基于空间信息网格的长江中下游矿产资源评价方法
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摘要
矿产资源潜力评价作为找矿勘查的前期工作,已日益受到各国政府的高度重视。同时,矿产资源评价的相关理论、技术方法在经历了实验探索、应用发展和信息化建设三个阶段的发展,也已日趋成熟。然而,在对目前矿产资源评价的相关理论、技术方法的进一步研究发现：①随着GIS的飞速发展,基于多源(异域)、异构空间信息资源的共享及其矿产资源评价方法的实现日益凸现；②在GIS矿产资源评价过程中如何避免图层的叠加简单,克服地质构造信息与矿产预测脱节、模型区与预测区信息不对等问题已逐步成为当前研究的主要内容。
矿床模型综合地质信息预测技术是在充分总结国内外二十多年来矿产资源评价方法的基础上,由叶天竺教授在国家高技术研究发展计划(863计划)《基于SIG的资源环境空间信息共享与应用服务》课题中提出的一套矿产资源预测方法评价体系,其核心是以矿床地质模型为指导,强化成矿地质构造的研究,旨在解决地质构造信息与矿产预测脱节等信息不对等问题,实现精细化预测。而空间信息网格是将空间数据资源、计算资源、存储资源、数据处理软件以及用户进行有效的连接,形成一个分布式的网络化环境,从而实现多源(异域)、异构空间信息资源的共享。基于此思路,本文提出了基于空间信息网格(SIG)的长江中下游矿产资源评价方法,并以构建的国家地质空间信息网格(NGSIG)为基础应用平台,以矿床模型综合地质信息预测技术方法为技术手段,以基于SIG的证据权法为评价方法,以长江中下游四省的实际资料为依托开展研究,并取得了较为理想的实际效果。
1、国家地质空间信息网格(NGSIG)
(1)网格体系结构
国家地质空间信息网格采用了万维网服务体系架构、并以资源和信息共享以及协同为主线,根据WSRF的服务机制和WSRF的设计理念,通过PORTL和网格结点计算池的协同而搭建。并在智能空间引擎、元服务及元服务级的并行计算、服务协同、均衡负载等关键技术上进行了创新,充分考虑和弥补了Web服务协议的不足,实现了Web服务和一个或者多个有状态,的资源之间的关联。实现了分布式数据、软件、硬件等资源的共享和协同,发展了空间信息网格技术。
(2)国家地质空间信息网格体系
国家地质空间信息网格(NGSIG)主要基于GIS技术、大型GIS平台与技术、空间信息共享规范等相关支撑技术,由逻辑体系、物理体系和应用体系等三大体系构成。
①逻辑体系
国家地质空间信息网格在逻辑上分为七层结构,即：获取预处理层、连接层、资源层、共享层、服务分析处理层、汇集层、应用层。上层可以调用下层的功能和服务。
②物理体系
物理体系的基本构成单元为“结点”。NGSIG的结点类型主要有UDDI注册结点、数据服务结点、专业处理服务结点、计算服务结点等。
如果按照行政区隶属关系划分,又可分为如下结点：(1)国家地质调查数据中心结点；
(2)大区与专业中心结点(10个);(3)省地调院结点(31个)。
③应用体系
从应用需求的角度出发,描述基于国家地质空间信息网格的空间信息应用流程,划分应用层次,描述各部分之间关系。
国家地质空间信息网格能够实现空间信息及空间处理资源的共享集成、信息融合和系统互操作。对于地矿行业的各种应用,地质空间信息服务体系可以联合一省、数省甚至全国的诸多行业部门,利用相关的多个分布的空间数据库,对相应的地物空间信息进行分析、处理、分发；形成强大的分布计算能力以及高速的空间信息获取、传输、存储、分发能力和共享互操作机制。
(3)国家地质空间信息网格平台基础设施
NGSIG网格平台基础设施构成有四大部分：数据模型与各种数据资源、网络基础设施、相关标准与协议和与环境资源相关的各种软硬件。
(4)国家地质空间信息网格平台基本框架
NGSIG网格平台的核心由两部分组成,即NGISG门户(PORTAL)和网格结点计算池组成。Portal是国家地质空间信息网格服务的入口,网格结点计算池是网格中间件平台,屏蔽底层硬件和软件信息,给用户提供完全透明的计算或服务环境。
2、矿床模型综合地质信息预测技术
矿床模型综合地质信息预测技术体系的核心是以矿床地质模型为指导,以地球动力学构造建造成矿预测分析为基础,全过程实现GIS。其核心主要体现在两个方面：
(1)通过成矿地质构造的研究,解决地质构造信息与矿产预测脱节等信息不对等的问题,实现精细化预测,其主要途径是通过编制沉积建造古构造图、岩浆构造图；大地构造相图等系列图来实现。
(2)全面全过程实现GIS,这也是矿床模型综合地质信息预测技术的特色之一,要做到这一点,首要的问题是研究解决一体化数据模型及多源、异构数据的一体化组织与管理。
3、基于SIG的矿产资源评价方法的研究与实践
国家地质空间信息网格(NGSIG)的搭建为本文的应用实践提供了基础应用平台,矿床模型综合地质信息预测技术体系得提出为本文的应用实践提供了技术思路和手段。但有了应用平台和技术框架,还应有适合于平台和技术应用的具体方法和操作环节。
(1)地质空间数据的一体化组织与管理
由于本文的研究数据是分布在四个省结点上,且为多源、多比例尺、异构地质空间数据,因此必须对地质空间数据进行一体化的组织与管理,才能保证应用示范的正常进行。
①数据的一体化描述
数据一体化描述的核心是建立数据模型。数据模型是一种数据(实体)、数据(实体)之间的联系,以及有关语义约束规则的形式化描述。数据模型规定了数据的内容、结构、行为和语义。本文根据地质调查数据产品生产的需要及以往数据模型建模的实践,建立了面向对象的数据模型。并在此基础上确立了地质调查信息分类和编码规则(包括地质要素类[实体类]编码规则、图元编码、要素标示编码和图层文件命名规则等)。
②数据的一体化组织与管理
根据上述数据模型,建立了本文的基础数据库和专题数据库,其中基础数据图层32个,专题图层21个。
③数据的一体化处理
数据处理是数据一体化组织与管理的核心环节之一,它主要是对省结点数据语义及表达的统一、省间图层的接边处理、省间图层的接图处理等。
④结点部属与发布
国家地质空间信息网格(NGSIG)结点部署主要分布在北京、6个大区中心(天津、南京、沈阳、宜昌、成都、西安)和15个省(自治区、直辖市)地质调查院,本文示范区主要部署在江苏、安徽、江西和湖北四个省结点上。
数据的发布与注册由各结点通过SIG结点客户端数据工具软件来完成。其主要任务是将完成的数据上载到SIG结点服务器上(其中江苏发布数据图层53个、安徽51个、江西52个、湖北52个),并同时在各结点和国家地质空间信息网格(NGSIG)上进行数据注册登记,使之成为国家地质空间信息网格(NGSIG)上可利用的数据资源。
(2)地质构造研究及综合地质信息编图
成矿地质构造研究是矿床模型综合地质信息预测技术用于解决地质构造信息与矿产预测脱节等信息不对等的问题,实现精细化预测的关键所在,其主要途径是通过编制沉积建造古构造图、岩浆构造图；大地构造相图等系列图来实现。
本文根据陈毓川院士的有关成矿理论,结合矿床模型综合地质信息预测技术的相关要求,编制了岩浆构造图；陆块区大地构造相图。同时按照铜矿成矿的目标层编制了早中三叠纪沉积建造古构造图、中晚二叠纪大隆—长兴期沉积建造古构造图、中晚二叠纪孤峰—武穴期沉积建造古构造图、中晚二叠纪龙潭—吴家坪期沉积建造古构造图、中晚二叠纪栖霞期沉积建造古构造图、中晚石炭-早二叠纪沉积建造古构造图。
