Centre dedocumentation
scientifique

A prediction model for surface deformation caused by underground mining based on spatio-temporal associations / Min Ren in Geomatics, Natural Hazards and Risk, vol 13 n° 1 (2022)  

Public [article]  inGeomatics, Natural Hazards and Risk > vol 13 n° 1 (2022) . - pp 94 - 122 Titre : A prediction model for surface deformation caused by underground mining based on spatio-temporal associations Type de document : Article/Communication Auteurs : Min Ren, Auteur ; Guanwen Cheng, Auteur ; Wancheng Zhu, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 94 - 122 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse des risques [Termes IGN] analyse spatio-temporelle [Termes IGN] Chine [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] déformation de la croute terrestre [Termes IGN] déformation de surface [Termes IGN] mine de fer [Termes IGN] modèle de simulation [Termes IGN] règle d'association Mots-clés libres : spatio-temporal association rule mining (STARM) Résumé : (auteur) Accurate predictions of the surface deformation caused by underground mining are crucial for the safe development of underground resources. Although surface deformation has been predicted by artificial intelligence (AI) methods, most AI models are established based on the relationships between surface deformation and influential factors. The lack of consideration of the deformation state transition often leads to errors in the prediction results of catastrophic deformation by conventional AI methods. In this respect, this study introduces a surface deformation prediction model based on spatio-temporal association rule mining (STARM). Surface deformation is classified as excessive deformation zone (EDZ) and hysteretic deformation zone (HDZ), representing different surface deformation stage or state. The spatio-temporal association rules between the monitored EDZ and HDZ data are then mined. A surface deformation prediction model is established according to the spatio-temporal relationship between monitored EDZ and HDZ data. The proposed model is verified based on a practical case study of the Chengchao Iron Mine in China. The data collection of the influential factors is not requisite for the proposed model. It can achieve accurate prediction of the catastrophic deformation that was characterized by deformation state transition. Numéro de notice : A2022-035 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/POSITIONNEMENT Nature : Article DOI : 10.1080/19475705.2021.2015460 Date de publication en ligne : 21/12/2021 En ligne : https://doi.org/10.1080/19475705.2021.2015460 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99359 [article]

Les journées de la Recherche IGN 2021 / Anonyme in Géomatique expert, n° 135 (septembre 2021)

Public [article]  inGéomatique expert > n° 135 (septembre 2021) . - pp 36 - 47 Titre : Les journées de la Recherche IGN 2021 Type de document : Article/Communication Auteurs : Anonyme, Auteur Année de publication : 2021 Conférence : Journées Recherche de l'IGN 2021, 30es Journées 25/05/2021 28/05/2021 en ligne France vidéos des journées Article en page(s) : pp 36 - 47 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Information géographique [Termes IGN] appariement d'images [Termes IGN] BD Topo [Termes IGN] chronométrie [Termes IGN] Copernicus (programme européen) [Termes IGN] correction radiométrique [Termes IGN] déformation de surface [Termes IGN] données GRACE [Termes IGN] éclairement lumineux [Termes IGN] extraction de données [Termes IGN] fonte des glaces [Termes IGN] horloge atomique [Termes IGN] ilot thermique urbain [Termes IGN] image aérienne [Termes IGN] intelligence artificielle [Termes IGN] MicMac [Termes IGN] modèle numérique de surface [Termes IGN] recherche scientifique [Termes IGN] série temporelle [Termes IGN] surveillance sanitaire [Termes IGN] visualisation de données Résumé : (Auteur) L’édition 2021 des Journées de la Recherche à l’IGN s’est déroulée, cette année encore, « en ligne ». C’était, malgré tout, l’occasion de marquer la trentième édition de l’événement. Numéro de notice : A2021-661 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE/POSITIONNEMENT Nature : Article nature-HAL : ArtSansCL DOI : sans Date de publication en ligne : 01/09/2021 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98481 [article]

Exemplaires (1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
IFN-001-P002273	PER	Revue	Nogent-sur-Vernisson	Salle périodiques	Exclu du prêt

