晨昏起伏电场对中性片离子的随机加热

本文从哈密顿原理出发,讨论磁尾中性片中粒子受晨昏起伏电场的影响问题,并把它归结于讨论标准映射的性质.中性片本身是非线性系统,外加起伏场会导致其进入混沌状态.本文计算了进入该状态的临界电场E_c以及不同E下的粒子轨迹.计算表明,观测到的晨昏电场可以使离子进入混沌状态,但远小于电子的临界场值.这样离子运动是随机的,电子运动是规则的.仅对离子的随机加热可能是导致中性片中离子温度高于电子温度的原因.     

大数据环境下数字填图数据集成服务技术

应用数字填图技术形成了大量地质填图图幅数据,这些数据空间结构化和非结构化特征并存,如何在网络环境下提供高效的数据服务是急需解决的一个难题。大数据技术的发展为数字填图、数据集成服务提供了一种新的途径。通过对数字填图数据特征的分析,在研究地质调查信息网格大数据处理框架的基础上,提出了结构化和非结构化数据相结合的有序化组织管理、发布与服务方法,并对关键技术进行了研究与试验,取得了良好的效果。     

Spatial-temporal patterns of China’s interprovincial migration, 1985-2010

Migration plays an increasing role in China's economy since mobility rose and economic restructuring has proceeded during the last three decades. Given the background of most studies focusing on migration in a particular period, there is a critical need to analyze the spatial-temporal patterns of migration. Using bicomponent trend mapping technique and interprovincial migration data during the periods 1985-1990, 1990-1995, 1995-2000, 2000-2005, and 2005-2010 we analyze net-, in-, out-migration intensity, and their changes over time in this study. Strong spatial variations in migration intensity were found in China's interprovincial migration, and substantial increase in migration intensity was also detected in eastern China during 1985-2010. Eight key destinations are mostly located within the three rapidly growing economic zones of eastern China (Pearl River Delta, Yangtze River Delta and Beijing-Tianjin-Hebei Metropolitan Region), and they are classified into three types: mature, emerging, and fluctuant origins, while most key origins are relatively undeveloped central and western provinces, which are exactly in accordance with China's economic development patterns. The results of bicomponent trend mapping indicate that, in a sense, the migration in the south was more active than the north over the last three decades. The result shows the new changing features of spatial-temporal patterns of China's interprovincial migration that Fan and Chen did not find out in their research. A series of social-economic changes including rural transformation, balanced regional development, and labor market changes should be paid more attention to explore China's future interprovincial migration.     

北京山区荒溪分类与危险区制图

根据中奥（奥地利）两国政府１９９２－１９９４年科技合作协议，开展了《北京山区荒溪分类与危险区制图技术研究》．介绍了该研究的目的、方法与成果，根据实践的经验，提出了进一步开展荒溪危险区制图的有关建议．     

Land-surface segmentation as a method to create strata for spatial sampling and its potential for digital soil mapping

Sampling efforts are constrained by limited availability of resources. Therefore, methods to reduce the number of samples, while still achieving reasonable accuracy are needed. Land-surface segmentation (LSS) has proven a powerful technique to partition digital elevation models (DEMs) and their derivatives into relatively homogeneous areas, which can be further employed as support in soil sampling. Though topography is one of the main soil forming factors, a robust assessment of the potential of this technique to digital soil mapping (DSM) is still missing. In this study, we aimed at evaluating the potential of LSS in stratifying a landscape into relatively homogeneous areas, which can be used as strata for guiding the selection of sampling points in DSM. The experiments were carried out in two study areas where soil samples were available. Land-surface derivatives were derived from DEMs and segmented with a tool based on the multiresolution segmentation algorithm, into objects considered as homogeneous soil-landscape divisions. Thus, one sample was randomly selected within each segment from the existing sample data, based on which predictions of soil classes/sub-orders and properties, i.e. soil texture and A-horizon thickness, were made. Results were compared with predictions based on simple random sampling (SRS) and conditioned Latin hypercube (cLHS). The segmentation-based sampling (SBS) scheme performed better than SRS and cLHS schemes in predicting the A-horizon thickness, soil texture fractions and soil classes, showing a high potential of LSS in stratifying a landscape for the purposes of DSM. The novelty of this study is in the way strata are constructed, rather than in the sampling design itself. Further research is needed to demonstrate the value of a SBS design for practical use. The analyses presented here further highlight the importance of considering locally adaptive techniques in optimization of sampling schemes and predictions of soil properties.     

