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Using machine learning to map Western Australian landscapes for mineral exploration / Thomas Albrecht in ISPRS International journal of geo-information, vol 10 n° 7 (July 2021)  

Public [article]  inISPRS International journal of geo-information > vol 10 n° 7 (July 2021) . - n° 459 Titre : Using machine learning to map Western Australian landscapes for mineral exploration Type de document : Article/Communication Auteurs : Thomas Albrecht, Auteur ; Ignacio Gonzalez-Alvarez, Auteur ; Jens Klump, Auteur Année de publication : 2021 Article en page(s) : n° 459 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] apprentissage automatique [Termes IGN] Australie occidentale (Australie) [Termes IGN] cartographie automatique [Termes IGN] classification dirigée [Termes IGN] classification par forêts aléatoires [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] géomorphologie [Termes IGN] modèle numérique de surface [Termes IGN] prospection minérale [Termes IGN] Python (langage de programmation) Résumé : (auteur) Landscapes evolve due to climatic conditions, tectonic activity, geological features, biological activity, and sedimentary dynamics. Geological processes at depth ultimately control and are linked to the resulting surface features. Large regions in Australia, West Africa, India, and China are blanketed by cover (intensely weathered surface material and/or later sediment deposition, both up to hundreds of metres thick). Mineral exploration through cover poses a significant technological challenge worldwide. Classifying and understanding landscape types and their variability is of key importance for mineral exploration in covered regions. Landscape variability expresses how near-surface geochemistry is linked to underlying lithologies. Therefore, landscape variability mapping should inform surface geochemical sampling strategies for mineral exploration. Advances in satellite imaging and computing power have enabled the creation of large geospatial data sets, the sheer size of which necessitates automated processing. In this study, we describe a methodology to enable the automated mapping of landscape pattern domains using machine learning (ML) algorithms. From a freely available digital elevation model, derived data, and sample landclass boundaries provided by domain experts, our algorithm produces a dense map of the model region in Western Australia. Both random forest and support vector machine classification achieve approximately 98% classification accuracy with a reasonable runtime of 48 minutes on a single Intel® Core™ i7-8550U CPU core. We discuss computational resources and study the effect of grid resolution. Larger tiles result in a more contiguous map, whereas smaller tiles result in a more detailed and, at some point, noisy map. Diversity and distribution of landscapes mapped in this study support previous results. In addition, our results are consistent with the geological trends and main basement features in the region. Mapping landscape variability at a large scale can be used globally as a fundamental tool for guiding more efficient mineral exploration programs in regions under cover. Numéro de notice : A2021-546 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10070459 date de publication en ligne : 06/07/2021 En ligne : https://doi.org/10.3390/ijgi10070459 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98048 [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)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 58 n° 8 (August 2020) . - pp 5393 - 5399 Titre : Novel communication channel model for signal propagation and loss through layered earth Type de document : Article/Communication Auteurs : David O. LeVan, Auteur Année de publication : 2020 Article en page(s) : pp 5393 - 5399 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement du signal [Termes IGN] atténuation du signal [Termes IGN] champ électromagnétique [Termes IGN] cible souterraine [Termes IGN] géophysique [Termes IGN] mine de charbon [Termes IGN] modèle de simulation [Termes IGN] modèle mathématique [Termes IGN] modélisation [Termes IGN] propagation du signal [Termes IGN] Terre (planète) Résumé : (auteur) Signal propagation through-the-Earth (TTE) is of great importance to geophysicists searching for underground resources such as oil and gas, homeland defense searching for tunnels and underground structures, and mining operations. The Earth is a conductive medium, unlike air or space, which tends to “short-out” electromagnetic fields traditionally used for wireless communications. The magnitude of this effect depends on many factors, such as frequency and the type of Earth-material. Mathematical models of energy propagation have been developed to help us understand the signal propagation issues, and some models can be used to predict the performance of the specific electromagnetic energies being used. There are numerous ways of modeling the Earth to study energy propagation. Some early literature presented models of signal propagation through a homogeneous Earth. These were fairly accurate for signals traveling from one point in the Earth to another point. However, signals traveling from below the ground to the surface of the Earth encounter many different layers of the Earth. This realization led to the development of models of a layered Earth. A novel layered-Earth communication model is presented and evaluated as to its accuracy by using measured data gathered during TTE communication tests from 2007 to 2012. Evaluations show that the new layered-EARTH model provides improved accuracy for the prediction of signal propagation performance from within a subterranean space, such as a mine, to and from the surface of the Earth. Numéro de notice : A2020-472 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.2965398 date de publication en ligne : 28/01/2020 En ligne : https://doi.org/10.1109/TGRS.2020.2965398 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95575 [article]

