安徽省东至地区金矿类型及找矿方向

安徽省东至地区位于扬子陆块北缘,跨下扬子前陆带和江南隆起带两个次级构造单元,独特的大地构造环境造就了本区有利的金矿成矿地质条件,形成多种类型的金矿床,其成因类型主要包括岩浆热液型和风化壳型,工业类型主要有破碎带蚀变岩型、含金石英脉型、微细粒浸染型及红土型。各类型金矿分类聚集,形成两个主要的金矿成矿带。沿赵家岭断层带以破碎带蚀变岩型为主,伴有含金石英脉型,中畈—戴家一带,赵家岭—杨家山一带均具较大找矿潜力,是本区金矿勘查重点地区,九华庄等地也具一定的找矿潜力;沿高坦断裂以微细粒浸染型为主,伴有破碎带蚀变岩型及红土型,查册桥地区是其重点勘查区,铜锣尖、小河等地找矿潜力也较大。     

Heavy Metal Pollution in Sediments from Aquatic Ecosystems in China

We conducted an analysis of heavy metals content, including As, Cd, Cr, Cu, Hg, Pb, and Zn in sediments from aquatic ecosystems in China measured in recent publications. Then, we evaluated the extent of heavy metal pollution in these ecosystems in seven different industrial districts in China (Dongbei, Huabei, Huazhong, Huanan, Huaxik, Xibei, and Huadong) with the potential ecological risk index. We found that Cd was the most concentrated pollutant, followed by Hg and As, while Cr, Cu, Pb, Zn were found in low concentrations in sediments from all types of aquatic ecosystem in China. Sediments collected from all seven industrial districts were heavily polluted, and the sequence, from most to least polluted was Dongbei>Huabei>Huazhong>Huanan>Huaxi>Xibei>Huadong. All four types of aquatic ecosystem were found to be seriously polluted and the sequence, from most to least polluted was: river>sea>lake>wetland. Specifically, Cd and Hg were the most serious pollutants in all four aquatic ecosystems, and As was also a serious pollutant in rivers. For the seven industrial districts studied the sea was the most polluted ecosystem in Dongbei, the river was the most polluted ecosystem in Huabei, Huanan, Huazhong, and the lake was the most polluted in Huadong, Huaxi, and Xibei.     

基于语义类型本体的地名组配查询

地名查询方式多种多样,但它们都没有考虑地名语义类型因素,而语义类型恰恰是地名信息中相当重要的一部分。以地名语义分类为基础,构建了地名语义类型本体模型,并以郑州市为例进行了地名组配查询实验。结果表明,该方式对于检索地名的相关信息具有较好的辅助作用,为地名查询与检索作了有益的补充。     

基于MSAVI-WI特征空间的新疆渭干河-库车河流域绿洲土壤盐渍化研究

土壤盐渍化是造成干旱区土地荒漠化及生态恶化的重要原因,及时获取大尺度高精度土壤盐渍信息是防治工作的基础。选取新疆塔里木盆地北缘渭干河—库车河流域三角洲绿洲为研究区,利用Lansat-TM数据与野外实测数据分析盐渍化土壤与修改型土壤调整植被指数(MSAVI)、湿度指数(WI)之间的关系,在此基础上提出了MSAVI-WI特征空间概念,构建了土壤盐渍化遥感监测指数模型(MWI)。结果表明:MWI与土壤表层含盐量相关性较高,其相关性为0.844,精度高于土壤盐渍监测常用的盐分指数与实测数据的相关性。MWI能较好的反映盐渍化土壤地表植被及土壤水分的组合变化,具有明确的生物物理意义,并且特征参量简单,理论上易于理解,实践上易于实现,MWI模型的构建有利于干旱区大尺度土壤盐渍化定量监测与评价工作的开展。     

Stochastic gradient boosting classification trees for forest fuel types mapping through airborne laser scanning and IRS LISS-III imagery

