A Hybrid Fuzzy Weights-of-Evidence Model for Mineral Potential Mapping

This paper describes a hybrid fuzzy weights-of-evidence (WofE) model for mineral potential mapping that generates fuzzy predictor patterns based on (a) knowledge-based fuzzy membership values and (b) data-based conditional probabilities. The fuzzy membership values are calculated using a knowledge-driven logistic membership function, which provides a framework for treating systemic uncertainty and also facilitates the use of multiclass predictor maps in the modeling procedure. The fuzzy predictor patterns are combined using Bayes’ rule in a log-linear form (under an assumption of conditional independence) to update the prior probability of target deposit-type occurrence in every unique combination of predictor patterns. The hybrid fuzzy WofE model is applied to a regional-scale mapping of base-metal deposit potential in the south-central part of the Aravalli metallogenic province (western India). The output map of fuzzy posterior probabilities of base-metal deposit occurrence is classified subsequently to delineate zones with high-favorability, moderate favorability, and low-favorability for occurrence of base-metal deposits. An analysis of the favorability map indicates (a) significant improvement of probability of base-metal deposit occurrence in the high-favorability and moderate-favorability zones and (b) significant deterioration of probability of base-metal deposit occurrence in the low-favorability zones. The results demonstrate usefulness of the hybrid fuzzy WofE model in representation and in integration of evidential features to map relative potential for mineral deposit occurrence.     

Spatial Modeling for Base-Metal Mineral Exploration Through Integration of Geological Data Sets

This study involves the integration of information interpreted from data sets such as LandsatTM, Airborne magnetic, geochemical, geological, and ground-based data of Rajpura—Dariba,Rajasthan, India through GIS with the help of (1) Bayesian statistics based on the weights ofevidence method and (2) a fuzzy logic algorithm to derive spatial models to target potentialbase-metal mineralized areas for future exploration. Of the 24 layers considered, five layers(graphite mica schist (GMS), calc-silicate marble (CALC), NE-SW lineament 0–2000 mcorridor (L4-NESW), Cu 200–250 ppm, and Pb 200–250 ppm) have been identified from theBayesian approach on the basis of contrast. Thus, unique conditions were formed based onthe presence and absence of these five map patterns, which are converted to estimate posteriorprobabilities. The final map, based on the same data used to determine the relationships, showsfour classes of potential zones of sulfide mineralization on the basis of posterior probability.In the fuzzy set approach, membership functions of the layers such as CALC, GMS, NE-SWlineament corridor maps, Pb, and Cu geochemical maps have been integrated to obtain thefinal potential map showing four classes of favorability index.     

基于规则的植被地图综合的研究

植被地图综合是专题地图综合的一个特例,需要遵循地理数据综合规则,以解决因表达空问缩小而造成的地物要素间的冲突问题,确保图面上图形表达的合理、清晰和美观;同时植被地图综合也要遵循植被分布自身的规律。该文主要研究和分析影响植被地图综合的主要规则,首先描述植被地图的特征,在此基础上分析讨论影响植被地图综合的主要综合规则,并简要介绍了用于表达综合规则的产生式规则方法,用实例描述了这些规则在植被地图综合各个阶段的应用和结果,以此来反映综合规则在植被地图综合过程中的重要性。     

Ontologies and representation spaces for sketch map interpretation

In this paper, we present a systematic approach to sketch map interpretation. The method decomposes the elements of a sketch map into a hierarchy of categories, from the material sketch map level to the non-material representational sketch map level, and then interprets the sketch map using the five formal representation spaces that we develop. These spaces (set, graph, metric and Euclidean) provide a tiered formal representation based on standard mathematical structures. We take the view that a sketch map bears information about the physical world and systematises this using extensions of existing formal ontologies. The motivation for this work is the partially automatic extraction and integration of information from sketch maps. We propose a set of ontologies and methods as a first step in the direction of a formalisation of partially automatic extraction and integration of sketch map content. We also see this work as a contribution to spatial cognition, where researchers externalise spatial knowledge using sketch mapping. The paper concludes by working through an example that demonstrates the sketch map interpretation at different levels using the underlying method.     