(3)预测标志的建立与选择
预测标志的建立和参数的选择是在典型矿床研究的基础,根据找矿模型来确定。就矿产资源评价工作而言,并不是参与评价的标志(参数)越多,其效果就越好,有时却恰恰相反,因为参数(变量)与参数之间是相互独立而又相互关联的,因此有些参数之间会产生相互消减。因此,预测标志的建立和参数的选择与筛选,即要充分考虑其控矿作用,又要考虑它在区域的代表性。
本文根据上述原则,用不同的方法和手段对预测标志和参数进行了筛选,通过反复叠加和筛选,本次预测共筛选和提取预测标志12个：
地层：三叠、二叠、石碳和志留系地层；
岩浆岩：主要为燕山期的中酸性岩类,如石英二长闪长玢岩、斑状石英二长闪长岩、石英二长闪长岩等；
沉积建造：中三叠纪、中晚二叠纪大隆—长兴期、中晚二叠纪孤峰—武穴期、中晚二叠纪龙潭—吴家坪期、中晚二叠纪栖霞期、中晚石炭-早二叠纪等六个沉积建造古构造图层的叠加部分；
物探：物探推断构造、重力异常、航磁异常、物化探推断的隐伏岩体；
化探：Cu、Pb、Zn、Au等单元素异常；
遥感：遥感解译的线性构造和环形构造。
根据上述研究,本文最终采用基于SIG的在线证据权法对长江中下游示范区进行了预测评价,获得了相应预测结果。经对圈定预测区的分析和对比,参与建模的18个典型矿床均在预测区内,同时有部分预测区为本次预测新发现的区域,值得重视,得到了专家的认可,预测结果科学、可信。
综上所述,基于空间信息网格(SIG)的长江中下游矿产资源评价方法研究首次以国家地质空间信息网格为平台,以长江中下游四省的实际资料为依托,以矿床模型综合地质信息预测技术方法为技术手段,采用基于SIG的在线证据权法对长江中下游示范区进行了预测评价,具备了坚实的理论基础(前人基础地质及矿产地质研究成果、成矿基础理论和预测理论)和较为成熟的技术条件(空间信息网格、空间数据的一体化组织与管理、空间分析方法)。同时通过研究,对矿床模型综合地质信息预测技术的方法、流程进行了全面探索和全过程实践,初步建立了矿床模型综合地质信息预测技术体系。建立在该理论体系之上的居于模型数据驱动的预测结果可视为一种较为客观的结果(包含客观数据、专家知识及基础理论),也是较为准确的预测结果。
本文的研究对矿产资源评价的技术和方法具有十分重要的意义：①空间信息网格的建立与应用,为预测评价提供了一种新型的思路和途径,有效地解决了分布式数据,一体化组织与处理的方法和途径,保护了数据生产单位的利益。信息网格是未来互联网信息技术发展主流,而空间信息网格也将成为地质信息化建设的趋势；②矿床模型综合地质信息预测技术体系的提出与建立,为有效地解决地质构造信息与矿产预测脱节等信息不对等,实现精细化预测提供了新的思路和技术手段,该方法已在现在中国地质调查局正在开展的《全国重要矿产资源潜力预测评价及综合》项目中全面应用,,为其提供了良好的理论基础和方法依据。
Appraise of mineral resources as prophase work of mineral exploration are high emphasized by governments. The correlation theory and technology are grown up going through experiment explore, application development and information construct three phases. But the problems of correlation theory and technology of appraise of mineral resources are existed as currently major research works:(1) The information resource communion based on multi-source (different field) and different construct space along with GIS developing;(2) Avoid graph layer simple superposition, conquer disjoint between geological constitution information and mineral resources and information non-equivalence between model field and forecast field.
The deposit model synthetically geology information forecast technology is a suit of mineral resources forecast appraise system put forward by Ye tian-zhu professor on the bases of plenty summing up mineral resources appraise method in more then twenty years in task of (863 plan). The key is intensify study on ore-forming geological tectonic guided by deposit geological model to resolve information non-equivalence between geological construction information and mineral resource forecast. The space information gridding connect by space data res, count res, memory res, data processing software with user forming distributing network condition to realize res communion for multiple data (different filed) sources. Based on this idea, the appraise method of mineral resource for middle-lower reaches of Changjiang based on Spatial Information Grid are put forward. By base apply plat roof of the national geological space grid (SIG), using technology means of deposit model geological info forecast and SIG attestation right, the practicality data of four provinces in middle-lower reaches Changjiang are studied to get unearthly purpose.
