中-哈-吉-乌天山变形带容矿金矿床:成矿环境和控矿要素与找矿标志

天山是全球第二大金矿富集区,世界级和大型-超大型金矿床东西成带横贯中国新疆中部—哈萨克斯坦东南部—吉尔吉斯斯坦—乌兹别克斯坦,构成巨型跨境金成矿带。天山巨型跨境金成矿带和重要金矿床形成的地质环境、成矿的控制要素、找矿勘查的标志都是学术界和工业界高度关注的重大地质和找矿问题。通过广泛、深入地文献调研和境内外天山较全面野外地质矿产调查与研究,本文认为中-哈-吉-乌天山大规模金成矿主体形成于晚石炭世—早二叠世古亚洲洋闭合后的陆块拼贴变形过程,部分形成于中—晚二叠世陆内走滑变形过程。中天山南、北缘古缝合带及其附近的大型脆性/韧-脆性变形带是巨量金成矿的关键控制因素,多期叠加复合成矿是天山变形带容矿金矿床的显著特征。地壳初始富集、构造变形活化、岩浆热液叠加是天山变形带容矿金矿床的主控因素。“碳质细碎屑岩+脆韧性变形带+海西末期岩体”是中-哈-吉-乌天山变形带容矿大型-超大型金矿的找矿标志组合。     

An integrated object-based image analysis and CA-Markov model approach for modeling land use/land cover trends in the Sarab plain

The present paper is an attempt to integrate a semi-automated object-based image analysis (OBIA) classification framework and a cellular automata-Markov model to study land use/land cover (LULC) changes. Land use maps for the Sarab plain in Iran for the years 2000, 2006, and 2014 were created from Landsat satellite data, by applying an OBIA classification using the normalized difference vegetation index, salinity index, moisture stress index, soil-adjusted vegetation index, and elevation and slope indicators. The classifications yielded overall accuracies of 91, 93, and 94% for 2000, 2006, and 2014, respectively. Finally, using the transition matrix, the spatial distribution of land use was simulated for 2020. The results of the study revealed that the number of orchards with irrigated agriculture and dry-farm agriculture in the Sarab plain is increasing, while the amount of bare land is decreasing. The results of this research are of great importance for regional authorities and decision makers in strategic land use planning.     

Forest fire susceptibility modeling using hybrid approaches

Forest fires are considered one of the most highly damaging and devastating of natural disasters, causing considerable casualties and financial losses every year. Hence, it is important to produce susceptibility maps for the management of forest fires so as to reduce their harmful effects. The purpose of this study is to map the susceptibility to forest fires over Nowshahr County in Iran, using an integrated approach of index of entropy (IOE) with fuzzy membership value (FMV), frequency ratio (FR), and information value (IV) with a comparison of their precision. The spatial database incorporated the inventory of forest fire and conditioning factors. As a whole, 41 forest fire locations were identified. Out of these, 29 locations (≈70%) were randomly chosen for the forest fire susceptibility modeling (FFSM), and the remaining 12 locations (≈30%) were utilized for the validation of the models. Subsequently, utilizing FMV‐IOE, FR‐IOE, and IV‐IOE models, forest fire susceptibility maps were acquired. Finally, the modeling ability of the models for FFSM was assessed using an area under the receiver operating characteristic (AUROC) curve. The results manifested that the prediction accuracy of the FMV‐IOE model is slightly higher than that of the FR‐IOE and IV‐IOE models. The incorporation of IOE with FMV, FR, and IV models had AUROC values of 0.890, 0.887, and 0.878, respectively. The resulting FFSM can be effective in fire repression resource planning, sustainable development, and primary warning in regions with similar conditions.     

