遥感技术在内蒙古东乌珠穆沁旗萨麦地区的找矿应用

本文以内蒙古东乌珠穆沁旗萨麦地区1:5万巴彦塔拉等4幅区域地质调查范围为研究区,以ETM+影像数据为信息源,以波谱理论为基础,从遥感图像中提取蚀变信息继而进行遥感找矿实践。针对区内铁染、羟基蚀变类型使用主成分分析等方法,将研究区划分为10个异常区,结合区域构造特征情况,对异常区域开展了1:1万路线调查,综合判定后,选择了4个找矿靶区进行了化探剖面探测并进行了成果分析,结果显示遥感蚀变信息与野外调查和化探异常吻合较好。     

Integration of GIS and video surveillance

This paper discusses the integration of three-dimensional (3D) geographic information systems (GIS) and video surveillance systems using augmented reality (AR) techniques. The motivation for this integration is to overcome problems faced by conventional video surveillance systems. Explicit information concerning which camera currently monitors what area in such systems is missing; therefore, insight into the situation depends heavily on the operator’s training and experience. To ensure the complete coordination and monitoring of a situation in a system with multiple cameras, it is necessary to introduce a single reference system. GIS arises as a natural solution because it not only provides a solid ground truth but also provides semantic information that can be highly important in certain video surveillance applications. To integrate information into a GIS application, that information must be georeferenced. Based on our previous research regarding the addition of georeferencing information to surveillance video, this paper introduces models that can be applied to help integrate video and GIS. With an analogy to Milgram’s continuum between the real world and virtual reality, and analogous to the augmented reality and augmented virtuality in Milgram’s continuum, two models of integration are defined here: GIS-augmented video and video-augmented GIS. Then, we define the architecture of GIS-based video surveillance based on these proposed integration models, and finally, a prototype is implemented. The implemented prototype serves as a basis for analysing possible applications of real-world systems based on the integration of GIS and video.     

Overcoming Trade Impediments: Considering SME Exporters from Nova Scotia

Firms often encounter location-based impediments that hinder them from engaging with international markets. These challenges can be exacerbated for smaller firms, which often have limited resources and exposure to global markets. This article examines successful small and medium-sized exporters from Nova Scotia, a province with decreased export activity in recent years. It explores these firms’ trade-related motivations, their impediments, and the strategies that they have used to address possible location-related problems. Although geographical distance does not appear to be a competitive challenge, other issues emerge, including travel expenditures and the costs of export intelligence gathering. Successful exporters have overcome many potential impediments by using government trade programs, establishing and maintaining face-to-face contacts, and working with international partners.     

Porphyry Copper Deposit Prognosis in the Middle Region of the Bangonghu–Nujiang Metallogenic Belt,Tibet, Using ASTER Remote Sensing Data

The B angonghu–N ujiang metallogenic belt is considered to be T ibet’s third copper belt after the Y ulong and G angdese copper belts. The D uolong gold‐rich porphyry copper deposit, located in the western part of the B angonghu–N ujiang belt was recently recognized as a superlarge prospect. The A dvanced S paceborne T hermal E mission and R eflection R adiometer (ASTER ) was used to characterize the D uolong porphyry deposit alteration area, and three methods, color enhancement, band ratio transformation, and spectral angle mapping, were utilized to extract the phyllic and argillic alteration zones, which are typically considered the most important predictors of porphyry copper. Seven prospecting areas, which match mapped alteration zones, were delineated in the D uolong deposit. In addition, an ASTER image of the eastern region of the B angonghu–N ujiang belt in the X iongmei area was used to extract alteration information, and an area with image characteristics similar to the D uobuza and B olong ore deposits was identified as a prospecting area. Numerous malachite outcrops were identified in the field, and both laboratory analysis and isotopic dating confirmed that the deposit had formed concurrently with the D uobuza deposit (119 M a). Geologic mapping at the 1:5000 scale was conducted in the area, and three types of ore‐bearing rocks were identified, indicating that this area has significant potential to host ore deposits. The discovery of the X iongmei copper mining area is significant for the B angonghu–N ujiang belt.     

庐枞矿集区中东部七家山—马口地区深部找矿潜力分析

为调查庐枞矿集区中东部七家山—马口地区深部矿产资源潜力,利用小波变换方法提取深源重磁场,通过对垂向一阶导数Z与水平方向导数模S进行参数变换,突出深源重磁场的局部异常; 结合频谱激电(spectrum induced polarization,SIP)、可控源音频大地电磁测深(controlled source audio-frequency magneto tellurics,CSAMT)成果,在调查区深部查明了一条长大于3.0 km、宽大于0.5 km的高重低磁、低阻高极化异常带; 根据调查区内外已知铜矿(化)体分布规律,结合已知矿(化)体在深源重磁异常中的分布及钻孔(zk4601)钻探验证结果,认为上述异常带是铜多金属矿化蚀变带的反映,是寻找铜多金属矿的有利部位,具有较好的找矿前景。     

Progress in the Application of Ground Gravity Observation Data in Earthquake Prediction