1. National Geology Spatial Information Grid (NGSIG)
(1) Grid architecture
The national geological space grid are cooperated with PORTL and grid node calculation pool to set up using World-Wide-Web serving system for communion of res and info according to WSRF serving mechanism and design concept. NGSIG is inaugurated in the key technically of intelligent space engine, element service parallel computation, service coordination and load balance making up the lack of Web service consultative to realize Web service associated with one or more postural res making res communion and cooperate with distributing data, software and hardware.
(2) System of National Geology Spatial Information Grid
The NGSIG are constituted of logic system, physics and application system based on GIS, GIS plat roof and criterion of space info communion.
①Logic system
The NGSIC is divide into 7 layers framework in logic as get pretreatment layer, connect, resources, share, service analysis dispose, influx, application layer. Super stratum layer may transfer function and service of lower layer.
②Physics system
The basis cell of physics of system is "nodes". The nodes style of NGSIG is UDDI enroll node, data service node, specialty disposal service node and calculate service node.
It may divide in district into:(1) The nodes of data center of national geological survey; (2) nodes of great section and professional centers (3) the nodes of geological survey of provinces.
③Application system
The space info apply flow is described based on NGSIG to divide apply arrangement and relations between each other from apply demand.
The NGSIG may be share integration, information fuse and operated each other for space information and space dispose res. The geological space information service system may associated with a province or much provinces more vocation branch using multi-space databank to analysis correspond terra space information and to form mighty calculate ability and high-speed space information taken, transmission, storage, dispense and communion for geological industry.
(3) Base establishment of NGSIG flat roof
NGSIG flat roof is composed of four parts:data model and data res, network base establishment, correlation criterion and agreement, each correlative soft-hardware.
(4)Basic frame of NGSIG flat roof
The key of NGSIG flat roof is composed of two parts as NGISG portal (PORTAL) and gridding node calculation pool. The Portal is the mouth of NGISG. The gridding node calculation pool is the plat roof to screen bottom hardware and software giving completeness transparent calculate or service condition.
2. Forecast technology of deposit model synthetically geological information
The key of Forecast technology of deposit model synthetically geological information is guided by deposit model based on geodynamics to form GIS in full process. Its key mostly is in two sides:
(1) The ore-forming geotectonic study resolves the problem of information non-equivalence between geotectonic information and deposit forecast by compiling sediment construct old structure map, magmatic structural map and earth structure graph map.
(2) The one of the feature of forecast technology of deposit model synthetically geological information is realized GIS in whole course.
3. The study and practice of mineral resources evaluation based on SIG
The NGSIG provide base apply flat roof for our practice. Forecast technology of deposit model synthetically geological information provides techno thought and means. The concrete method and operation link being fit for plat roof are needed for practice.
(1) Integration organize and manage of geological space data
Because of the data distributed in four provinces node with different resource, different scale and different tectonic space data, integration organize and manage of geological space data are needed to pledge on the rails of demonstration.
①Integration describing of data
The key of Integration describing of data is set up data model. The data model is a relation between data (entity) and data (entity) and formalize describe of leash regular. The data model regulates data content, data frame, data action and data meaning. The data model is set up for user according to geological survey data and practice. On the bases above, the geological survey information classify and coding rule are set up (including geological essential coding rule, graphic element, basic designation coding and graphic layer document naming rule).
②Integration organize and manage of data
Based on the data above, basic data data-base and special data-base are set up, including basic data graphic layer 32 and special graphic layer 21.
③Integration deal with data
The data processing is one of the core segment of Integration organize and manage of data which are manly consolidate data Punjabi and expression of province node, meet border of graphic layer in different provinces and meet graphic layer dispose in different.
④Node arrange and issue
The node arrange of NGSIG are manly distributed in Beijing, six centers of great section (Tianjing, Nanjing, Shengyang, Yichang, Chengdou and Xian) 15 provinces geological survey yard. The demonstration borough in this paper is manly arranged bodes in Jiangsu, Anhui, Jiangxi and Hubei provinces.
The issue and enroll of data are achieved by each node passing SIG node client end tool software, which are manly record data to SIG node server(among them,53 graphic layer of Jiangsu,51 graphic layer of Anhui,52 graphic layer of Jiangxi and 52 graphic layer of Hubei) and data enroll becoming available data of NGSIG.
(2) Geological structure study and synthetically geological information drawing
Ore-forming geological structure study is the shoe pinches of forecast technology of deposit model synthetically geological information to resolve information non-equivalence between geological construction information and mineral resource forecast and to realize fine forecast by compiling sediment construct old structure map, magmatic structural map and earth structure graph map.
According to the metallogenic theory of Cheng yu-chuan combined with correlation require of Forecast technology of deposit model synthetically geological information, the magmatic structural map and earth structure graph map are compiling. At the same time, we are compiling early-middle Trias sediment construct old structure map, middle-late Permian period Dalong-Changxin sediment construct old structure map, middle-late Permian period Gufeng-Wuxue sediment construct old structure map, middle-late Permian period Longtan-wujiapin sediment construct old structure map, middle-late Permian period Qixia sediment construct old structure map and middle-late Carboniferous-early Permian period sediment construct old structure map with the copper object layer.
(3) Marker for predicting foundation and choice
Marker for predicting foundation and parameter choice confirmed base on exploration model. Ascertain of Marker for predicting foundation and parameter choice confirmed by ore-controlling factors and regional representative.
According to the principle above,12 markers for predicting are set up by different method and means.
Stratum:Trias, Permian, Carboniferous and Silurian;
Magma:mostly Yanshanian intermediate-acidic rocks, as quartz monzodiorite porphyrite, quartz monzodiorite and porphyritic quartz monzodiorite;
Sediment construct:middle Trias, middle-late Permian period Dalong-Changxin, middle-late Permian period Gufeng-Wuxue, middle-late Permian period Longtan-wujiapin, middle-late Permian period Qixia and middle-late Carboniferous-early Permian period six sediment construct
Physical exploration:physical exploration concluded structure, gravity anomaly, aeromagnetic anomaly and Concealed Rock Mass.
Geochemical exploration:single element anomaly of Cu、Pb、Zn、Au;
Remote sensing:linearity and ring structure by remote sensing interpretation.
