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The fractional vegetation cover (FVC) and associated driving factors of modeling in mining areas / Jun Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 10 (October 2022)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 88 n° 10 (October 2022) . - pp 665 - 671 Titre : The fractional vegetation cover (FVC) and associated driving factors of modeling in mining areas Type de document : Article/Communication Auteurs : Jun Li, Auteur ; Tianyu Guo, Auteur ; Chengye Zhang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 665 - 671 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse comparative [Termes IGN] Chine [Termes IGN] couvert végétal [Termes IGN] Google Earth Engine [Termes IGN] hétérogénéité spatiale [Termes IGN] image Landsat-ETM+ [Termes IGN] image Landsat-OLI [Termes IGN] industrie minière [Termes IGN] mine [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] régression géographiquement pondérée [Termes IGN] régression multiple [Termes IGN] réseau neuronal artificiel Résumé : (auteur) To determine the fractional vegetation cover (FVC) and associated driving factors of modeling in mining areas, six types of data were used as driving factors and three methods —multi-linear regression (MLR), geographically weighted regression (GWR), and geographically weighted artificial neural network (GWANN)— were adopted in the modeling. The experiments, conducted in Shengli mining areas located in Xilinhot city, China, show that the MLR model without consideration of spatial heterogeneity and spatial non-stationarity performs the worst and that the GWR model presents obvious location differences, since it predefines a linear relationship which is unable to describe FVC for some locations. The GWANN model, improving on these defects, is the most suitable model for the FVC driving process in mining areas; it outperforms the other two models, with root-mean-square error (RMSE) and mean absolute percentage error (MAPE) reaching 0.16 and 0.20. It has improvements of approximately 24% in RMSE and 33% in MAPE compared to the MLR model, and those values grow to 59% and 71% when compared with the GWR model. Numéro de notice : A2022-813 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.21-00070R3 Date de publication en ligne : 01/10/2022 En ligne : https://doi.org/10.14358/PERS.21-00070R3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101973 [article]

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Advancements in underground mine surveys by using SLAM-enabled handheld laser scanners / Artu Ellmann in Survey review, vol 54 n° 385 (July 2022)  

Public [article]  inSurvey review > vol 54 n° 385 (July 2022) . - pp 363 - 374 Titre : Advancements in underground mine surveys by using SLAM-enabled handheld laser scanners Type de document : Article/Communication Auteurs : Artu Ellmann, Auteur ; Kaia Kütimets, Auteur ; Sander Varbla, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 363 - 374 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] arpentage [Termes IGN] carrière souterraine [Termes IGN] cartographie et localisation simultanées [Termes IGN] données lidar [Termes IGN] Estonie [Termes IGN] géoréférencement [Termes IGN] industrie minière [Termes IGN] mine [Termes IGN] modélisation 3D [Termes IGN] schiste [Termes IGN] semis de points [Termes IGN] système de numérisation mobile [Termes IGN] télémètre laser terrestre Résumé : (auteur) Applicability of SLAM (simultaneous localization and mapping) technology for mine surveys and subsequent 3D modelling of post-extracted surfaces is assessed. The resulting surface geometry is validated via terrestrial laser scanner (TLS) acquired reference data. Typical discrepancies remained within 2 and 5 cm in horizontal and vertical directions, respectively. Discrepancies between TLS, SLAM-enabled handheld scanner and conventional surveying results are small and fully satisfy the contemporary accuracy requirements, yet evidence that the conventional mine survey results are affected by the subjectivity of the surveyors. The SLAM-enabled laser scanning hence appears to be the most suitable method for underground mining surveys. Numéro de notice : A2022-537 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2021.1944545 Date de publication en ligne : 07/07/2021 En ligne : https://doi.org/10.1080/00396265.2021.1944545 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101093 [article]

Risk assessment and prediction of forest health for effective geo-environmental planning and monitoring of mining affected forest area in hilltop region / Narayan Kayet in Geocarto international, vol 37 n° 11 ([15/06/2022])  

Public [article]  inGeocarto international > vol 37 n° 11 [15/06/2022] . - pp 3091 - 3115 Titre : Risk assessment and prediction of forest health for effective geo-environmental planning and monitoring of mining affected forest area in hilltop region Type de document : Article/Communication Auteurs : Narayan Kayet, Auteur ; Khanindra Pathak, Auteur ; Abhisek Chakrabarty, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 3091 - 3115 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] analyse de sensibilité [Termes IGN] analyse multicritère [Termes IGN] impact sur l'environnement [Termes IGN] mine [Termes IGN] prévention des risques [Termes IGN] processus de hiérarchisation analytique [Termes IGN] santé des forêts Résumé : (auteur) This paper focuses on forest health risk (FHR) assessment and prediction in the mining-affected forest region using AHP model based on multi-criteria analysis in a GIS platform. We considered a total twenty-eight (twenty two present and six predicted) causative parameters including climate, natural or geomorphological, forestry, topographical, environmental, and anthropogenic. The assessment results of FHR show that of the total existing forest area, 2.85% area under very high, 13.63% high, 31.98% moderate, 32.68% low, and 18.87% are under very low categories. According to the assessment and prediction FHR results, the very high-risk classes were found at mines surrounding forest compartments. The sensitivity analysis showed that some factors were more sensitive to FHR. The correlation results showed a negative relationship between FHR and distance from mines and foliar dust concentration. This work will provide a basic guideline for effective planning and management in forestry studies for the mining-affected region. Numéro de notice : A2022-585 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2020.1849413 Date de publication en ligne : 08/12/2020 En ligne : https://doi.org/10.1080/10106049.2020.1849413 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101358 [article]

