire frame of the Corona image, bundle adjustment using well-distributed GCPs results in an average standard deviation (SD) of less than 2 pixels. We evaluate fiducial marks on the Corona films and show that pre-processing the Corona images to compensate for film bending improves the accuracy. We further assess a polynomial epipolar resampling method for rectification of Corona stereo images. The distortion pattern of image residuals of GCPs and y-parallax in epipolar resampled images suggest that film distortions due to long term storage as likely cause of systematic deviations. Compared to the SRTM DEM, the Corona DEM computed using CoSP achieved a Normalized Median Absolute Deviation (NMAD) of elevation differences of ? 4m over an area of approx. 4000km2. We show that the proposed pipeline can be applied to sequence of complex scenes involving high relief and glacierized terrain and that the resulting DEMs can be used to compute long term glacier elevation changes over large areas. Numéro de notice : A2022-952 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Autre URL associée : vers ArXiv Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2022.3200151 Date de publication en ligne : 19/08/2022 En ligne : https://doi.org/10.1109/TGRS.2022.3200151 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103286
in IEEE Transactions on geoscience and remote sensing > vol 60 n° 8 (August 2022) . - pp[article]Spatial–spectral attention network guided with change magnitude image for land cover change detection using remote sensing images / Zhiyong Lv in IEEE Transactions on geoscience and remote sensing, vol 60 n° 8 (August 2022)
[article]
Titre : Spatial–spectral attention network guided with change magnitude image for land cover change detection using remote sensing images Type de document : Article/Communication Auteurs : Zhiyong Lv, Auteur ; Fengjun Wang, Auteur ; Guoqing Cui, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 4412712 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage profond
[Termes IGN] attention (apprentissage automatique)
[Termes IGN] détection de changement
[Termes IGN] image Landsat-TM
[Termes IGN] jeu de données
[Termes IGN] occupation du sol
[Termes IGN] prévention des risques
[Termes IGN] réseau neuronal siamoisRésumé : (auteur) Land cover change detection (LCCD) using remote sensing images (RSIs) plays an important role in natural disaster evaluation, forest deformation monitoring, and wildfire destruction detection. However, bitemporal images are usually acquired at different atmospheric conditions, such as sun height and soil moisture, which usually cause pseudo and noise change in the change detection map. Changed areas on the ground also generally have various shapes and sizes, consequently making the utilization of spatial contextual information a challenging task. In this article, we design a novel neural network with a spatial–spectral attention mechanism and multiscale dilation convolution modules. This work is based on the previously demonstrated promising performance of convolutional neural network for LCCD with RSIs and attempts to capture more positive changes and further enhance the detection accuracies. The learning of the proposed neural network is guided with a change magnitude image. The performance and feasibility of the proposed network are validated with four pairs of RSIs that depict real land cover change events on the Earth’s surface. Comparison of the performance of the proposed approach with that of five state-of-art methods indicates the superiority of the proposed network in terms of ten quantitative evaluation metrics and visual performance. Such as, the proposed network achieved an improvement of about 0.08%–14.87% in terms of overall accuracy (OA) for Dataset-A. Numéro de notice : A2022-660 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2022.3197901 Date de publication en ligne : 17/08/2022 En ligne : https://doi.org/10.1109/TGRS.2022.3197901 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101516
in IEEE Transactions on geoscience and remote sensing > vol 60 n° 8 (August 2022) . - n° 4412712[article]Tracking annual dynamics of mangrove forests in mangrove National Nature Reserves of China based on time series Sentinel-2 imagery during 2016–2020 / Rong Zhang in International journal of applied Earth observation and geoinformation, vol 112 (August 2022)
[article]
Titre : Tracking annual dynamics of mangrove forests in mangrove National Nature Reserves of China based on time series Sentinel-2 imagery during 2016–2020 Type de document : Article/Communication Auteurs : Rong Zhang, Auteur ; Mingming Jia, Auteur ; Zongming Wang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 102918 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] algorithme de Otsu
[Termes IGN] analyse d'image orientée objet
[Termes IGN] analyse diachronique
[Termes IGN] Chine
[Termes IGN] dynamique de la végétation
[Termes IGN] image Sentinel-MSI
[Termes IGN] mangrove