According to the study above, we introduce finally online evidence right based on SIG to forecast evaluation of middle-lower of Changjiang river demonstration and to get correspond results. The 18 representative modeling deposits all exist in forecast section finding new region recognized by experts.
As mentioned above, the mineral resources evaluation method of middle-lower Changjiang river have stability theory base and adult technology based on SIG and late roof of NGISG supported by practicality data of four provinces in middle-lower Changjiang river and finally online evidence right. The system of forecast technology of deposit model synthetically geological information is set up by study and process practice. The forecast result may treat as an external result and an exact result based on system info driving by model data (impersonality, expert knowledge and basic theory).
The study have quite important sense for mineral resources evaluation technology and method:①The apace information grid establishing and application provide a new thought and approach to resolve availably distributing data and integration organize and manage of data means and approach, and to protect advantage of data manufacture. Information grid is development artery of future internet information technology. The space information grid would be current of geological information-based.②The forecast technology system of deposit model synthetically geological information put forward and foundation settle availably conquer disjoint between geological constitution information and mineral resources and information non-equivalence between model field and forecast field to come true fine forecast by new thought and technology. Now the method is application in the item< The important mineral resources potential evaluation and colligate> of geological survey bureau of China providing favorable theory base and method gist.
矿床模型综合地质信息预测技术是在充分总结国内外二十多年来矿产资源评价方法的基础上,由叶天竺教授在国家高技术研究发展计划(863计划)《基于SIG的资源环境空间信息共享与应用服务》课题中提出的一套矿产资源预测方法评价体系,其核心是以矿床地质模型为指导,强化成矿地质构造的研究,旨在解决地质构造信息与矿产预测脱节等信息不对等问题,实现精细化预测。而空间信息网格是将空间数据资源、计算资源、存储资源、数据处理软件以及用户进行有效的连接,形成一个分布式的网络化环境,从而实现多源(异域)、异构空间信息资源的共享。基于此思路,本文提出了基于空间信息网格(SIG)的长江中下游矿产资源评价方法,并以构建的国家地质空间信息网格(NGSIG)为基础应用平台,以矿床模型综合地质信息预测技术方法为技术手段,以基于SIG的证据权法为评价方法,以长江中下游四省的实际资料为依托开展研究,并取得了较为理想的实际效果。
1、国家地质空间信息网格(NGSIG)
(1)网格体系结构
国家地质空间信息网格采用了万维网服务体系架构、并以资源和信息共享以及协同为主线,根据WSRF的服务机制和WSRF的设计理念,通过PORTL和网格结点计算池的协同而搭建。并在智能空间引擎、元服务及元服务级的并行计算、服务协同、均衡负载等关键技术上进行了创新,充分考虑和弥补了Web服务协议的不足,实现了Web服务和一个或者多个有状态,的资源之间的关联。实现了分布式数据、软件、硬件等资源的共享和协同,发展了空间信息网格技术。
(2)国家地质空间信息网格体系
国家地质空间信息网格(NGSIG)主要基于GIS技术、大型GIS平台与技术、空间信息共享规范等相关支撑技术,由逻辑体系、物理体系和应用体系等三大体系构成。
①逻辑体系
国家地质空间信息网格在逻辑上分为七层结构,即：获取预处理层、连接层、资源层、共享层、服务分析处理层、汇集层、应用层。上层可以调用下层的功能和服务。
②物理体系
物理体系的基本构成单元为“结点”。NGSIG的结点类型主要有UDDI注册结点、数据服务结点、专业处理服务结点、计算服务结点等。
如果按照行政区隶属关系划分,又可分为如下结点：(1)国家地质调查数据中心结点；
(2)大区与专业中心结点(10个);(3)省地调院结点(31个)。
③应用体系
从应用需求的角度出发,描述基于国家地质空间信息网格的空间信息应用流程,划分应用层次,描述各部分之间关系。
国家地质空间信息网格能够实现空间信息及空间处理资源的共享集成、信息融合和系统互操作。对于地矿行业的各种应用,地质空间信息服务体系可以联合一省、数省甚至全国的诸多行业部门,利用相关的多个分布的空间数据库,对相应的地物空间信息进行分析、处理、分发；形成强大的分布计算能力以及高速的空间信息获取、传输、存储、分发能力和共享互操作机制。
(3)国家地质空间信息网格平台基础设施
NGSIG网格平台基础设施构成有四大部分：数据模型与各种数据资源、网络基础设施、相关标准与协议和与环境资源相关的各种软硬件。
(4)国家地质空间信息网格平台基本框架
NGSIG网格平台的核心由两部分组成,即NGISG门户(PORTAL)和网格结点计算池组成。Portal是国家地质空间信息网格服务的入口,网格结点计算池是网格中间件平台,屏蔽底层硬件和软件信息,给用户提供完全透明的计算或服务环境。
2、矿床模型综合地质信息预测技术
矿床模型综合地质信息预测技术体系的核心是以矿床地质模型为指导,以地球动力学构造建造成矿预测分析为基础,全过程实现GIS。其核心主要体现在两个方面：
(1)通过成矿地质构造的研究,解决地质构造信息与矿产预测脱节等信息不对等的问题,实现精细化预测,其主要途径是通过编制沉积建造古构造图、岩浆构造图；大地构造相图等系列图来实现。
(2)全面全过程实现GIS,这也是矿床模型综合地质信息预测技术的特色之一,要做到这一点,首要的问题是研究解决一体化数据模型及多源、异构数据的一体化组织与管理。
3、基于SIG的矿产资源评价方法的研究与实践
国家地质空间信息网格(NGSIG)的搭建为本文的应用实践提供了基础应用平台,矿床模型综合地质信息预测技术体系得提出为本文的应用实践提供了技术思路和手段。但有了应用平台和技术框架,还应有适合于平台和技术应用的具体方法和操作环节。
(1)地质空间数据的一体化组织与管理
由于本文的研究数据是分布在四个省结点上,且为多源、多比例尺、异构地质空间数据,因此必须对地质空间数据进行一体化的组织与管理,才能保证应用示范的正常进行。
