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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)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 60 n° 8 (August 2022) . - pp 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.pdf Langues : 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'appui Résumé : (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 [article]

Glacier mass loss in the Alaknanda basin, Garhwal Himalaya on a decadal scale / S.N. Remya in Geocarto international, vol 37 n° 10 ([01/06/2022])  

Public [article]  inGeocarto international > vol 37 n° 10 [01/06/2022] . - pp 3014 - 3032 Titre : Glacier mass loss in the Alaknanda basin, Garhwal Himalaya on a decadal scale Type de document : Article/Communication Auteurs : S.N. Remya, Auteur ; Anil V. Kulkarni, Auteur ; Tajdarul Hassan Syed, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 3014 - 3032 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] altitude [Termes IGN] analyse diachronique [Termes IGN] bilan de masse [Termes IGN] carte choroplèthe [Termes IGN] changement climatique [Termes IGN] fonte des glaces [Termes IGN] glacier [Termes IGN] Himalaya [Termes IGN] image Cartosat-1 [Termes IGN] MNS SRTM [Termes IGN] point d'appui Résumé : (auteur) The Himalayan glaciers significantly contribute to the largest river systems like the Indus, Ganga, and the Brahmaputra. The change in glacial area and mass can affect the mountain community and people living in the Indo-Gangetic plain. The present study adopted the geodetic method to estimate the elevation change and mass budget of 61 glaciers in the Alaknanda Basin, using the satellite data of Cartosat-1 (2011, 2014, 2017) and SRTM (2000). Besides, the DEM of 1962 (SOI Toposheet) and 2000 (SRTM) is used to estimate the mass budget of Satopanth (SPG) and Bhagirath Kharak glaciers (BKG). The field debris thickness of SPG (2015-2017) is compared with the elevation change (2000-2017). Further, we have compared the mass loss of the glaciers with their volume. The results suggest the sustained mass loss of 1.85 ± 0.10 Gt out of 33.9 ± 8.8 Gt for 61 glaciers in the basin from 2000-2017. The mass loss of SPG and BKG during 2000-2017 is 0.20 ± 0.02 Gt and 0.24 ± 0.03 Gt, whereas from 1962 to 2000, is 0.083 ± 0.03 Gt and 0.091 ± 0.04 Gt, respectively. The analysis facilitates a better understanding of glacier mass changes in the Alaknanda basin on a multi-decadal scale. Numéro de notice : A2022-597 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2020.1844309 En ligne : https://doi.org/10.1080/10106049.2020.1844309 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101301 [article]

Physical modelling of Nanda Devi National Park, a natural world heritage site, from GIS data / Sanat Agrawal in Cartographica, vol 57 n° 2 (Summer 2022)  

Public [article]  inCartographica > vol 57 n° 2 (Summer 2022) . - pp 179 - 194 Titre : Physical modelling of Nanda Devi National Park, a natural world heritage site, from GIS data Type de document : Article/Communication Auteurs : Sanat Agrawal, Auteur ; Akshay Jain, Auteur Année de publication : 2022 Article en page(s) : pp 179 - 194 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] conservation du patrimoine [Termes IGN] Himalaya [Termes IGN] Inde [Termes IGN] modèle numérique de surface [Termes IGN] modèle physique [Termes IGN] patrimoine naturel [Termes IGN] QGIS [Termes IGN] site [Termes IGN] surface du sol [Termes IGN] système d'information géographique Résumé : (auteur) A methodology has been developed to create a physical model of the Nanda Devi National Park (NDNP), a Natural World Heritage Site (NWHS), by additive fabrication, to facilitate effective communication among the stakeholders for conservation management. The GIS data of a terrain give elevation values on the surface of a terrain only and lack 3D definition. The DEM ASCII XYZ file format is converted into a 3D STL file with walls and a base. Gaps and singularities in the data are taken care of. There is ample scope for aiding conservation management and restoration of NWHS sites using additive manufacturing (AM). A physical model of the NDNP was created using the methodology. The model holds very high value for long-term monitoring of the NWHS and the Himalayas. The physical model of the NDNP can serve as an effective medium of communication for conservation management. Physical models of the glacial basins or the Nanda Devi peak will provide further value. The research work can be extended to making models of the NDNP of larger sizes or by focusing on smaller region of the NDNP in consultation with the stakeholders. Numéro de notice : A2022-636 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3138/cart-2021-0025 Date de publication en ligne : 25/06/2022 En ligne : https://doi.org/10.3138/cart-2021-0025 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101426 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
031-2022021	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Detection and mapping of snow avalanche debris from Western Himalaya, India using remote sensing satellite images / Kamal Kant Singh in Geocarto international, vol 37 n° 9 ([15/05/2022])  

