GeoVisuals: a visual analytics approach to leverage the potential of spatial videos and associated geonarratives

ABSTRACT

Videos embedded with spatial coordinates, especially when combined with additional expert insights, offer the potential to acquire fine-scale multi-time period contextualized data for a variety of different environments. However, while these geospatial multimedia (GSMM) data include abundant spatiotemporal, semantic and visual information, the means to fully leverage their potential using a suite of visual and interactive analysis techniques and tools has thus far been lacking. In this paper, we address this gap by first identifying the types of tasks required of GSMM data, and then presenting a solution platform. This GeoVisuals system utilizes a visual analysis approach built on semantic data points that can be integrated spatially, which in turn enables management in a unified database with combined spatio-temporal and text querying. A set of visualization functions are integrated in two investigation modes: geo-video analysis and geo-location analysis.     

A modified monthly degree‐day model for evaluating glacier runoff changes in China. Part I: model development

The retreat of mountain glaciers and ice caps has dominated the rise in global sea level and is likely to remain an import component of eustatic sea‐level rise in the 21st century. Mountain glaciers are critical in supplying freshwater to populations inhabiting the valleys downstream who heavily rely on glacier runoff, such as arid and semi‐arid regions of western China. Owing to recent climate warming and the consequent rapid retreat of many glaciers, it is essential to evaluate the long‐term change in glacier melt water production, especially when considering the glacier area change. This paper describes the structure, principles and parameters of a modified monthly degree‐day model considering glacier area variation. Water balances in different elevation bands are calculated with full consideration of the monthly precipitation gradient and air temperature lapse rate. The degree‐day factors for ice and snow are tuned by comparing simulated variables to observation data for the same period, such as mass balance, equilibrium line altitude and glacier runoff depth. The glacier area–volume scaling factor is calibrated with the observed glacier area change monitored by remote sensing data of seven sub‐basins of the Tarim interior basin. Based on meteorological data, the glacier area, mass balance and runoff are estimated. The model can be used to evaluate the long‐term changes of melt water in all glacierized basins of western China, especially for those with limited observation data. Copyright © 2011 John Wiley & Sons, Ltd.     

One mechanism of production of additional components in emission lines of the spectra of active galaxies

A new mechanism is suggested to explain the physical phenomenon of the appearance of additional new emission components of hydrogen lines in the spectra of active galactic nuclei (AGNs). The mechanism is based on the assumption that a dense clump of hydrogen is ejected from an AGN and expands rapidly due to a presumed explosion. Two main features of this phenomenon are explained fairly simply: a) the pronounced shift of the additional components from the main components (up to several thousand kilometers per second); b) the large width of the additional components, reaching 100–200 Å. The large share of emission by the additional components in comparison with the main lines is also explained well. Estimates obtained for the physical parameters of the new formations in AGNs fit well into modern concepts of AGNs and the forms of their activity.     

Estimating and mapping snow hazard based on at-site analysis and regional approaches

The estimation of snow hazard and load faces the small sample size effect because of the short snow depth record at a station. To reduce such an effect, we propose to estimate the return period value of the annual maximum ground snow depth S, s_T, for Canada sites by applying the regional frequency analysis (RFA) and the region of influence approach (ROIA). The use of RFA and ROIA to map Canadian snow hazard is new. The comparison of their performance for snow hazard mapping has not been explored in the literature. We also consider the at-site analysis approach (ASA) for estimating s_T by using three often used probability distributions for S. A comparison of the estimated s_T by using the three approaches (ASA, RFA, ROIA) indicates that there is considerable scatter between the estimated s_T value although the identified overall spatial trends of s_T are similar. It is shown that the two-parameter lognormal distribution for S at most Canadian sites, based on the at-site analysis, is preferred; this differs from the Gumbel distribution used to develop the design snow load in Canadian structural design code. The new findings indicate that it is valuable to consider the lognormal distribution for developing design snow load for Canadian sites.