①数据的一体化描述
数据一体化描述的核心是建立数据模型。数据模型是一种数据(实体)、数据(实体)之间的联系,以及有关语义约束规则的形式化描述。数据模型规定了数据的内容、结构、行为和语义。本文根据地质调查数据产品生产的需要及以往数据模型建模的实践,建立了面向对象的数据模型。并在此基础上确立了地质调查信息分类和编码规则(包括地质要素类[实体类]编码规则、图元编码、要素标示编码和图层文件命名规则等)。
②数据的一体化组织与管理
根据上述数据模型,建立了本文的基础数据库和专题数据库,其中基础数据图层32个,专题图层21个。
③数据的一体化处理
数据处理是数据一体化组织与管理的核心环节之一,它主要是对省结点数据语义及表达的统一、省间图层的接边处理、省间图层的接图处理等。
④结点部属与发布
国家地质空间信息网格(NGSIG)结点部署主要分布在北京、6个大区中心(天津、南京、沈阳、宜昌、成都、西安)和15个省(自治区、直辖市)地质调查院,本文示范区主要部署在江苏、安徽、江西和湖北四个省结点上。
数据的发布与注册由各结点通过SIG结点客户端数据工具软件来完成。其主要任务是将完成的数据上载到SIG结点服务器上(其中江苏发布数据图层53个、安徽51个、江西52个、湖北52个),并同时在各结点和国家地质空间信息网格(NGSIG)上进行数据注册登记,使之成为国家地质空间信息网格(NGSIG)上可利用的数据资源。
(2)地质构造研究及综合地质信息编图
成矿地质构造研究是矿床模型综合地质信息预测技术用于解决地质构造信息与矿产预测脱节等信息不对等的问题,实现精细化预测的关键所在,其主要途径是通过编制沉积建造古构造图、岩浆构造图；大地构造相图等系列图来实现。
本文根据陈毓川院士的有关成矿理论,结合矿床模型综合地质信息预测技术的相关要求,编制了岩浆构造图；陆块区大地构造相图。同时按照铜矿成矿的目标层编制了早中三叠纪沉积建造古构造图、中晚二叠纪大隆—长兴期沉积建造古构造图、中晚二叠纪孤峰—武穴期沉积建造古构造图、中晚二叠纪龙潭—吴家坪期沉积建造古构造图、中晚二叠纪栖霞期沉积建造古构造图、中晚石炭-早二叠纪沉积建造古构造图。
(3)预测标志的建立与选择
预测标志的建立和参数的选择是在典型矿床研究的基础,根据找矿模型来确定。就矿产资源评价工作而言,并不是参与评价的标志(参数)越多,其效果就越好,有时却恰恰相反,因为参数(变量)与参数之间是相互独立而又相互关联的,因此有些参数之间会产生相互消减。因此,预测标志的建立和参数的选择与筛选,即要充分考虑其控矿作用,又要考虑它在区域的代表性。
本文根据上述原则,用不同的方法和手段对预测标志和参数进行了筛选,通过反复叠加和筛选,本次预测共筛选和提取预测标志12个：
地层：三叠、二叠、石碳和志留系地层；
岩浆岩：主要为燕山期的中酸性岩类,如石英二长闪长玢岩、斑状石英二长闪长岩、石英二长闪长岩等；
沉积建造：中三叠纪、中晚二叠纪大隆—长兴期、中晚二叠纪孤峰—武穴期、中晚二叠纪龙潭—吴家坪期、中晚二叠纪栖霞期、中晚石炭-早二叠纪等六个沉积建造古构造图层的叠加部分；
物探：物探推断构造、重力异常、航磁异常、物化探推断的隐伏岩体；
化探：Cu、Pb、Zn、Au等单元素异常；
遥感：遥感解译的线性构造和环形构造。
根据上述研究,本文最终采用基于SIG的在线证据权法对长江中下游示范区进行了预测评价,获得了相应预测结果。经对圈定预测区的分析和对比,参与建模的18个典型矿床均在预测区内,同时有部分预测区为本次预测新发现的区域,值得重视,得到了专家的认可,预测结果科学、可信。
综上所述,基于空间信息网格(SIG)的长江中下游矿产资源评价方法研究首次以国家地质空间信息网格为平台,以长江中下游四省的实际资料为依托,以矿床模型综合地质信息预测技术方法为技术手段,采用基于SIG的在线证据权法对长江中下游示范区进行了预测评价,具备了坚实的理论基础(前人基础地质及矿产地质研究成果、成矿基础理论和预测理论)和较为成熟的技术条件(空间信息网格、空间数据的一体化组织与管理、空间分析方法)。同时通过研究,对矿床模型综合地质信息预测技术的方法、流程进行了全面探索和全过程实践,初步建立了矿床模型综合地质信息预测技术体系。建立在该理论体系之上的居于模型数据驱动的预测结果可视为一种较为客观的结果(包含客观数据、专家知识及基础理论),也是较为准确的预测结果。
本文的研究对矿产资源评价的技术和方法具有十分重要的意义：①空间信息网格的建立与应用,为预测评价提供了一种新型的思路和途径,有效地解决了分布式数据,一体化组织与处理的方法和途径,保护了数据生产单位的利益。信息网格是未来互联网信息技术发展主流,而空间信息网格也将成为地质信息化建设的趋势；②矿床模型综合地质信息预测技术体系的提出与建立,为有效地解决地质构造信息与矿产预测脱节等信息不对等,实现精细化预测提供了新的思路和技术手段,该方法已在现在中国地质调查局正在开展的《全国重要矿产资源潜力预测评价及综合》项目中全面应用,,为其提供了良好的理论基础和方法依据。
Appraise of mineral resources as prophase work of mineral exploration are high emphasized by governments. The correlation theory and technology are grown up going through experiment explore, application development and information construct three phases. But the problems of correlation theory and technology of appraise of mineral resources are existed as currently major research works:(1) The information resource communion based on multi-source (different field) and different construct space along with GIS developing;(2) Avoid graph layer simple superposition, conquer disjoint between geological constitution information and mineral resources and information non-equivalence between model field and forecast field.
The deposit model synthetically geology information forecast technology is a suit of mineral resources forecast appraise system put forward by Ye tian-zhu professor on the bases of plenty summing up mineral resources appraise method in more then twenty years in task of (863 plan)
1. National Geology Spatial Information Grid (NGSIG)
(1) Grid architecture
The national geological space grid are cooperated with PORTL and grid node calculation pool to set up using World-Wide-Web serving system for communion of res and info according to WSRF serving mechanism and design concept. NGSIG is inaugurated in the key technically of intelligent space engine, element service parallel computation, service coordination and load balance making up the lack of Web service consultative to realize Web service associated with one or more postural res making res communion and cooperate with distributing data, software and hardware.