[Termes IGN] réserve naturelleRésumé : (auteur) Mangrove National Nature Reserves (MNNRs) play an extraordinarily significant role in conserving mangrove forests and their habitats. In China, one-fourth of the total mangrove forests were located in MNNRs. Understanding annual spatial distributions and conversions of these mangrove forests are important for precision conservation and rehabilitation efforts. However, to date, annual land cover maps of China’s MNNRs are still unavailable. Here, we proposed a rapid and robust approach to produce annual maps of each MNNRs for the time period of 2016–2020 based on 10-m resolution Sentinel-2 imagery. The proposed approach was developed using object-based image analysis, Otsu and Random Forest algorithm. Results showed that 1) during 2016–2020, areal extents of mangrove forest in all the MNNRs continuously increased from 5912 ha to 6128 ha; 2) obvious increase were found in Zhanjiang Mangrove National Nature Reserve where mangrove forest increased by 127 ha, accounted for 59% of national total increases; 3) newly grown mangrove forests were mainly converted from tidal flats and aquaculture ponds. Our annual maps of China’s MNNRs could provide a basis for managing mangrove ecosystems and supporting the implementation of Sustainable Development Goals related to coastal development. Numéro de notice : A2022-583 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.jag.2022.102918 En ligne : https://doi.org/10.1016/j.jag.2022.102918 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101348
in International journal of applied Earth observation and geoinformation > vol 112 (August 2022) . - n° 102918[article]Transfer learning from citizen science photographs enables plant species identification in UAV imagery / Salim Soltani in ISPRS Open Journal of Photogrammetry and Remote Sensing, vol 5 (August 2022)PermalinkUAV-borne, LiDAR-based elevation modelling: a method for improving local-scale urban flood risk assessment / Katerina Trepekli in Natural Hazards, vol 113 n° 1 (August 2022)PermalinkUncertainty interval estimates for computing slope and aspect from a gridded digital elevation model / Carlos López-Vázquez in International journal of geographical information science IJGIS, vol 36 n° 8 (August 2022)PermalinkPS-InSAR based validated landslide susceptibility modelling: a case study of Ghizer valley, Northern Pakistan / Sajid Hussain in Geocarto international, vol 37 n° 13 ([15/07/2022])PermalinkValidation of a corner reflector installation at Côte d’Azur multi-technique geodetic observatory / Xavier Collilieux in Advances in space research, vol 70 n° 2 (15 July 2022)PermalinkAdaptive transfer of color from images to maps and visualizations / Mingguang Wu in Cartography and Geographic Information Science, Vol 49 n° 4 (July 2022)PermalinkAdvancements in underground mine surveys by using SLAM-enabled handheld laser scanners / Artu Ellmann in Survey review, vol 54 n° 385 (July 2022)PermalinkDiscriminative information restoration and extraction for weakly supervised low-resolution fine-grained image recognition / Tiantian Yan in Pattern recognition, vol 127 (July 2022)PermalinkExploring the vertical dimension of street view image based on deep learning: a case study on lowest floor elevation estimation / Huan Ning in International journal of geographical information science IJGIS, vol 36 n° 7 (juillet 2022)PermalinkFusing Sentinel-2 and Landsat 8 satellite images using a model-based method / Jakob Sigurdsson in Remote sensing, vol 14 n° 13 (July-1 2022)PermalinkFusion of GNSS and InSAR time series using the improved STRE model: applications to the San Francisco bay area and Southern California / Huineng Yan in Journal of geodesy, vol 96 n° 7 (July 2022)PermalinkGANmapper: geographical data translation / Abraham Noah Wu in International journal of geographical information science IJGIS, vol 36 n° 7 (juillet 2022)PermalinkGeographic knowledge graph attribute normalization: Improving the accuracy by fusing optimal granularity clustering and co-occurrence analysis / Chuan Yin in ISPRS International journal of geo-information, vol 11 n° 7 (July 2022)PermalinkInvestigating the ability to identify new constructions in urban areas using images from unmanned aerial vehicles, Google Earth, and Sentinel-2 / Fahime Arabi Aliabad in Remote sensing, vol 14 n° 13 (July-1 2022)PermalinkInvestigating the role of image retrieval for visual localization / Martin Humenberger in International journal of computer vision, vol 130 n° 7 (July 2022)PermalinkLidar point-to-point correspondences for rigorous registration of kinematic scanning in dynamic networks / Aurélien Brun in ISPRS Journal of photogrammetry and remote sensing, vol 189 (July 2022)PermalinkQuantifying the influence of plot-level uncertainty in above ground biomass up scaling using remote sensing data in central Indian dry deciduous forest / Thangavelu Mayamanikandan in Geocarto international, vol 37 n° 12 ([01/07/2022])PermalinkA second-order attention network for glacial lake segmentation from remotely sensed imagery / Shidong Wang in ISPRS Journal of photogrammetry and remote sensing, vol 189 (July 2022)PermalinkSemantic feature-constrained multitask siamese network for building change detection in high-spatial-resolution remote sensing imagery / Qian Shen in ISPRS Journal of photogrammetry and remote sensing, vol 189 (July 2022)PermalinkSimulation-driven 3D forest growth forecasting based on airborne topographic LiDAR data and shading / Štefan Kohek in International journal of applied Earth observation and geoinformation, vol 111 (July 2022)Permalink