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1.
Application of surface-wave tomography to mineral exploration: a case study from Siilinjärvi,Finland
Federico Da Col Myrto Papadopoulou Emilia Koivisto Łukasz Sito Mikko Savolainen Laura Valentina Socco 《Geophysical Prospecting》2020,68(1):254-269
In order to assess the feasibility and validity of surface-wave tomography as a tool for mineral exploration, we present an active seismic three-dimensional case study from the Siilinjärvi mine in Eastern Finland. The aim of the survey is to identify the formation carrying the mineralization in an area south of the main pit, which will be mined in the future. Before acquiring the data, we performed an accurate survey design to maximize data coverage and minimize the time for deployment and recollection of the equipment. We extract path-averaged Rayleigh-wave phase-velocity dispersion curves by means of a two-station method. We invert them using a computationally efficient tomographic code which does not require the computation of phase-velocity maps and inverts directly for one-dimensional S-wave velocity models. The retrieved velocities are in good agreement with the data from a borehole in the vicinity, and the pseudo three–dimensional S-wave velocity volume allows us to identify the geological contact between the formation hosting most of the mineralization and the surrounding rock. We conclude that the proposed method is a valid tool, given the small amount of equipment used and the acceptable amount of time required to process the data. 相似文献
2.
本文利用全球陆面数据同化系统与降雨观测数据,以陕西半湿润区陈河流域为研究对象,驱动WRF-Hydro模型,研究该模型的表现和适用性,并在结构、参数、输入输出和模拟结果方面与新安江模型对比.考虑到次表面层与实际包气带的区别,引入土层厚度乘子ZSOILFAC对前者进行等比缩放,发现其与新安江模型反推包气带的厚度有较好的一致性.研究表明:在陈河流域中WRF-Hydro计算步长须在建议值的基础上缩小; WRF-Hydro模型善于模拟洪水细节,新安江模型表现好且稳定;前者的径流深和洪峰合格率平于或略低于后者;在两个指标均合格的洪水中,前者平均均方根误差比后者小21.5%,但对于其他洪水,前者平均均方根误差比后者大56.2%; WRF-Hydro在洪水起涨时刻模拟较好,表现出其在中小流域应用的潜力. 相似文献
3.
China’s tourism industry has witnessed rapid progress in recent years, and is now an important part of global tourism in dealing with climate change. Within a framework of Pressure-State-Response (PSR), this paper focuses on the emission reduction pressure, carbon emission status, and responses of stakeholders in China’s tourism industry. Findings include: 1) The central government’s strategy and rapid growth of the industry scale exert rising pressure on China’s tourism to reduce carbon emissions. 2) Carbon emissions of China's tourism account for 13%-14.6% of global tourism, and about 3% of China’s emissions overall. Chinese tourists’ per capita carbon emission is lower than half of the global level. 3) The Chinese government attaches great importance to energy-saving and carbon emission reduction. In the tourism industry, documents, standards and other regulative measures have been issued to ensure that business practitioners set up green operational and managerial systems. In the field of tourism transportation, China's high-speed rail, new energy vehicles, and urban shared bicycles, have developed very rapidly in recent years, and they have effectively reduced the carbon emissions in traveling. Furthermore, this paper finds that Chinese tourists already have awareness and willingness for low-carbon tourism. 相似文献
4.
纱岭金矿床位于焦家断裂中南段,属于典型的焦家式金矿床,探获金资源量约389.2t,目前是国内平均勘查深度最大的金矿床。为进一步探讨纱岭金矿床深部成矿潜力,该文在野外地质工作的基础上,选取钻孔岩心样品,采用构造叠加晕研究方法,重点研究Ⅰ-2号主矿体地球化学特征、原生晕分带特征,建立构造叠加晕模型并进行深部找矿预测。研究结果表明:矿床的前缘晕指示元素为As-Sb-Hg,近矿晕指示元素为Au-Ag-Cu-Pb-Zn,尾晕指示元素为Bi-Mo-W-Sn;Ⅰ-2号主矿体构造叠加晕出现"反分带"现象,表明纱岭金矿床具有多期成矿成晕特征;在矿体尾部存在前缘晕与尾晕共存叠加现象,指示深部有良好的找矿前景,预测矿体侧伏方向深部(-1600m之下)有盲矿存在,预测靶位标高为-1600m~-2000m。 相似文献
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Lucas May Petry Camila Leite Da Silva Andrea Esuli Chiara Renso Vania Bogorny 《International journal of geographical information science》2020,34(7):1428-1450
ABSTRACT The increasing popularity of Location-Based Social Networks (LBSNs) and the semantic enrichment of mobility data in several contexts in the last years has led to the generation of large volumes of trajectory data. In contrast to GPS-based trajectories, LBSN and context-aware trajectories are more complex data, having several semantic textual dimensions besides space and time, which may reveal interesting mobility patterns. For instance, people may visit different places or perform different activities depending on the weather conditions. These new semantically rich data, known as multiple-aspect trajectories, pose new challenges in trajectory classification, which is the problem that we address in this paper. Existing methods for trajectory classification cannot deal with the complexity of heterogeneous data dimensions or the sequential aspect that characterizes movement. In this paper we propose MARC, an approach based on attribute embedding and Recurrent Neural Networks (RNNs) for classifying multiple-aspect trajectories, that tackles all trajectory properties: space, time, semantics, and sequence. We highlight that MARC exhibits good performance especially when trajectories are described by several textual/categorical attributes. Experiments performed over four publicly available datasets considering the Trajectory-User Linking (TUL) problem show that MARC outperformed all competitors, with respect to accuracy, precision, recall, and F1-score. 相似文献
8.