(2) System of National Geology Spatial Information Grid
The NGSIG are constituted of logic system, physics and application system based on GIS, GIS plat roof and criterion of space info communion.
①Logic system
The NGSIC is divide into 7 layers framework in logic as get pretreatment layer, connect, resources, share, service analysis dispose, influx, application layer. Super stratum layer may transfer function and service of lower layer.
②Physics system
The basis cell of physics of system is "nodes". The nodes style of NGSIG is UDDI enroll node, data service node, specialty disposal service node and calculate service node.
It may divide in district into:(1) The nodes of data center of national geological survey; (2) nodes of great section and professional centers (3) the nodes of geological survey of provinces.
③Application system
The space info apply flow is described based on NGSIG to divide apply arrangement and relations between each other from apply demand.
The NGSIG may be share integration, information fuse and operated each other for space information and space dispose res. The geological space information service system may associated with a province or much provinces more vocation branch using multi-space databank to analysis correspond terra space information and to form mighty calculate ability and high-speed space information taken, transmission, storage, dispense and communion for geological industry.
(3) Base establishment of NGSIG flat roof
NGSIG flat roof is composed of four parts:data model and data res, network base establishment, correlation criterion and agreement, each correlative soft-hardware.
(4)Basic frame of NGSIG flat roof
The key of NGSIG flat roof is composed of two parts as NGISG portal (PORTAL) and gridding node calculation pool. The Portal is the mouth of NGISG. The gridding node calculation pool is the plat roof to screen bottom hardware and software giving completeness transparent calculate or service condition.
2. Forecast technology of deposit model synthetically geological information
The key of Forecast technology of deposit model synthetically geological information is guided by deposit model based on geodynamics to form GIS in full process. Its key mostly is in two sides:
(1) The ore-forming geotectonic study resolves the problem of information non-equivalence between geotectonic information and deposit forecast by compiling sediment construct old structure map, magmatic structural map and earth structure graph map.
(2) The one of the feature of forecast technology of deposit model synthetically geological information is realized GIS in whole course.
3. The study and practice of mineral resources evaluation based on SIG
The NGSIG provide base apply flat roof for our practice. Forecast technology of deposit model synthetically geological information provides techno thought and means. The concrete method and operation link being fit for plat roof are needed for practice.
(1) Integration organize and manage of geological space data
Because of the data distributed in four provinces node with different resource, different scale and different tectonic space data, integration organize and manage of geological space data are needed to pledge on the rails of demonstration.
①Integration describing of data
The key of Integration describing of data is set up data model. The data model is a relation between data (entity) and data (entity) and formalize describe of leash regular. The data model regulates data content, data frame, data action and data meaning. The data model is set up for user according to geological survey data and practice. On the bases above, the geological survey information classify and coding rule are set up (including geological essential coding rule, graphic element, basic designation coding and graphic layer document naming rule).
②Integration organize and manage of data
Based on the data above, basic data data-base and special data-base are set up, including basic data graphic layer 32 and special graphic layer 21.
③Integration deal with data
The data processing is one of the core segment of Integration organize and manage of data which are manly consolidate data Punjabi and expression of province node, meet border of graphic layer in different provinces and meet graphic layer dispose in different.
④Node arrange and issue
The node arrange of NGSIG are manly distributed in Beijing, six centers of great section (Tianjing, Nanjing, Shengyang, Yichang, Chengdou and Xian) 15 provinces geological survey yard. The demonstration borough in this paper is manly arranged bodes in Jiangsu, Anhui, Jiangxi and Hubei provinces.
The issue and enroll of data are achieved by each node passing SIG node client end tool software, which are manly record data to SIG node server(among them,53 graphic layer of Jiangsu,51 graphic layer of Anhui,52 graphic layer of Jiangxi and 52 graphic layer of Hubei) and data enroll becoming available data of NGSIG.
(2) Geological structure study and synthetically geological information drawing
Ore-forming geological structure study is the shoe pinches of forecast technology of deposit model synthetically geological information to resolve information non-equivalence between geological construction information and mineral resource forecast and to realize fine forecast by compiling sediment construct old structure map, magmatic structural map and earth structure graph map.
According to the metallogenic theory of Cheng yu-chuan combined with correlation require of Forecast technology of deposit model synthetically geological information, the magmatic structural map and earth structure graph map are compiling. At the same time, we are compiling early-middle Trias sediment construct old structure map, middle-late Permian period Dalong-Changxin sediment construct old structure map, middle-late Permian period Gufeng-Wuxue sediment construct old structure map, middle-late Permian period Longtan-wujiapin sediment construct old structure map, middle-late Permian period Qixia sediment construct old structure map and middle-late Carboniferous-early Permian period sediment construct old structure map with the copper object layer.
(3) Marker for predicting foundation and choice
Marker for predicting foundation and parameter choice confirmed base on exploration model. Ascertain of Marker for predicting foundation and parameter choice confirmed by ore-controlling factors and regional representative.
According to the principle above,12 markers for predicting are set up by different method and means.
Stratum:Trias, Permian, Carboniferous and Silurian;
Magma:mostly Yanshanian intermediate-acidic rocks, as quartz monzodiorite porphyrite, quartz monzodiorite and porphyritic quartz monzodiorite;
Sediment construct:middle Trias, middle-late Permian period Dalong-Changxin, middle-late Permian period Gufeng-Wuxue, middle-late Permian period Longtan-wujiapin, middle-late Permian period Qixia and middle-late Carboniferous-early Permian period six sediment construct
Physical exploration:physical exploration concluded structure, gravity anomaly, aeromagnetic anomaly and Concealed Rock Mass.
Geochemical exploration:single element anomaly of Cu、Pb、Zn、Au;
Remote sensing:linearity and ring structure by remote sensing interpretation.
According to the study above, we introduce finally online evidence right based on SIG to forecast evaluation of middle-lower of Changjiang river demonstration and to get correspond results. The 18 representative modeling deposits all exist in forecast section finding new region recognized by experts.