Application of Data-Driven Evidential Belief Functions to Prospectivity Mapping for Aquamarine-Bearing Pegmatites,Lundazi District,Zambia

A case application of data-driven estimation of evidential belief functions (EBFs) is demonstrated to prospectivity mapping in Lundazi district (eastern Zambia). Spatial data used to represent recognition criteria of prospectivity for aquamarine-bearing pegmatites include mapped granites, mapped faults/fractures, mapped shear zones, and radioelement concentration ratios derived from gridded airborne radiometric data. Data-driven estimates EBFs take into account not only (a) spatial association between an evidential map layer and target deposits but also (b) spatial relationships between classes of evidences in an evidential map layer. Data-driven estimates of EBFs can indicate which spatial data provide positive or negative evidence of prospectivity. Data-driven estimates of EBFs of only spatial data providing positive evidence of prospectivity were integrated according to Dempster’s rule of combination. Map of integrated degrees of belief was used to delineate zones of relative degress of prospectivity for aquamarine-bearing pegmatites. The predictive map has at least 85% prediction rate and at least 79% success rate of delineating training and validation deposits, respectively. The results illustrate usefulness of data-driven estimation of EBFs in GIS-based predictive mapping of mineral prospectivity. The results also show usefulness of EBFs in managing uncertainties associated with evidential maps.     

Automated landslide mapping using spectral analysis and high-resolution topographic data: Puget Sound lowlands, Washington, and Portland Hills, Oregon

Landslide inventory maps are necessary for assessing landslide hazards and addressing the role slope stability plays in landscape evolution over geologic timescales. However, landslide inventory maps produced with traditional methods — aerial photograph interpretation, topographic map analysis, and field inspection — are often subjective and incomplete. The increasing availability of high-resolution topographic data acquired via airborne Light Detection and Ranging (LiDAR) over broad swaths of terrain invites new, automated landslide mapping procedures. We present two methods of spectral analysis that utilize LiDAR-derived digital elevation models of the Puget Sound lowlands, Washington, and the Tualatin Mountains, Oregon, to quantify and automatically map the topographic signatures of deep-seated landslides. Power spectra produced using the two-dimensional discrete Fourier transform and the two-dimensional continuous wavelet transform identify the characteristic spatial frequencies of deep-seated landslide morphologic features such as hummocky topography, scarps, and displaced blocks of material. Spatial patterns in the amount of spectral power concentrated in these characteristic frequency bands highlight past slope instabilities and allow the delineation of landslide terrain. When calibrated by comparison with detailed, independently compiled landslide inventory maps, our algorithms correctly classify an average of 82% of the terrain in our five study areas. Spectral analysis also allows the creation of dominant wavelength maps, which prove useful in analyzing meter-scale topographic expressions of landslide mechanics, past landslide activity, and landslide-modifying geomorphic processes. These results suggest that our automated landslide mapping methods can create accurate landslide maps and serve as effective, objective, and efficient tools for digital terrain analysis.     

Uncertainty management in integration of exploration data using the belief function

The evidential belief function (EBF) provides an adequate theoretical basis for managing uncertainties in exploration data integration. The EBF can be used to represent uncertainties in the reasoning process and provides the capability of distinguishing between lack of information and negative information. This capability is desirable when combining diverse data sets, which often vary in spatial resolution and spatial extent. The uncertainties associated with data and propositions can be represented naturally and consistently using belief functions. Hence, using the EBF approach can provide a realistic quantitative picture of the target proposition.     

Forest fire risk maps: a GIS open source application – a case study in Norwest of Portugal