This paper presents an application of Airborne Laser Scanning (ALS) data in conjunction with an IRS LISS-III image for mapping forest fuel types. For two study areas of 165 km² and 487 km² in Sicily (Italy), 16,761 plots of size 30-m × 30-m were distributed using a tessellation-based stratified sampling scheme. ALS metrics and spectral signatures from IRS extracted for each plot were used as predictors to classify forest fuel types observed and identified by photointerpretation and fieldwork. Following use of traditional parametric methods that produced unsatisfactory results, three non-parametric classification approaches were tested: (i) classification and regression tree (CART), (ii) the CART bagging method called Random Forests, and (iii) the CART bagging/boosting stochastic gradient boosting (SGB) approach. This contribution summarizes previous experiences using ALS data for estimating forest variables useful for fire management in general and for fuel type mapping, in particular. It summarizes characteristics of classification and regression trees, presents the pre-processing operation, the classification algorithms, and the achieved results. The results demonstrated superiority of the SGB method with overall accuracy of 84%. The most relevant ALS metric was canopy cover, defined as the percent of non-ground returns. Other relevant metrics included the spectral information from IRS and several other ALS metrics such as percentiles of the height distribution, the mean height of all returns, and the number of returns.     

A Machine Learning-based Cloud Detection Algorithm for the Himawari-8 Spectral Image

Cloud Masking is one of the most essential products for satellite remote sensing and downstream applications. This study develops machine learning-based (ML-based) cloud detection algorithms using spectral observations for the Advanced Himawari Imager (AHI) onboard the Himawari-8 geostationary satellite. Collocated active observations from Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) are used to provide reference labels for model development and validation. We introduce both daytime and nighttime algorithms that differ according to whether solar band observations are included, and the artificial neural network (ANN) and random forest (RF) techniques are adopted for comparison. To eliminate the influences of surface conditions on cloud detection, we introduce three models with different treatments of the surface. Instead of developing independent ML-based algorithms, we add surface variables in a binary way that enhances the ML-based algorithm accuracy by ~5%. Validated against CALIOP observations, we find that our daytime RF-based algorithm outperforms the AHI operational algorithm by improving the accuracy of cloudy pixel detection by ~5%, while at the same time, reducing misjudgment by ~3%. The nighttime model with only infrared observations is also slightly better than the AHI operational product but may tend to overestimate cloudy pixels. Overall, our ML-based algorithms can serve as a reliable method to provide cloud mask results for both daytime and nighttime AHI observations. We furthermore suggest treating the surface with a set of independent variables for future ML-based algorithm development.     

云南景谷登海山铜矿地质特征与成因探讨

云南景谷登海山铜矿5个含矿层呈层状贮存于"滇中红层"第三系始新统等黑组紫红色砂岩所夹白色砂岩中,矿石具层纹状原始沉积特征,无明显热液改造痕迹,矿体明显受层位控制,成矿物质主要来源于元谋古陆。结合区域成矿地质背景、矿床地质特征及控矿条件,认为景谷登海山铜矿为砂岩型铜矿床。     

新的构造控矿类型——螺旋构造控矿

概括天宝山新兴角砾岩筒铅锌矿,山东七宝火山岩型金矿,安徽铜陵凤凰山铜矿,辽宁簸箕山磷矿,辽宁清源红透山铜(锌)矿等构造控矿实例的解读,表明它们可建立一种新的构造控矿类型——螺旋构造控矿。受幔团螺旋运动上冲的地幔热柱多级浸演化的幔枝构造制约。     

浅析吉林省浑江煤田构造控煤及构造样式

构造作用是控制煤矿床形成、演化和现今赋存状况的首要地质因素。煤田构造以研究煤盆地和煤层构造的几何形态、组合型式、分布规律、成因机制和发展演化进程为主要内容,以此服务于煤炭资源勘查和开发。     

综合地质-地球物理方法在金矿中的应用

河北省丰宁县坝州营金矿床赋存于五台期侵位的“变闪长岩”中,该区从太古代到中生代长期处于构造隆升剥蚀状态,发育多期岩浆侵位事件,为金矿提供了充分的成矿条件。根据区域地质背景及围岩蚀变、矿化等特征,推断本矿床属于受构造控制的中一低温热液石英脉型金矿。结合矿区地质特征开展地球物理工作,以高密度电法圈定了地下矿化体的范围,辅以音频大地电磁测量,实现探测相对深部断裂构造,并以钻探证实,取得了找矿突破,达到了推断控矿构造的走向和找矿前景等目的。