The mechanism of earthquake inoculation and the process of earthquake occurrence are very complicated. Additionally, earthquakes do not happen very often, and we lack enough cognition to the earth’s interior structure, activity regularity and other key elements. As a result, research progress about the theory of earthquake precursors has been greatly restricted. Ground gravity observation has become one of the main ways to study earthquake precursor information in many countries and regions. This paper briefly summarized the surface gravity observation technology and observation network in China: the surface gravity measurement instrument developed from Huygens physical pendulum in seventeenth Century to today’s high-precision absolute gravimeter, and its accuracy reached to ±1×10^-8 m/s². China has successively established the National Gravity Network, Digital Earthquake Observation Network of China,the Crustal Movement Observation Network of China Ⅰ and the Crustal Movement Observation Network of China, to provide a public platform for monitoring non tidal gravity change, seismic gravity and tectonic movement. The use of specific examples illustrated the role of gravity observation data in earthquake prediction. The gravity observation data of ground gravity can be used to capture the information of gravity change in the process of strong earthquake inoculation, and to provide an important basis for the long-term prediction of strong earthquakes. The temporal and spatial variation characteristics of the regional gravity field and its relation to strong earthquakes were analyzed: Before the earthquake whose magnitude is higher than M_S 5, generally there will be a large amplitude and range of gravity anomaly zones. Strong earthquakes occur mainly in areas where the gravity field changes violently. The dynamic change images of gravity field can clearly reflect the precursory information of large earthquakes during the inoculation and occurrence. Finally, the existing problems of surface gravity technology in earthquake precursor observation were put forward and the use of gravity measurement data in earthquake prediction research was prospected.     

Revisiting the death of geography in the era of Big Data: the friction of distance in cyberspace and real space

Many scholars have argued that the importance of geographic proximity in human interactions has been diminished by the use of the Internet, while others disagree with this argument. Studies have noted the distance decay effect in both cyberspace and real space, showing that interactions occur with an inverse relationship between the number of interactions and the distance between the locations of the interactors. However, these studies rarely provide strong evidence to show the influence of distance on interactions in cyberspace, nor do they quantify the differences in the amount of friction of distance between cyberspace and real space. To fill this gap, this study used massive amounts of social media data (Twitter) to compare the influence of distance decay on human interactions between cyberspace and real space in a quantitative manner. To estimate the distance decay effect in both cyberspace and real space, the distance decay function of interactions in each space was modeled. Estimating the distance decay in cyberspace in this study can help predict the degree of information flow across space through social media. Measuring how far ideas can be diffused through social media is useful for users of location-based services, policy advocates, public health officials, and political campaigners.     

GIS professional development for teachers: lessons learned from high-needs schools

University faculty partners from the Departments of Geography and Instruction and Teacher Education at a large, public university collaborated with K-12 teachers and the leadership of a rural school district in order to investigate the crosscutting content of science, mathematics, and geography through the integration of web-based GIS technologies. The project explored the critical connections among technology, pedagogy, and content with a particular emphasis on developing technology-enhanced, inquiry-based lessons in which the teachers and their students used GIS technologies to analyze, visualize, and present data in real-world contexts. The findings highlight the importance of well-structured professional development that builds community, integrates diverse content and pedagogical expertise, provides feedback and coaching, and is of sufficient duration to effect change.     

广东省仁化县书楼丘铀矿床三维地质建模及成矿预测

综合地质、地球化学等资料进行多元信息成矿预测是目前深部固体矿产主要工作方法。广东仁化县书楼丘铀矿床位于诸广南铀矿田北部,是诸广南铀矿田重要的组成之一。本次为了拓宽书楼丘矿床深部找矿思路,探讨其找矿潜力,在前人研究和勘探基础上,总结了矿床综合信息找矿模型,以三维定量预测研究理论基础,根据矿床成矿条件和找矿标志特征,提取地质、化探、钻探资料的成矿有利信息,并利用COCAD软件构建了地形-地表、岩体、构造、矿体等地质模型,对信息进行综合成矿有利分析,运用信息量法进行研究区深部矿产资源预测,共圈定了3片靶区。     

Spatial landslide susceptibility assessment using machine learning techniques assisted by additional data created with generative adversarial networks

In recent years,landslide susceptibility mapping has substantially improved with advances in machine learning.However,there are still challenges remain in landslide mapping due to the availability of limited inventory data.In this paper,a novel method that improves the performance of machine learning techniques is presented.The proposed method creates synthetic inventory data using Generative Adversarial Networks(GANs)for improving the prediction of landslides.In this research,landslide inventory data of 156 landslide locations were identified in Cameron Highlands,Malaysia,taken from previous projects the authors worked on.Elevation,slope,aspect,plan curvature,profile curvature,total curvature,lithology,land use and land cover(LULC),distance to the road,distance to the river,stream power index(SPI),sediment transport index(STI),terrain roughness index(TRI),topographic wetness index(TWI)and vegetation density are geo-environmental factors considered in this study based on suggestions from previous works on Cameron Highlands.To show the capability of GANs in improving landslide prediction models,this study tests the proposed GAN model with benchmark models namely Artificial Neural Network(ANN),Support Vector Machine(SVM),Decision Trees(DT),Random Forest(RF)and Bagging ensemble models with ANN and SVM models.These models were validated using the area under the receiver operating characteristic curve(AUROC).The DT,RF,SVM,ANN and Bagging ensemble could achieve the AUROC values of(0.90,0.94,0.86,0.69 and 0.82)for the training;and the AUROC of(0.76,0.81,0.85,0.72 and 0.75)for the test,subsequently.When using additional samples,the same models achieved the AUROC values of(0.92,0.94,0.88,0.75 and 0.84)for the training and(0.78,0.82,0.82,0.78 and 0.80)for the test,respectively.Using the additional samples improved the test accuracy of all the models except SVM.As a result,in data-scarce environments,this research showed that utilizing GANs to generate supplementary samples is promising because it can improve the predictive capability of common landslide prediction models.