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)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 165 (July 2020) . - pp 1 - 15 Titre : Complete and accurate data correction for seamless mosaicking of airborne hyperspectral images: A case study at a mining site in Inner Mongolia, China Type de document : Article/Communication Auteurs : Kun Tan, Auteur ; Chao Niu, Auteur ; Xiuping Jia, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 1 - 15 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] atténuation [Termes IGN] correction atmosphérique [Termes IGN] distorsion du signal [Termes IGN] distribution du coefficient de réflexion bidirectionnelle BRDF [Termes IGN] image hyperspectrale [Termes IGN] mine [Termes IGN] Mongolie intérieure (Chine) [Termes IGN] mosaïquage d'images [Termes IGN] radiance [Termes IGN] rayonnement infrarouge [Termes IGN] réflectance de surface [Termes IGN] Short Waves InfraRed [Termes IGN] spectroradiométrie [Termes IGN] surveillance écologique Résumé : (auteur) Airborne hyperspectral remote sensing is an important application in the ecological monitoring of the environment in mining areas, and accurate preprocessing of the original images is the key to quantitative information retrieval. The original image data need radiation correction to acquire surface reflectance data. Due to the impact of the field angle, incidental radiance, and the bidirectional reflectance distribution function (BRDF), there can be a brightness gradient between adjacent strips, which leads to radiance difference and obvious chromatic aberration of the mosaicked images. We propose a novel data correction method for seamless mosaicking of airborne hyperspectral images. Firstly, visible and near-infrared (VNIR) and shortwave infrared (SWIR) sensors are calibrated in the laboratory, and the radiation calibration model of the sensor is established by an integrating-sphere system. A correction function is then established by combining the BRDF effect and the radiation attenuation coefficients. We also normalize the exposure time, sun altitude angle, and sensor altitude angle according to the flight strip. The results showed that this method is able to eliminate the signal distortion, allowing the seamless mosaicking of 37 strip images which were taken in different date and conditions in the study area. After the atmospheric correction of the imagery was completed, the accuracy of the preprocessing results was evaluated by field-measured ASD spectroradiometer data. The coefficient of determination R2 of the results for the reflectance was greater than 0.9. The experiments show that the proposed method has a good performance in radiation accuracy, and can provide high-quality hyperspectral data for the follow-up application of the ecological monitoring of a mining area. Numéro de notice : A2020-465 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.04.022 date de publication en ligne : 16/05/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.04.022 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95092 [article]

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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)  

Public [article]  inJournal of geodesy > vol 94 n° 5 (May 2020) Titre : 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 Type de document : Article/Communication Auteurs : Yuedong Wang, Auteur ; Zefa Yang, Auteur ; Zhiwei Li, Auteur ; et al., Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] analyse des risques [Termes IGN] Chine [Termes IGN] déformation de la croute terrestre [Termes IGN] données localisées 3D [Termes IGN] données polarimétriques [Termes IGN] échantillonnage de données [Termes IGN] image ALOS-PALSAR [Termes IGN] image radar moirée [Termes IGN] interféromètrie par radar à antenne synthétique [Termes IGN] méthode des moindres carrés [Termes IGN] mine de charbon [Termes IGN] série temporelle [Termes IGN] surveillance géologique Résumé : (auteur) Interferometric synthetic aperture radar (InSAR) technology can be used to observe high spatial resolution one-dimensional (1-D) deformation along the line-of-sight direction from a single-track synthetic aperture radar (SAR) dataset. With the aid of multi-track InSAR data or a prior model, InSAR can be extended to infer 3-D deformation information, but the temporal resolution is generally limited. This paper presents an InSAR-based method to retrieve high spatio-temporal resolution 3-D displacements over mining areas (hereafter referred to as the MTI-based method). The core idea of the proposed method is to enhance the temporal resolution of the time-series 3-D displacement estimates by fusing multi-track InSAR observations and a prior model. Firstly, we retrieve high spatial resolution 3-D mining displacements from single-track InSAR 1-D deformation observations, with the assistance of the prior deformation model. By applying this approach to multi-track InSAR data over the same area, we obtain much denser 3-D mining displacement samples in time than those derived from a single-track InSAR dataset. Secondly, we propose a generalized weighted least-squares method to integrate the denser 3-D displacement samples, to solve the high temporal resolution 3-D mining displacements, in which the rank deficiency needs to be tackled. Finally, time-series 3-D mining displacements at the chronological dates of all the available multi-track SAR images are estimated. The Yungang coal mining area of China was selected to test the proposed method using two adjacent-track ALOS PALSAR-1 datasets. Compared with the single-track InSAR-derived results, the proposed method not only significantly improves the temporal resolution of the monitoring results by 42.6%, obtaining more detailed 3-D displacements, but it also provides important data support for understanding and modeling the distinctive kinematics of mining deformation and assessing mining-related geohazards. What is more, the core idea of the proposed method will be beneficial to high spatio-temporal resolution 3-D deformation estimation in other geophysical processes. Numéro de notice : A2020-239 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-020-01374-8 date de publication en ligne : 23/04/2020 En ligne : https://doi.org/10.1007/s00190-020-01374-8 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94992 [article]