As mentioned above, the mineral resources evaluation method of middle-lower Changjiang river have stability theory base and adult technology based on SIG and late roof of NGISG supported by practicality data of four provinces in middle-lower Changjiang river and finally online evidence right. The system of forecast technology of deposit model synthetically geological information is set up by study and process practice. The forecast result may treat as an external result and an exact result based on system info driving by model data (impersonality, expert knowledge and basic theory).
The study have quite important sense for mineral resources evaluation technology and method:①The apace information grid establishing and application provide a new thought and approach to resolve availably distributing data and integration organize and manage of data means and approach, and to protect advantage of data manufacture. Information grid is development artery of future internet information technology. The space information grid would be current of geological information-based.②The forecast technology system of deposit model synthetically geological information put forward and foundation settle availably conquer disjoint between geological constitution information and mineral resources and information non-equivalence between model field and forecast field to come true fine forecast by new thought and technology. Now the method is application in the item< The important mineral resources potential evaluation and colligate> of geological survey bureau of China providing favorable theory base and method gist.
引文
[1]陈毓川.矿产资源展望与西部大开发[J].地球科学与环境学报.2006,28(1)：1-4。
[2]赵鹏大.当代矿产资源勘查评价的理论和方法[M].地震出版社.1999,283-292。
[3]陈建平,张寿廷,汤军等.非传统矿产资源定量预测的理论思考[J].地球物理学进展,2002,17(2)：342-347.
[4]叶天竺等.固体矿产预测评价技术方法[M].北京：中国地大出版社,2004。
[5]肖克炎,张晓华,王四龙等.矿产资源GIS评价系统[M].北京：地质出版社.2000.1-3。
[6]朱裕生.矿产资源潜力评价在我国的发展[J].中国地质,1999,270(20)：31-33.
[7]薛顺荣,胡光道,丁俊.成矿预测研究现状及发展趋势[J].云南地质,2001,20(4)：411-416
[8]朱裕生.矿产预测方法学导论(M).北京：地质出版社,1984.
[9]BOTBOL J M. An Application of Characteristic Analysis to Mineral Exploration [J]. Procgth Int,1971.
[10]Bonham-Carter G. f., Chung C. f. Integration of mineral resources data for Kasmere Lake area, Northwest Manitoba, with emphasis on uranium[J]. Computer & Geosciences 15.1983.25-45
[11]Bonham-Carter G. f, Agterberg F. P., Wright D.F.. Integration of geological datasets for gold exploration in Nova Scotia [J]. Photogrammertric Engineering and Remote Sensing,54(11).1988.1585-1592
[12]Bonham-Carter. G.F., Agterberg. F. P and Wright. D. F. Weights of Evidence Modeling:A New Approach to Mapping mineral potential [A]. In Ag terberg. F. P and Bonham-Carter.G. F. Statistical Applications in the Earth Sciences:Geol [C]. Survey of Canada Paper.1990.171-183.
[13]Agterberg. F. P. Computer Programs for Mineral Exploration [J]. Science.1989. 245:76-81.
[14]F. P. Agterberg, G.F. Bonham-Carter, Q. Cheng etal. Weights of Evidence Modeling and Weighted Logistic Regression for Mineral Potential Mapping [A]. In:Davis. J. C. and Herzfeld. U. C. (eds.). Computers in Geology,25 Years of Progress [C]. London:Oxford University Press,1993.13-32.
[15]Campbell A. N., Holloster V. f., Duda R.0.. Recognition of a hidden mineral deposits by an artificial intelligence program. Science.1982.217(3):929-972
[16]Burrough P. A. Principles of Geographical Information Systems for land resources assessment. Oxford:Oxford University Press.1982
[17]赵鹏大,”三联式”资源定量预测与评价—数字找矿理论与实践探讨[J].地球科学,2002年第05期.
[18]赵鹏大、胡旺亮,地质异常理论与矿产预测,新疆第二届天山地质矿产讨论会论文集,1991,241-248
[19]王世称,陈永良,夏立显.综合信息矿产预测理论与方法[M].北京：科学出版社.2000.
[20]徐道一等.数学地质引论[M].北京：地质出版社,1977.
[21]刘承祚. 地质专家系统与成矿预测(M).当代矿产资源勘查评价的理论与方法,北京：地震出版社,1999.
[22]李新中、赵鹏大、胡光道.基于规则知识表示的模型单元选择专家系统的实现(J).地球科学——中国地质大学学报,1995,20(2)：173-178.
[23]王世称、叶水盛等.综合信息成矿系列预测专家系统(M).长春出版社,1999.
[24]美国国家空间数据基础设施计划.ACSM Bulletin.1999.7.8
[25]美国地质调查局,美国本土矿产资源评价计划系列报告之一(M).地理信息系统及其在地学领域中的应用译文集,地矿部科技司计算机办公室,1993.
[26]美国地质调查局,美国本土矿产资源评价计划系列报告之二(M).地理信息系统及其在地学领域中的应用译文集,地矿部科技司计算机办公室,1993.
[27]G. F. Bonham, F. P. Agterberg, D. F. Wright. Nova Scotia地区金矿勘探地质资料的综合利用(M).地理信息系统及其在地学领域中的应用译文集,地矿部科技司计算机办公室,1993.
[28]G.P.Watson, A. N. Rencz, G. F. Bonham, Geographic information system are being applied to mineral re-source assessment in Northern New Brunswick (J). GEOS 1989,18(1).
[29]Lesley Wyborn et all. Using GIS for mineral potential evalution in Areas with few know mineral occurences (J). The second forum on GIS in the geosciences, AGSO,1995,199-211.
[30]Lyle A.Burgess, Recent applications and research into mineral prospective mapping using GIS (J). Proceeding of third national forum on GIS in the geosciences, AGSO,1997,121-129.
[31]C. M. Knox-Robinson, L.A. I. Wyborn, Towards a holistic exploration strategy Using geographic information systems as a tool to enhance exploration (J) Australian journal of earth sciences,1997,44:453-463.
[32]胡光道,陈建国.金属矿产资源评价分析系统设计[J].地质科技情报,1998,17(1)：45-49.