     

二连盆地伊和高勒地区下白垩统赛汉组沉积特征

为揭示二连盆地马尼特坳陷伊和高勒地区下白垩统赛汉组沉积特征,文章通过综合分析研究区内露头剖面、钻孔等,较为精细地研究了赛汉组岩性特征、地层空间展布特征、底板埋深分布特征、沉积相类型、沉积相展布特征等。研究区赛汉组分布范围广,具有东厚西薄的格局。底板埋深东部深西部浅,西部发育构造斜坡。西部为砂岩与泥岩,砂岩富炭屑;东部为砂砾岩与泥岩,砂砾岩中含炭屑。发育南、北两个方向物源,北部物源占主导作用。西部发育辫状河三角洲,砂体发育,"泥-砂-泥"结构好,为砂岩型铀矿最有利的沉积相带;东部发育扇三角洲,砂体极为发育,"泥-砂-泥"结构较好,为砂岩型铀矿较为有利的沉积相带;中部为半深湖-滨浅湖,砂体不发育,不利于砂岩型铀成矿。     

河南兰考地区地热回灌影响因素分析及对策

地热回灌是保障地热资源可持续开发利用的关键环节之一。本文结合河南兰考地区热储层地质条件、水质特点、地热井井管材质,开展了室内腐蚀观察实验和PHREEQC地球化学模拟软件分析,从化学沉淀趋势、地热水腐蚀性和钻井成井工艺方面分析了回灌效果的影响因素,并从地热水水质处理、地热井井管材料选择、钻井与成井工艺优化、回灌温度、项目选址等方面提出提高回灌效果的建议。     

Genesis of Re-rich Molybdenite in the Baishan Mo deposit,Eastern Tianshan,Xinjiang, Northwest China

The Baishan molybdenum deposit is located in the central part of the Eastern Tianshan-Beishan tectonic belt, NW China. The deposit is hosted in early Carboniferous Gandun Formation biotite-rich hornfels and is genetically related to unexposed granodiorite porphyry beneath the orebodies. The molybdenite occurs in three different types from early to late stage: Molybdenite - Fe-Cu-sulfides - K-feldspar - quartz veins (Group 1); Molybdenite - Fe-Cu-sulfides - quartz veins (Group 2); and disseminated molybdenite in the wall rock (Group 3). Rhenium concentrations in the molybdenite grains range from 108 to 277 ppm in Group 1, 69–121 ppm in Group 2 and 46–135 ppm in Group 3. The Re concentrations of molybdenite in the Baishan Mo deposit decrease from early to late and from the center to periphery, and molybdenite types vary from the 2H₁ poly-type in Groups 1 and 2 to the 2H₁ + 3R2H₁ poly-type in Group 3, based on X-ray diffraction results. The Re-enriched molybdenite probably formed from an oxidized magmatic fluid that separated from a highly oxidized and H₂O- and volatile-enriched adakitic intrusion generated in the lower crust.     

An attention-constrained neural network with overall cognition for landslide spatial prediction

The occurrence of landslides is affected by various environmental factors. When predicting landslides, conventional neural networks optimize parameters using global connectivity, which limits their efficiency in extracting features of contributing factors. In this study, we developed an attention-constrained neural network with overall cognition (OC-ACNN) to focus on important features from the complex data. The method has four steps: (1) extract the overall cognition as the prior input based on historical landslide distribution and contributing factors, (2) embed an attention mechanism in hidden layers to allocate more weight to noteworthy features, (3) update weights and fit the nonlinear relationship by the back-propagation neural network (BPNN), and (4) generate prediction results using a classifier. This model was applied to the Sichuan-Tibet Highway, considering 10 predisposing factors and 1449 historical landslides. The evaluation results indicate that OC-ACNN (0.822) had a higher predictive capability than multiple linear regression (MLR, 0.734) and BPNN (0.789) in terms of the area under the receiver operating characteristic curve (AUC). Further, we compared different attention patterns and score functions for use with the proposed model. The results show that OC-ACNN offered greater predictive performance than Self-ACNN (without OC, 0.803) and that the improved cosine (0.822) score function had better results and stability than others (0.819 highest).

     

中亚造山带岩浆铜镍硫化物矿床深部找矿：以红旗岭铜镍矿床为例

为了对中亚造山成矿带东段南缘红旗岭岩浆型铜镍硫化物矿床深部（500～1 000 m）隐伏矿体进行成矿预测,采用高精度重力和2.5维人机交互式反演方法,对含矿性较好的镁铁质—超镁铁质岩体（如#1、#3及新#3岩体）进行底部含矿性研究。结果表明：高精度重力异常开展不同高度上延并结合垂向一阶导数等数据处理,可有效地厘定深部隐伏岩体空间展布;2.5维人机交互式反演方法可以识别深部微弱的矿致异常,推测研究区#3岩体埋深700～1 100 m存在5个脉状盲矿体。经钻探验证,成功发现32 259 t]镍矿（矿石平均品位达0.36%）,其中②号矿体为最厚矿体,见矿深度为700～1 100 m,镍矿平均品位为0.39%,储量达27 433 t。