Forest fires are widely recognized as one of the most critical events in global change. Successful fire management depends on effective fire prevention, detection, and presuppression, having an adequate fire suppression capability, and consideration of fire ecology relationships. Geographical information systems (GIS) provide tools to create, transform, and combine georeferenced variables. In Portugal, as in many other countries, it is mandatory that all the municipalities produce forest fire risk maps on an annual basis, following the rules of the Portuguese Forest Authority, a governmental association. This article presents the results of a research project aimed at producing forest fire risk maps in a GIS open source environment in Portugal. The requirements of an open source application are better quality, higher reliability, more flexibility, lower cost, and an end to predatory vendor lock-in. Three different open source desktop GIS software projects were evaluated: Quantum GIS (QGIS), generalitat valenciana, Sistema d'Informacio Geografica, and Kosmo. Taking into account the skills and experience of the authors, the main advantage of QGIS relies on the easiness and quickness in developing new plug-ins, using Python language. Therefore, this project was developed in QGIS platform and the interface was created in Python. This application incorporates seven procedures under a single toolbar. The production of the forest fire risk map comprises several steps and the production of several maps: probability, susceptibility, hazard, vulnerability, economic value, potential loss, and finally the forest fire risk map. The forest fire risk map comprises five classes: very low risk (dark green), low risk (green), medium risk (yellow), high risk (orange), and very high risk (red). This application was tested in three different municipal governments of the Norwest zone of Portugal. This application has the advantages of grouping in a unique toolbar all the procedures needed to produce forest fire risk maps and is free for the institution/user. Beyond being an open source application, this application may be faster and easier when compared with the GIS proprietary solutions that usually comprise several steps and the use of different software extensions. This work presents several contributions for the area of the GIS open source applications to forest fire risk management.     

基于XML Schema的多源地名词典集成方法

目前,我国已经构建大量不同级别、面向不同应用的地名词典,网络大众化地名服务成为地名词典的必然发展趋势。该文提出一种基于XML Schema的多源异构地名词典集成方法,以XML Schema对地名词典进行数据描述,采用XSLT数据转换方法,运用MapForce软件,快速进行地名词典的数据结构映射,能够有效解决地名词典的跨平台及数据类型不统一问题。     

地球空间数据集成研究概况

数字地球空间数据的集成研究及应用始于本世纪 60年代 ,地理信息系统的出现及应用、多元数据的使用推动了地球空间数据集成研究及其应用。本文首先对地球空间数据概念进行描述 ,然后对地球空间数据集成研究状况及存在的问题进行了详细的分析。结合数据集成需求及存在的问题 ,论文分析了数据集成的发展方向。     

Knowledge-Driven Prospectivity Mapping for Granite-Related Polymetallic Sn–F–(REE) mineralization,Bushveld Igneous Complex,South Africa

This paper presents mineral prospectivity mapping to identify potential new exploration ground for polymetallic Sn–F–REE mineralization associated with the Bushveld granites of the Bushveld Igneous Complex, South Africa. The Lebowa Granite Suite, commonly known as the Bushveld granites, is host to a continuum of polymetallic mineralization with a wide range of metal assemblages (Sn–Mo–W–Cu–Pb–Zn–As–Au–Ag–Fe–F–U–REE), ranging from a high-temperature to a low-temperature magmatic hydrothermal mineralizing environment. The prospectivity map was generated by fuzzy logic modeling and a selection of targeting criteria (or spatial proxies) based on a conceptual mineral system highlighting critical processes responsible for the formation of the polymetallic mineralization. The spatial proxies include proximity to differentiated granites (as heat and metal-rich fluid sources), Rb geochemical map (fluid-focusing mechanism such as fractionation process), principal component maps (PC 4 Y–Th and PC 14 Sn–W, fluid pathways for both high- and low-temperature mineralization) and proximity to roof rocks (traps for fluids). Logarithmic functions were used to rescale rasterized evidential maps into continuous fuzzy membership scores in a range of [0, 1]. The evidential maps were combined in two-staged integration matrix using fuzzy AND, OR and gamma operators to produce the granite-related polymetallic Sn–F–(REE) prospectivity map. The conceptual mineral system model and corresponding prospectivity model developed in this study yielded an encouraging result by delineating the known mineral deposits and occurrences of Sn–F–(REE) mineralization that were not used to assign weights to the evidential maps. The prospectivity model predicted, on average, 77% of the known mineral occurrences in the BIC (i.e., 56 of 73 Sn occurrences, 12 of 15 F occurrences and 6 of 8 REE occurrences). Based on this validation, 13 new targets were outlined in this study.     