Public [article]  inGeocarto international > vol 37 n° 9 [15/05/2022] . - pp 2561 - 2579 Titre : Detection and mapping of snow avalanche debris from Western Himalaya, India using remote sensing satellite images Type de document : Article/Communication Auteurs : Kamal Kant Singh, Auteur ; Dhiraj Kumar Singh, Auteur ; Narinder Kumar Thakur, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 2561 - 2579 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse d'image orientée objet [Termes IGN] avalanche [Termes IGN] Himalaya [Termes IGN] image Sentinel-MSI [Termes IGN] matrice de co-occurrence [Termes IGN] modèle numérique de surface [Termes IGN] réflectance [Termes IGN] signature spectrale Résumé : (auteur) Release of snow avalanche from a mountain slope depends on various parameters such as snow cover, terrain and meteorological conditions of the region. The precise information of avalanche occurrence in terms of its location and extent is essentially important for hazard mapping and for avalanche occurrence feedback. In the present study, various techniques have been explored for automatic detection and mapping of snow avalanche debris for a part of Western Himalayan region using Sentinel-2 satellite data. Spectral signatures of avalanche and non-avalanche snow collected from the field spectroradiometer survey are used for identifying suitable spectral bands of Sentinel-2 for avalanche debris detection. Techniques such as Ratio Method, Gray Level Co-occurrence Matrix, a new proposed index, i.e. Avalanche Debris Index and Object-Based Image Analysis (OBIA) are applied on satellite images to retrieve the avalanche debris. Retrieved avalanche debris are further compared with the manually digitized avalanche occurred boundaries. The OBIA method has been found the most suitable for avalanche debris detection and mapping using the medium resolution satellite data. Numéro de notice : A2022-565 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2020.1762762 Date de publication en ligne : 26/05/2020 En ligne : https://doi.org/10.1080/10106049.2020.1762762 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101245 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
059-2022091	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Lithological mapping based on fully convolutional network and multi-source geological data / Ziye Wang in Remote sensing, vol 13 n° 23 (December-1 2021)  

Public [article]  inRemote sensing > vol 13 n° 23 (December-1 2021) . - n° 4860 Titre : Lithological mapping based on fully convolutional network and multi-source geological data Type de document : Article/Communication Auteurs : Ziye Wang, Auteur ; Renguang Zuo, Auteur ; Hao Liu, Auteur Année de publication : 2021 Article en page(s) : n° 4860 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte [Termes IGN] apprentissage profond [Termes IGN] carte géologique [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] données géologiques [Termes IGN] fusion de données multisource [Termes IGN] Himalaya [Termes IGN] lithologie [Termes IGN] segmentation sémantique Résumé : (auteur) Deep learning algorithms have found numerous applications in the field of geological mapping to assist in mineral exploration and benefit from capabilities such as high-dimensional feature learning and processing through multi-layer networks. However, there are two challenges associated with identifying geological features using deep learning methods. On the one hand, a single type of data resource cannot diagnose the characteristics of all geological units; on the other hand, deep learning models are commonly designed to output a certain class for the whole input rather than segmenting it into several parts, which is necessary for geological mapping tasks. To address such concerns, a framework that comprises a multi-source data fusion technology and a fully convolutional network (FCN) model is proposed in this study, aiming to improve the classification accuracy for geological mapping. Furthermore, multi-source data fusion technology is first applied to integrate geochemical, geophysical, and remote sensing data for comprehensive analysis. A semantic segmentation-based FCN model is then constructed to determine the lithological units per pixel by exploring the relationships among multi-source data. The FCN is trained end-to-end and performs dense pixel-wise prediction with an arbitrary input size, which is ideal for targeting geological features such as lithological units. The framework is finally proven by a comparative study in discriminating seven lithological units in the Cuonadong dome, Tibet, China. A total classification accuracy of 0.96 and a high mean intersection over union value of 0.9 were achieved, indicating that the proposed model would be an innovative alternative to traditional machine learning algorithms for geological feature mapping. Numéro de notice : A2021-878 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs13234860 Date de publication en ligne : 30/11/2021 En ligne : https://doi.org/10.3390/rs13234860 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99146 [article]

Snow cover change assessment in the upper Bhagirathi basin using an enhanced cloud removal algorithm / Mritunjay Kumar Singh in Geocarto international, vol 36 n° 20 ([01/12/2021])  

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Joint inversion of ground gravity data and satellite gravity gradients between Nepal and Bhutan: New insights on structural and seismic segmentation of the Himalayan arc / Rodolphe Cattin in Physics and chemistry of the Earth (A/B/C), vol 123 (October 2021)  

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Orogenic collapse and stress adjustments revealed by an intense seismic swarm following the 2015 Gorkha earthquake in Nepal / Lok Bijaya Adhikari in Frontiers in Earth Science, vol 9 (2021)  

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Basin-scale high-resolution extraction of drainage networks using 10-m Sentinel-2 imagery / Zifeng Wang in Remote sensing of environment, Vol 255 (March 2021)  

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Landslide susceptibility mapping and assessment using geospatial platforms and weights of evidence (WoE) method in the indian Himalayan region: Recent developments, gaps, and future directions / Amit Batar in ISPRS International journal of geo-information, vol 10 n° 3 (March 2021)  

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Une nouvelle détermination de l'altitude de l'Everest par le Népal et la Chine / Gavin Schrock in XYZ, n° 166 (mars 2021)

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Optimizing flood mapping using multi-synthetic aperture radar images for regions of the lower mekong basin in Vietnam / Vu Anh Tuan in European journal of remote sensing, vol 54 n° 1 (2021)  

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Les impacts spatiaux du changement climatique / Denis Mercier (2021)

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Wide-area near-real-time monitoring of tropical forest degradation and deforestation using Sentinel-1 / Dirk Hoekman in Remote sensing, vol 12 n° 19 (October-1 2020)  

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Mapping croplands of Europe, Middle East, Russia, and Central Asia using Landsat, Random Forest, and Google Earth Engine / Aparna R. Phalke in ISPRS Journal of photogrammetry and remote sensing, vol 167 (September 2020)  

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