Sébastien Gogo Jean-Baptiste Paroissien Fatima Laggoun-Défarge Jean-Marc Antoine Léonard Bernard-Jannin Guillaume Bertrand Philippe Binet Stéphane Binet Guillaume Bouger Yohann Brossard Thierry Camboulive Jean-Pierre Caudal Stéphane Chevrier Geneviève Chiapiuso Benoît D'Angelo Pilar Durantez Chris Flechard André-Jean Francez Didier Galop Laure Gandois Daniel Gilbert Christophe Guimbaud Louis Hinault Adrien Jacotot Franck Le Moing Emilie Lerigoleur Gaël Le Roux Fabien Leroy Alexandre Lhosmot Qian Li Elodie Machado Da Silva Jean-Sébastien Moquet Juanita Mora-Gomez Laurent Perdereau Thomas Rosset Marie-Laure Toussaint 《水文研究》2021,35(6):e14244
Mitigating and adapting to global changes requires a better understanding of the response of the Biosphere to these environmental variations. Human disturbances and their effects act in the long term (decades to centuries) and consequently, a similar time frame is needed to fully understand the hydrological and biogeochemical functioning of a natural system. To this end, the ‘Centre National de la Recherche Scientifique’ (CNRS) promotes and certifies long-term monitoring tools called national observation services or ‘Service National d'Observation’ (SNO) in a large range of hydrological and biogeochemical systems (e.g., cryosphere, catchments, aquifers). The SNO investigating peatlands, the SNO ‘Tourbières’, was certified in 2011 ( https://www.sno-tourbieres.cnrs.fr/ ). Peatlands are mostly found in the high latitudes of the northern hemisphere and French peatlands are located in the southern part of this area. Thus, they are located in environmental conditions that will occur in northern peatlands in coming decades or centuries and can be considered as sentinels. The SNO Tourbières is composed of four peatlands: La Guette (lowland central France), Landemarais (lowland oceanic western France), Frasne (upland continental eastern France) and Bernadouze (upland southern France). Thirty target variables are monitored to study the hydrological and biogeochemical functioning of the sites. They are grouped into four datasets: hydrology, fluvial export of organic matter, greenhouse gas fluxes and meteorology/soil physics. The data from all sites follow a common processing chain from the sensors to the public repository. The raw data are stored on an FTP server. After operator or automatic processing, data are stored in a database, from which a web application extracts the data to make them available ( https://data-snot.cnrs.fr/data-access/ ). Each year at least, an archive of each dataset is stored in Zenodo, with a digital object identifier (DOI) attribution ( https://zenodo.org/communities/sno_tourbieres_data/ ). 相似文献
9.
Dim and small target detection is one of the most challenging issues based on space-based detector. Original space-based detector only uses infrared bands, and the target information is limited in one-band image, so that detection error rate is high. In order to increase the target information, we suppose spectral imaging technology can be applied to the space-based detection system. Use bands of stronger radiation of targets than that of background as detection bands theoretically; the detection bands also can be called as the characteristic bands of targets. On these bases, the paper proposes methods of fuzzy fusion and fusion segmentation to achieve the target detection. Fusion is a combination of images from the characteristic bands, which can eliminate background, restrain noise, and enhance the target. Threshold segmentation and fuzzy algorithm assisted fusion algorithm to complete the final detection. In the simulation experiment, missile plume is considered as the detection target, atmosphere, cloud and jet plume is considered as the detection background, and the advantages of the characteristic spectrum detection and the proposed algorithm are verified from SNR, SCR, ROC curve, and time. 相似文献
10.
庞达 《测绘与空间地理信息》2018,(3):171-174,177
针对沉降监测中用时间序列分析数据样本较少、处理精度不高的问题,本文引入厄米特插值,提出用厄米特插值法对数据进行插值,增加数据样本,然后用时间序列对数据进行建模分析。为了验证用厄米特插值后的数据建模精度,将上述理论运用到工程实例中,用时间序列分析分别对厄米特插值处理后的数据和原始数据进行建模分析,得到用厄米特插值处理后的数据进行时间序列分析建模的平均绝对误差比原始数据建模的平均绝对误差高0.083 8 mm。说明厄米特插值和时间序列组合模型精度比较高。 相似文献