Estimation of surface deformation due to Pasni earthquake using RADAR interferometry / Muhammad Ali in Geocarto international, vol 36 n° 14 ([01/08/2021])  

Public [article]  inGeocarto international > vol 36 n° 14 [01/08/2021] . - pp 1630 - 1645 Titre : Estimation of surface deformation due to Pasni earthquake using RADAR interferometry Type de document : Article/Communication Auteurs : Muhammad Ali, Auteur ; Muhammad Shahzad, Auteur ; Majir Nazeer, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 1630 - 1645 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] bande C [Termes IGN] déformation de surface [Termes IGN] déformation verticale de la croute terrestre [Termes IGN] image radar moirée [Termes IGN] image Sentinel-SAR [Termes IGN] interféromètrie par radar à antenne synthétique [Termes IGN] Pakistan [Termes IGN] polarisation [Termes IGN] rapport signal sur bruit [Termes IGN] séisme [Termes IGN] série temporelle Résumé : (auteur) This study analyzed the land deformation associated with Mw 6.3 earthquake along Pasni coast, Pakistan. Post-earthquake widespread surface displacements were found using Sentinel-1 data. Pre, Co and Post-seismic images were used to investigate the deformation trends. Before the earthquake, 89.65% of Pasni land mass showed uplifting from 0.0 to 3.0 cm at 1.00 mm/day while 3.0 cm subsidence was noted in 86.36% of the land mass after the earthquake at 2.5 mm/day. However, two weeks after the earthquake, 72.9% Pasni land mass showed uplifting at an unprecedented rate of 3.3 mm/day. The maximum deformation along the Line Of Sight (LOS) direction in co-seismic time was about -4.0 cm. Azimuthal interferogram showed more complex displacement pattern with both negative and positive displacements between ±5.0 cm. Pasni is already facing many problems due to increased sea water intrusion under prevailing climatic changes and land deformation due to strong earthquakes. Numéro de notice : A2021-557 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1661031 Date de publication en ligne : 09/09/2019 En ligne : https://doi.org/10.1080/10106049.2019.1661031 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98110 [article]

Spatio-temporal linking of multiple SAR satellite data from medium and high resolution Radarsat-2 images / Bin Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 176 (June 2021)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 176 (June 2021) . - pp 222 - 236 Titre : Spatio-temporal linking of multiple SAR satellite data from medium and high resolution Radarsat-2 images Type de document : Article/Communication Auteurs : Bin Zhang, Auteur ; Ling Chang, Auteur ; Alfred Stein, Auteur Année de publication : 2021 Article en page(s) : pp 222 - 236 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] déformation de surface [Termes IGN] données spatiotemporelles [Termes IGN] image radar moirée [Termes IGN] image Radarsat [Termes IGN] méthode de Monte-Carlo [Termes IGN] points homologues [Termes IGN] série temporelle Résumé : (auteur) A recent development in Interferometric Synthetic Aperture Radar (InSAR) technology is integrating multiple SAR satellite data to dynamically extract ground features. This paper addresses two relevant challenges: identification of common ground targets from different SAR datasets in space, and concatenation of time series when dealing with temporal dynamics. To address the first challenge, we describe the geolocation uncertainty of InSAR measurements as a three-dimensional error ellipsoid. The points, among InSAR measurements, which have error ellipsoids with a positive cross volume are identified as tie-point pairs representing common ground objects from multiple SAR datasets. The cross volumes are calculated using Monte Carlo methods and serve as weights to achieve the equivalent deformation time series. To address the second challenge, the deformation time series model for each tie-point pair is estimated using probabilistic methods, where potential deformation models are efficiently tested and evaluated. As an application, we integrated two Radarsat-2 datasets in Standard and Extra-Fine modes to map the subsidence of the west of the Netherlands between 2010 and 2017. We identified 18128 tie-point pairs, 5 intersection types of error ellipsoids, 5 deformation models, and constructed their long-term deformation time series. The detected maximum mean subsidence velocity in Line-Of-Sight direction is up to 15 . We conclude that our method removes limitations that exist in single-viewing-geometry SAR when integrating multiple SAR data. In particular, the proposed time-series modeling method is useful to achieve a long-term deformation time series of multiple datasets. Numéro de notice : A2021-414 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.04.005 Date de publication en ligne : 08/05/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.04.005 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97745 [article]