Predicting landslides for risk analysis — Spatial models tested by a cross-validation technique

A landslide-hazard map is intended to show the location of future slope instability. Most spatial models of the hazard lack reliability tests of the procedures and predictions for estimating the probabilities of future landslides, thus precluding use of the maps for probabilistic risk analysis. To correct this deficiency we propose a systematic procedure comprising two analytical steps: “relative-hazard mapping” and “empirical probability estimation”. A mathematical model first generates a prediction map by dividing an area into “prediction” classes according to the relative likelihood of occurrence of future landslides, conditional by local geomorphic and topographic characteristics. The second stage estimates empirically the probability of landslide occurrence in each prediction class, by applying a cross-validation technique. Cross-validation, a “blind test” here using non-overlapping spatial or temporal subsets of mapped landslides, evaluates accuracy of the prediction and from the resulting statistics estimates occurrence probabilities of future landslides. This quantitative approach, exemplified by several experiments in an area near Lisbon, Portugal, can accommodate any subsequent analysis of landslide risk.     

A Review of: “Applications of Spatial Data Structures: Computer Graphics,Image Processing,and GIS”. By H. SAMET. (Addison-Wesley Publishing Company,Inc, 1989.) [Pp. xv + 507; figures,tables, appendix,references, name and credit index,subject index.] Price US $49.95. ISBN 020150300 X (hardback).

The introduction of automated generalisation procedures in map production systems requires that generalisation systems are capable of processing large amounts of map data in acceptable time and that cartographic quality is similar to traditional map products. With respect to these requirements, we examine two complementary approaches that should improve generalisation systems currently in use by national topographic mapping agencies. Our focus is particularly on self‐evaluating systems, taking as an example those systems that build on the multi‐agent paradigm. The first approach aims to improve the cartographic quality by utilising cartographic expert knowledge relating to spatial context. More specifically, we introduce expert rules for the selection of generalisation operations based on a classification of buildings into five urban structure types, including inner city, urban, suburban, rural, and industrial and commercial areas. The second approach aims to utilise machine learning techniques to extract heuristics that allow us to reduce the search space and hence the time in which a good cartographical solution is reached. Both approaches are tested individually and in combination for the generalisation of buildings from map scale 1:5000 to the target map scale of 1:25 000. Our experiments show improvements in terms of efficiency and effectiveness. We provide evidence that both approaches complement each other and that a combination of expert and machine learnt rules give better results than the individual approaches. Both approaches are sufficiently general to be applicable to other forms of self‐evaluating, constraint‐based systems than multi‐agent systems, and to other feature classes than buildings. Problems have been identified resulting from difficulties to formalise cartographic quality by means of constraints for the control of the generalisation process.     

Beyond the epsilon band: polygonal modeling of gradation/uncertainty in area-class maps

A spatial modeling technique is proposed to represent boundary uncertainty or gradation on area-class maps using a simple polygon tessellation with designated zones of indeterminacy or transition zones. The transition zone can be conceptualized as a dual of the epsilon band, but is more flexible and allows for a wide range of polygonal configurations, including polygons with sinuous boundaries, spurs, three-way transition zones, and null polygons. The model is specified using the medial axis to capture the general shape characteristics of a transition zone. Graph theoretic representation of an extended version of the medial axis captures key junctions in both shape and classification and is used to identify well-formed transition zones that can be logically and unambiguously handled by the model. A multivariate classification surface is specified by first defining degrees or probabilities of membership at every point on the medial axis and transition zone boundary. Degrees or probabilities of membership at all other points are defined by linear interpolation. The technique is illustrated with an example of a complex transition zone, and a simple isoline representation that can be derived from the model is presented. The proposed modeling technique promises to facilitate expert characterization of soil formations, ecological systems, and other types of areal units where gradation and/or boundary uncertainty are prevalent.     

基于规则数据驱动的专题制图技术及其应用研究

地图制图自动化是地图学的重要目标之一,也是当前研究的热点问题之一,对地球空间信息科学的发展具有十分重要的意义。通过采用Representation技术,以昆明市入滇河道(管线)专题地图制图项目为例,研究探讨基于规则化数据驱动的计算机地图制图表达,部分解决了传统上必须通过大量人工编辑才能够完成的制图任务,特别是实现了传统上需要以破坏数据的GIS属性为代价才能够实现的地图制图效果,结果表明:基于规则驱动的计算机地图制图表达技术能够兼顾GIS和地图制图对数据的不同要求,可快速完成地图制作,并达到传统地图制图效果,节省大量的人力物力,具有广阔的推广和工程应用价值。     