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 (2022)  

Public [article]  inGeomatics, Natural Hazards and Risk > vol 13 (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]

Validation of the accuracy of geodetic automated measurement system based on GNSS platform for continuous monitoring of surface movements in post-mining areas / Violetta Sokoła-Szewioła in Reports on geodesy and geoinformatics, vol 112 n° 1 (December 2021)  

Public [article]  inReports on geodesy and geoinformatics > vol 112 n° 1 (December 2021) . - pp 47 - 57 Titre : Validation of the accuracy of geodetic automated measurement system based on GNSS platform for continuous monitoring of surface movements in post-mining areas Type de document : Article/Communication Auteurs : Violetta Sokoła-Szewioła, Auteur ; Zbigniew Siejka, Auteur Année de publication : 2021 Article en page(s) : pp 47 - 57 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes IGN] coordonnées GNSS [Termes IGN] mine [Termes IGN] Pologne [Termes IGN] positionnement cinématique en temps réel [Termes IGN] précision du positionnement [Termes IGN] surveillance géologique Résumé : (auteur) The problem involving the monitoring of surface ground movements in post-mining areas is particularly important during the period of mine closures. During or after flooding of a mine, mechanical properties of the rock mass may be impaired, and this may trigger subsidence, surface landslides, uplift, sinkholes or seismic activity. It is, therefore, important to examine and select updating methods and plans for long-term monitoring of post-mining areas to mitigate seismic hazards or surface deformation during and after mine closure. The research assumed the implementation of continuous monitoring of surface movements using the Global Navigation Satellite System (GNSS) in the area of a closed hard coal mine ‘Kazimierz-Juliusz’, located in Poland. In order to ensure displacement measurement results with the accuracy of several millimetres, the accuracy of multi-GNSS observations carried out in real time as a combination of four global navigation systems, Global Positioning System (GPS), Globalnaja Navigacionnaja Sputnikova Sistema (GLONASS), Galileo and BeiDou, was determined. The article presents the results of empirical research conducted at four reference points. The test observations were made in variants comprising measurements based on: GPS, GPS and GLONASS systems, GPS, GLONASS and Galileo systems, GPS, GLONASS, Galileo and BeiDou systems. For each adopted solution, daily measurement sessions were performed using the RTK technique. The test results were subjected to accuracy analyses. Based on the obtained results, it was found that GNSS measurements should be carried out with the use of three navigation systems (GPS, GLONASS, Galileo), as an optimal solution for the needs of continuous geodetic monitoring in the area of the study. Numéro de notice : A2021-963 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.2478/rgg-2021-0007 Date de publication en ligne : 30/12/2021 En ligne : https://doi.org/10.2478/rgg-2021-0007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100115 [article]

Novel communication channel model for signal propagation and loss through layered earth / David O. LeVan in IEEE Transactions on geoscience and remote sensing, vol 58 n° 8 (August 2020)  

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Complete and accurate data correction for seamless mosaicking of airborne hyperspectral images: A case study at a mining site in Inner Mongolia, China / Kun Tan in ISPRS Journal of photogrammetry and remote sensing, vol 165 (July 2020)  

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Fusing adjacent-track InSAR datasets to densify the temporal resolution of time-series 3-D displacement estimation over mining areas with a prior deformation model and a generalized weighting least-squares method / Yuedong Wang in Journal of geodesy, vol 94 n° 5 (May 2020)  

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Estimating the volume of an open-pit mine using UAV photogrammetry / Marion Brunet (2018) 

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La mine en France : histoire industrielle et sociale / Michel Pascal (2018)

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Waste heaps left by historical Zn-Pb ore mining are hotspots of species diversity of beech forest understory vegetation / Marcin W. Woch in Science of the total environment, vol 599 - 600 (December 2017)  

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What miners want / Lewis Graham in GEO: Geoconnexion international, vol 16 n° 6 (June2017)

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Underground incrementally deployed magneto-inductive 3-D positioning network / Traian E. Abrudan in IEEE Transactions on geoscience and remote sensing, vol 54 n° 8 (August 2016)  

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Above-ground and below-ground competition between the willow Salix caprea and its understorey / Ondřej Mudrák in Journal of vegetation science, vol 27 n° 1 (January 2016)  

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Spatial distribution of coal quality parameters with respect to production requirements: an adaptive neuro-fuzzy application for the Can coal field (Turkey) / Ali Kayabasi in Geocarto international, vol 31 n° 1 - 2 (January - February 2016)  

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