Saline-soil deformation extraction based on an improved time-series InSAR approach / Wei Xiang in ISPRS International journal of geo-information, vol 10 n° 3 (March 2021)  

Public [article]  inISPRS International journal of geo-information > vol 10 n° 3 (March 2021) . - n° 112 Titre : Saline-soil deformation extraction based on an improved time-series InSAR approach Type de document : Article/Communication Auteurs : Wei Xiang, Auteur ; Rui Zhang, Auteur ; Guoxiang Liu, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 112 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] bande C [Termes IGN] Chine [Termes IGN] déformation de surface [Termes IGN] extraction de traits caractéristiques [Termes IGN] image radar moirée [Termes IGN] image Sentinel-SAR [Termes IGN] série temporelle [Termes IGN] sol salin [Termes IGN] surface du sol [Termes IGN] variation saisonnière Résumé : (auteur) Significant seasonal fluctuations could occur in the regional scattering characteristics and surface deformation of saline soil, and cause decorrelation, which limits the application of the conventional time-series InSAR (TS-InSAR). For extending the saline-soil deformation monitoring capability, this paper presents an improved TS-InSAR approach, based on the interferometric coherence statistics and high-coherence interferogram refinement. By constructing a network of the refined interferograms, high-accuracy ground deformation can be extracted through the weighted least square estimation and the coherent target refinement. To extract the high-accuracy deformation of a representative saline soil area in the Qarhan Salt Lake, 119 C-band Sentinel-1A images collected between May 2015 and May 2020 are selected as the data source. Subsequently, 845 refined interferograms are selected from all possible interferograms to conduct the network inversion, based on the related thresholds (the temporal baseline 0.5, respectively). Compared with the conventional TS-InSAR measurements, both the accuracy and reliability of the extracted deformation results of the saline soil increased dramatically. Furthermore, the testing results indicate that the improved TS-InSAR method has advantages on the deformation extraction in the saline soil region, and is adaptive to reflecting the typical seasonal variations of the saline soil. Numéro de notice : A2021-234 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10030112 Date de publication en ligne : 27/02/2021 En ligne : https://doi.org/10.3390/ijgi10030112 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97230 [article]

Reclaimed-airport surface-deformation monitoring by improved permanent-scatterer interferometric synthetic-aperture radar: a case study of Shenzhen Bao'an international airport, China / Lu Miao in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 2 (February 2021)  

Permalink

Study of systematic bias in measuring surface deformation with SAR interferometry / Homa Ansari in IEEE Transactions on geoscience and remote sensing, vol 59 n° 2 (February 2021)  

Permalink

Local terrain modification method considering physical feature constraints for vector elements / Jiangfeng She in Cartography and Geographic Information Science, Vol 47 n° 5 (September 2020)  

Permalink

Landslide displacement mapping based on ALOS-2/PALSAR-2 data using image correlation techniques and SAR interferometry: application to the Hell-Bourg landslide (Salazie Circle, La Réunion Island) / Daniel Raucoules in Geocarto international, vol 35 n° 2 ([01/02/2020])  

Permalink

A spatio-temporal deformation model for laser scanning point clouds / Corinna Harmening in Journal of geodesy, vol 94 n°2 (February 2020)  

Permalink

Learning 3D generation and matching / Thibault Groueix (2020)  

Permalink

Système de traitement d’images temps réel dédié à la mesure de champs denses de déplacements et de déformations / Seyfeddine Boukhtache (2020)  

Permalink

Analyse de la déformation récente dans le Grand Tunis par interférométrie radar SAR / Anis Chaabani (2019)  

Permalink

Suivi géodésique des réservoirs souterrains / Eric Henrion (2019)  

Permalink

Estimation of 3-D surface displacement based on InSAR and deformation modeling / Jun Hu in IEEE Transactions on geoscience and remote sensing, vol 55 n° 4 (April 2017)  

Permalink