基于MGE的数字地图制图系统若干关键技术

本文在综述数字地图技术功能、特征、发展现状的基础上,介绍了ＭＧＥ数字地图制图系统的体系结构、技术流程和特点,进而从地图数据输入/数字化技术(包括地图的扫描输入、数字影像数据的输入处理、航摄资料的立体数字化、地图/ＧＩＳ数据库的提取４种)、地图色彩库和符号库的制作、地图组版和分色制版关键技术(分为一般地图、影像地图、图－文－图片混排地图等几种类型地图的组版和分色制版,以及一些特殊制图效果的实现技术等)、印刷地图与电子地图的互相转换等方面阐述了基于ＭＧＥ的数字地图制图系统的若干关键技术问题。这些技术对于数字地图环境的地图设计、编辑、印前处理等许多方面都有参考作用。最后,本文对于数字地图一体化的技术进行了展望。     

国家能源、矿产资源安全的功能区划与西部地区定位

资源安全是国家安全的重要组成部分。国家资源安全须建立在地区间合理分工与协作的基础之上 ,是对地区资源安全的整合。我国东、中、西三大地带的资源赋存状况和社会经济条件差异显著 ,在保障国家资源安全方面承担的职能也应有所区别。能源和矿产资源是非原位性资源 ,地区间的合理配置是保障国家资源安全的基础 ;为此 ,本文在综合考虑资源条件、交通运输条件以及生态条件等因素的前提下 ,进行了国家能矿资源安全的功能区域划分 ,提出应将全国的能矿资源富集区划分为开发区、接替区和储备区三种类型 ,并将这一划分方案具体运用到西部地区 ,针对各能矿资源集中区的实际情况 ,提出了相应的对策和建议。最后 ,在客观评价西部能矿资源特点及开发现状的基础上 ,展望了西部在国家资源安全格局中所应具有的地位以及为此需要做出的努力。     

Automatic change detection in lane-level road networks using GPS trajectories

Lane-level road network updating is crucial for urban traffic applications that use geographic information systems contributing to, for example, intelligent driving, route planning and traffic control. Researchers have developed various algorithms to update road networks using sensor data, such as high-definition images or GPS data; however, approaches that involve change detection for road networks at lane level using GPS data are less common. This paper presents a novel method for automatic change detection of lane-level road networks based on GPS trajectories of vehicles. The proposed method includes two steps: map matching at lane level and lane-level change recognition. To integrate the most up-to-date GPS data with a lane-level road network, this research uses a fuzzy logic road network matching method. The proposed map-matching method starts with a confirmation of candidate lane-level road segments that use error ellipses derived from the GPS data, and then computes the membership degree between GPS data and candidate lane-level segments. The GPS trajectory data is classified into successful or unsuccessful matches using a set of defuzzification rules. Any topological and geometrical changes to road networks are detected by analysing the two kinds of matching results and comparing their relationships with the original road network. Change detection results for road networks in Wuhan, China using collected GPS trajectories show that these methods can be successfully applied to detect lane-level road changes including added lanes, closed lanes and lane-changing and turning rules, while achieving a robust detection precision of above 80%.     

支持动态地理现象理解的运动要素地图表现

空间运动现象是动态地理现象的一种重要表现形式,该文从运动状态与历史过程的静态表现、运动过程生命期的顺序动态表现及目标运动过程的动态特征表现等方面,论述了运动系统中运动对象运动特征的地图表现问题。对于目标运动过程动态特征的地图表现,提出了运动实时动态特征中的方向关系、距离关系及拓扑关系表现问题与方法,并以船舶导航为对象给出了相应的实例。     

Utilizing the Audio-Tutorial Approach

Abstract

Construction of raised-relief maps by students in middle school to high school is a rewarding “hands-on” experience. A major feature of this project is that materials are readily available, inexpensive and manageable by students themselves. Tracing from topographic maps on to inexpensive, easily-carved materials like cardboard or foam-core board involves the student in map interpretation techniques. Concepts such as interpreting elevations from contour lines, recognizing symbolization on a map, seeing raised-relief as representing “the lay of the land,” understanding map scale, and recognition of color in representation of elevations are part of this experience. Carving and construction of the raised-relief map give the student an appreciation of topographic features in 3-D. The finished model can serve as a display and learning tool for the future.