西天山金铜多金属重要成矿类型、成矿环境及找矿潜力

西天山跨乌兹别克斯坦、塔吉克斯坦、吉尔吉斯斯坦、哈萨克斯坦南部和中国新疆西天山,东西绵延2500 km,是"亚洲金腰带"核心地带,金铜铅锌矿产优势明显,中国新疆西天山金铜铅锌重大找矿发现令人期待。通过广泛深入的文献调研和较全面的地质矿产调查,论文针对重要成矿类型、成矿环境和找矿潜力的研究表明,西天山金铜铅锌成矿重要类型是造山型金矿、斑岩型金铜矿、SEDEX型和砂岩型铅锌矿等。造山型金矿形成于古生代俯冲增生和碰撞造山两类地质环境,斑岩型金铜矿形成于古生代不同时期的成熟岛弧环境,SEDEX型铅锌矿在新元古代陆缘盆地富集,砂岩型铅锌矿形成于中—新生代山前盆地。西天山金铜铅锌成矿类型和环境优越,找矿潜力巨大,新疆西天山有望实现金铜铅锌找矿持续重大突破。本文为西天山区域成矿研究和金铜铅锌找矿勘查提供了新的参考和引导。     

An uncertainty and sensitivity analysis approach for GIS-based multicriteria landslide susceptibility mapping

GIS-based multicriteria decision analysis (MCDA) methods are increasingly being used in landslide susceptibility mapping. However, the uncertainties that are associated with MCDA techniques may significantly impact the results. This may sometimes lead to inaccurate outcomes and undesirable consequences. This article introduces a new GIS-based MCDA approach. We illustrate the consequences of applying different MCDA methods within a decision-making process through uncertainty analysis. Three GIS-MCDA methods in conjunction with Monte Carlo simulation (MCS) and Dempster–Shafer theory are analyzed for landslide susceptibility mapping (LSM) in the Urmia lake basin in Iran, which is highly susceptible to landslide hazards. The methodology comprises three stages. First, the LSM criteria are ranked and a sensitivity analysis is implemented to simulate error propagation based on the MCS. The resulting weights are expressed through probability density functions. Accordingly, within the second stage, three MCDA methods, namely analytical hierarchy process (AHP), weighted linear combination (WLC) and ordered weighted average (OWA), are used to produce the landslide susceptibility maps. In the third stage, accuracy assessments are carried out and the uncertainties of the different results are measured. We compare the accuracies of the three MCDA methods based on (1) the Dempster–Shafer theory and (2) a validation of the results using an inventory of known landslides and their respective coverage based on object-based image analysis of IRS-ID satellite images. The results of this study reveal that through the integration of GIS and MCDA models, it is possible to identify strategies for choosing an appropriate method for LSM. Furthermore, our findings indicate that the integration of MCDA and MCS can significantly improve the accuracy of the results. In LSM, the AHP method performed best, while the OWA reveals better performance in the reliability assessment. The WLC operation yielded poor results.     

Comparing GIS-based support vector machine kernel functions for landslide susceptibility mapping

This study compares the predictive performance of GIS-based landslide susceptibility mapping (LSM) using four different kernel functions in support vector machines (SVMs). Nine possible causal criteria were considered based on earlier similar studies for an area in the eastern part of the Khuzestan province of southern Iran. Different models and the resulting landslide susceptibility maps were created using information on known landslide events from a landslide inventory dataset. The models were trained using landslide inventory dataset. A two-step accuracy assessment was implemented to validate the results and to compare the capability of each function. The radial basis function was identified as the most efficient kernel function for LSM with the resulting landslide susceptibility map showing the highest predictive accuracy, followed by the polynomial kernel function. According to the obtained results, it concluded that using SVMs can generally be considered to be an effective method for LSM while it demands careful consideration of kernel function. The results of the present research will also assist other researchers to select the best SVM kernel function to use for LSM.     

中国及境外天山铅锌成矿作用与找矿方向

中国及境外天山铅锌矿床多有发现,如哈萨克斯坦Tekeli、Shalkiya和Achisai,乌兹别克斯坦Kurgashinkan和Uchkulach,塔吉克斯坦Altyntopkan,中国新疆乌拉根、彩霞山、阿齐山、阿尔恰勒等大型—超大型铅锌矿床,构成了天山巨型铅锌成矿带.这些铅锌矿床形成于怎样的地球动力学背景?铅锌成...     