Mineral-Potential Mapping for MVT Deposits with Limited Data Sets Using Landsat Data and Geological Evidence in the Borden Basin, Northern Baffin Island, Nunavut, Canada

Posterior probabilities of occurrence for Zn-Pb Mississippi Valley Type (MVT) mineralization were calculated based on evidence maps derived from regional geology, Landsat-TM, RADARSAT-1, a digital elevation model and aeromagnetic data sets in the Borden Basin of northern Baffin Island, Canada. The vector representation of geological contacts and fault traces were refined according to their characteristics identified in Landsat-TM, RADARSAT-1, DEM, slope, aspect, and shaded relief data layers. Within the study area, there is an association between the occurrence of MVT mineralization and proximity to the contact of platformal carbonates and shale units of the adjacent geological formation. A spatial association also tends to exist between mineralization and proximity to E-W and NW-SE trending faults. The relationships of known MVT occurrences with the geological features were investigated by spatial statistical techniques to generate evidence maps. Supervised classification and filtering were applied to Landsat-TM data to divide the Society Cliffs Formation into major stratigraphic subunits. Because iron oxides have been observed at some of the MVT occurrences within the Borden Basin, Landsat-TM data band ratio (3/1) was calculated to highlight the potential presence of iron-oxides as another evidence map. Processed Landsat-TM data and other derived geological evidence maps provided useful indicators for identifying areas of potential MVT mineralization. Weights of evidence and logistic regression were used independently to integrate and generate posterior probability maps showing areas of potential mineralization based on all derived evidence maps. Results indicate that in spite of the lack of important data sets such as stream or lake sediment geochemistry, Landsat-TM data and regional geological data can be useful for MVT mineral-potential mapping.     

REVIEWS OF GEOGRAPHIC SOFTWARE

Geographic Software Reviewed in this article: LIFE TABLES and the LESLIE MATRIX. CONDUIT MENTMAP2 . Lawrence W. Carstensen Jr . PC-MATLAB , Version 1.0. The Math Works, Inc. QUICKMAP , version 1.0. Sammamish Data Systems, Inc. SYSTAT: THE SYSTEM FOR STATISTICS , Version 2.1, Systat Inc. USA DISPLAY . Instant Tecall     

Knowledge-Driven and Data-Driven Fuzzy Models for Predictive Mineral Potential Mapping

In this paper, we describe new fuzzy models for predictive mineral potential mapping: (1) a knowledge-driven fuzzy model that uses a logistic membership function for deriving fuzzy membership values of input evidential maps and (2) a data-driven model, which uses a piecewise linear function based on quantified spatial associations between a set of evidential evidence features and a set of known mineral deposits for deriving fuzzy membership values of input evidential maps. We also describe a graphical defuzzification procedure for the interpretation of output fuzzy favorability maps. The models are demonstrated for mapping base metal deposit potential in an area in the south-central part of the Aravalli metallogenic province in the state of Rajasthan, western India. The data-driven and knowledge-driven models described in this paper predict potentially mineralized zones, which occupy less than 10% of the study area and contain at least 83% of the model and validation base metal deposits. A cross-validation of the favorability map derived from using one of the models with the favorability map derived from using the other model indicates a remarkable similarity in their results. Both models therefore are useful for predicting favorable zones to guide further exploration work.     

Incorporating GIS Building Data and Census Housing Statistics for Sub-Block-Level Population Estimation

This article presents a deterministic model for sub-block-level population estimation based on the total building volumes derived from geographic information system (GIS) building data and three census block-level housing statistics. To assess the model, we generated artificial blocks by aggregating census block areas and calculating the respective housing statistics. We then applied the model to estimate populations for sub-artificial-block areas and assessed the estimates with census populations of the areas. Our analyses indicate that the average percent error of population estimation for sub-artificial-block areas is comparable to those for sub-census-block areas of the same size relative to associated blocks. The smaller the sub-block-level areas, the higher the population estimation errors. For example, the average percent error for residential areas is approximately 0.11 percent for 100 percent block areas and 35 percent for 5 percent block areas.     

Spatial Analysis Techniques as Successful Mineral-Potential Mapping Tools for Orogenic Gold Deposits in the Northern Fennoscandian Shield,Finland

Geoscientific Information Systems (GIS) provide tools to quantitatively analyze and integrate spatially referenced information from geological, geophysical, and geochemical surveys for decision-making processes. Excellent coverage of well-documented, precise and good quality data enables testing of variable exploration models in an efficient and cost effective way with GIS tools. Digital geoscientific data from the Geological Survey of Finland (GTK) are being used widely as spatial evidence in exploration targeting, that is ranking areas based on their exploration importance. In the last few years, spatial analysis techniques including weights-of-evidence, logistic regression, and fuzzy logic, have been increasingly used in GTK’s mineral exploration and geological mapping projects. Special emphasis has been put into the exploration for gold because of the excellent data coverage within the prospective volcanic belts and because of the increased activity in gold exploration in Finland during recent years. In this paper, we describe some successful case histories of using the weights-of-evidence method for the Au-potential mapping. These projects have shown that, by using spatial modeling techniques, exploration targets can be generated by quantitatively analyzing extensive amounts of data from various sources and to rank these target areas based on their exploration potential.