Geological map generalization driven by size constraints / Azimjon Sayidov in ISPRS International journal of geo-information, vol 9 n° 4 (April 2020)  

Public [article]  inISPRS International journal of geo-information > vol 9 n° 4 (April 2020) . - 29 p. Titre : Geological map generalization driven by size constraints Type de document : Article/Communication Auteurs : Azimjon Sayidov, Auteur ; Meysam Aliakbarian, Auteur ; Robert Weibel, Auteur Année de publication : 2020 Article en page(s) : 29 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] algorithme de généralisation [Termes IGN] carte géologique [Termes IGN] données environnementales [Termes IGN] généralisation automatique de données [Termes IGN] opérateur de généralisation [Termes IGN] programmation par contraintes [Termes IGN] prospection minérale [Termes IGN] taille (variable visuelle) [Vedettes matières IGN] Généralisation Résumé : (auteur) Geological maps are an important information source used in the support of activities relating to mining, earth resources, hazards, and environmental studies. Owing to the complexity of this particular map type, the process of geological map generalization has not been comprehensively addressed, and thus a complete automated system for geological map generalization is not yet available. In particular, while in other areas of map generalization constraint-based techniques have become the prevailing approach in the past two decades, generalization methods for geological maps have rarely adopted this approach. This paper seeks to fill this gap by presenting a methodology for the automation of geological map generalization that builds on size constraints (i.e., constraints that deal with the minimum area and distance relations in individual or pairs of map features). The methodology starts by modeling relevant size constraints and then uses a workflow consisting of generalization operators that respond to violations of size constraints (elimination/selection, enlargement, aggregation, and displacement) as well as algorithms to implement these operators. We show that the automation of geological map generalization is possible using constraint-based modeling, leading to improved process control compared to current approaches. However, we also show the limitations of an approach that is solely based on size constraints and identify extensions for a more complete workflow. Numéro de notice : A2020-261 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9040284 date de publication en ligne : 24/04/2020 En ligne : https://doi.org/10.3390/ijgi9040284 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95021 [article]

Spatial visualization of quantitative landscape changes in an industrial region between 1827 and 1883. Case study Katowice, southern Poland / Paweł Cybulski in Journal of maps, vol 16 n° 1 ([02/01/2020])  

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Optimisation des services de positionnement GNSS pour les opérations offshore d’Exploration Production de Total / Gautier Jolain (2020)  

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Relevé et modélisation 3D de la carrière de Froidmont (Aisne) / Angélique Richard (2020)  

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Mapping the wavelength position of mineral features in hyperspectral thermal infrared data / Christoph Hecker in International journal of applied Earth observation and geoinformation, vol 79 (July 2019)  

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Exploitation of hyperspectral data for assessing vegetation health under exposure to petroleum hydrocarbons / Guillaume Lassalle (2019)  

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Application of Landsat-8 and ASTER satellite remote sensing data for porphyry copper exploration: a case study from Shahr-e-Babak, Kerman, south of Iran / Morteza Safari in Geocarto international, vol 33 n° 11 (November 2018)  

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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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