An interval matrix method used to optimize the decision matrix in AHP technique for land subsidence susceptibility mapping

The analytical hierarchy process (AHP) is one of the most effective methods for criteria ranking/weighting to have been successfully incorporated into GIS analyses. We present a new method for optimizing pairwise comparison decision-making matrices in AHP method, which has been developed on the basis of an interval pairwise comparison matrix (IPCM) derived from expert knowledge. The method has been used for criteria ranking in land subsidence susceptibility mapping (LSSM) as a practical test case, for which an interval matrix was generated by pairwise comparison. To compare the capability of the AHP method (a traditional approach) with that of the proposed IPCM method (a novel approach), 11 creations of LSSM were ranked using each approach in turn. The criteria weightings obtained were then used to produce LSSM maps based on each of these approaches. The results were tested against a data set of known land subsidence occurrences, indicating an improvement in accuracy of about 14% in the LSSM map that was developed using the IPCM method. This improvement was achieved by minimizing the uncertainty associated with criteria ranking/weighting in a traditional AHP and could form a basis for future research into minimizing the uncertainty in weightings derived using the AHP method. Our results will be of considerable importance for researchers involved in GIS-based multi-criteria decision analysis (MCDA) and those dealing with GIS-based spatial decision-making methods.     

Thermoluminescence and the shock and reheating history of meteorites—II: Annealing studies of the Kernouve meteorite

Samples of the unshocked, equilibrated chondrite, Kernouve (H6), have been annealed for 1–100 hours at 500–1200°C, their thermoluminescence sensitivity measured and Na, K, Mn, Ca and Sc determined by instrumental neutron activation analysis. The TL sensitivity decreased with temperature until by 1000°C it had fallen by 40%. The process responsible has an activation energy of ~8 kcal/mole and probably involves diffusion. Samples annealed 1000–1200°C had TL sensitivities 10^?2 times the unannealed values, most of the decrease occurring ~1100°C. This process has an activation energy of ~100 kcal/mole and is probably related to the melting of the TL phosphor, feldspar, with some decomposition and loss of Cs, Na and K. Meteorites whose petrography indicates healing > 1100°C by natural shock heating events (shock facies d-f). have TL sensitivities similar to samples annealed > 1100°C. Our own and literature compositional data indicate that TL is more stable to annealing than Ag, In, Tl, Bi, Zn and Te and less stable than Na, K, Mn, Ca, Se and Co, while the TL decrease resembles very closely the pattern of Cs loss on annealing.     

Study of subsurface structures using seismic reflection data for Kalar–Khanaqin area/Kurdistan region,Iraq

The study is carried out to detect the subsurface structures that have geological and economic importance by interpreting the available seismic reflection data of an area estimated to be about 1,752 km². The study comprises of the Kalar–Khanaqin and surrounding area, which is located at Zagros folded zone. Twenty-five seismic sections had been interpreted. The total length of all the seismic lines is about 650.4 km. Interpretation of the seismic data is focused on two reflectors, lower Fars and Jeribe formation. The lower Fars reflector picked at the two-way time ranging from 0.1 to 2.6 second, while the Jeribe reflector picked at the two-way time ranging from 1.0 to 2.7 second. The constructed maps denote to the existence of many closed and nose structures, in addition, to numerous fault types. All these features were detected in the area having the NW–SE trend. The depth of the lower Fars formation is ranging from 100.0 to 4,800.0 m, while the depth of the Jeribe formation is ranging from 1,700.0 to 5,000.0 m. The depth maps for the two formations also refer to the similarity of the major geological structures. These structures appear in both formations with existence of slight variation in dimensions. The closed structure no. (1) is located at the north of the study area. The nose structure no. (2) is located at the south of the area. At the west of the area, the elongated structure no. (3). The longitudinal reveres fault intersects the SW limb of the structure. The SW limb of elongated structure no. (4), intersect by longitudinal reveres fault, is located at the east of the area. There is also the semi-closed structure no. (5), which appears at the west of the area around the Qr-1 well. Most of detected faults are of reverse and thrust types having a variable amount of throws and horizontal displacements. Some seismic sections explained the existence of the decollement surface within lower Fars formation, which caused the thrusting and faulting of the overlaying beds.