[33]池顺都、周顺平、吴新林.GIS支持下的地质异常分析及金属矿产经验预测(J).地球科学—中国地质大学学报,1997,22(1)：99-103.
[34]池顺都、赵鹏大、刘粤湘.应用GIS研究矿产资源潜力—以云南澜沧江流域为例(J).地球科学—中国地质大学学报,1999,24(5)：493-497.
[35]肖克炎张晓华. “区域矿产资源综合信息评价系统(MRAS)培训班”获得圆满成功[J].矿床地质,2003,22(4),376
[36]向运川,任天祥,杨竹溪.开发利用地理信息系统(GIS)综合分析地学信息进行矿产预测[J].物探与化探,1996,20(1)：1-13.
[37]陈述彭,鲁学军,周成虎.地理信息系统导论[M].北京：科学出版社,2000.1-240.
[38]陈小云,胡光道.GIS在矿产资源预测中的现状和研究思路[J].资源环境与工程,2006,20(1)：56-59
[39]李德仁,朱欣焰,龚健雅.从数字地图到空间信息网格—空间信息多级网格理论思考[J].武汉大学学报.2003,28(6)：642-649.
[40]肖志坚,左爱利,班宜忠等.矿产资源评价的新探索[J].地质与勘探,2006,42(3)：86-90.
[41]F. P. Agterberg and Qiuming Cheng. Conditional Independence Test for Weights-of-Evidence Modeling [J]. Natural Resources Research,2002,11(4): 249-255.
[42]杜鹃,关泽群.空间信息网格的框架体系和关键技术[J].地理空间信息.2005,3(2)：27-29.
[43]骆剑承,周成虎,蔡少华等.基于中间件技术的网格GIS体系结构[J].地球信息科学,2002,(3)：17-25
[44]Foster I, Kesselman C, Tuecke S. The Anatomy of theGrid:Enabling Scalable Virtual Organizations. International Journal Supercomputer Applications, 2001,15 (3):200-222
[45]Ian Foster, Carl Kesselman.网格计算(第二版)[M].北京：电子工业出版社,2005：35-106.
[46]董立平,陈丽萍.网格计算技术研究动向[J].高性能计算技术,2005,17(2)：74-78.
[47]I. Foster, C. Kesselman. The Grid:Blueprint for a Future Computing Infrastructure. San Francisco.USA:Morgan Kaufmann Publishers.1999.
[48]Guting R H.An Introduction to Spatial Database System[A]. VLDB Journal. Special issue on Spatial Database System[C]. Santiago de Chile, Chile,1994,3 (4):357-399.
[49]Gong J Y Foundation of Geographical Information System[M]. Beijing:Science Press,2001.
[50]Foster I, Kesselman C, Nick J M, et al. The Physiology of the Grid:An Open Grid Services Architecture for Distributed Systems Integration [R].2002.
[51]A Chervenak, I Foster et al. The data grid:Towards an architecture for the distributed management and analysis of large scientific datasets. Journal of Network and Computer Applications,2001,23:187-200.
[52]K Czajkowski,S Fitzgerald, I Foster et al. Grid information service for distributed resource sharing. In:Proc of the 10th IEEE Intl Symp on High-Performance Distributed Computer (hpdc-10). San Francisco: IEEEPress,2001.
[53]World Wide Web Consortium. Web Services Architecture, Draft 14[R].2002.
[54]Buehler K, Mckee L. The OpenGIS Guide:An introduction to Iteroperable Geoprocessing and the OpenGIS Specification [M]. Wayland. USA:OpenGIS Consortium Inc.1998.
[55]OpenGIS Abstract Specification, OpenGIS Consortium, version4.2[S].2001. http://www. opengis. org.
[56]OpenGIS Consortium. The OpenGIS Abstract Specification Topic 0:Abstract Specification Overview, version 4.0[R].1999.
[57]钟志农,李军,景宁等.数字图书馆中地理信息系统的设计与实现[J].国防科技大学学报.2002,24(6)：87-90.
[58]国家高技术研究发展计划(863计划).基于SIG的资源环境空间信息共享与应用服务研究报告[R].北京：2005,
[59]唐宇,陈荦,何凯涛等.空间信息栅格SIG框架体系与关键技术研究[J].遥感学报,2004,8(5)：425-433。
[60]Data Grid Requirements specification (EO application requirements for grid)[R].EO WP9,2001
[61]叶天竺,肖克炎,严光生.矿床模型综合地质信息预测技术研究[J].地学前缘,2007,14(5)：11-19.
[62]肖克炎,张晓华,李景朝等.全国重要矿产总量预测方法[J].地学前缘,2007,14(5)：20-26
[63]叶天竺.空间信息网格及其在地质工作中的应用.地球信息科学,2006,8(4)：4-7.
[64]S Tuecke, K Czajkowski, I Foster, et al. Open Grid Service Infrastructure (OGSI) Version 1.0[R].2003.
[65]Foster I,Kesseleman C,Nick J M. Grid services for distributed systems integration[C]. IEEE Computer,2002,35 (6):37-46.
[66]于雷易.GIS网格体系结构探讨[J].武汉大学学报,2004.29(2)：153-156.
[67]Karl Czajkowski, Donald F Ferguson, Ian Foster, et al. From Open Grid Service Infrastructure to WS-Resource Framework:Refactoring & Evolution Version 1.0[R].Globus Alliance,2004.
[68]Karl Czajkowski, Donald F Ferguson, Ian Foster, et al. The WS-Resource Framework Version 1.0[R].Globus Alliance,2004.
[69]Ian Foster, Carl Kesselman. The Grid 2:Blueprint for a New Computing Infrastructure Morgan Kaufmann.2006.
[70]朱民,张德贤.网格体系结构综述[J].网络安全技术与应用,2009-02：69-71.
[71]唐宇,何凯涛,肖侬等.国家地质调查应用网格体系及关键技术研究[J].计算机研究与发展,2003,40(12)：1682-1688。
[72]肖志坚,左爱利,班宜忠等.基于SIG框架下的矿产资源评价[J].地质通报,2006,25(5)：630-638.
[73]李超岭,李丰丹,罗显刚. 国家地质空间信息网格结点计算池构架及其实现[J].国土资源信息化,2006(6)：1-8.
[74]李丰丹,李超岭,罗显刚等.分布式空间数据注册容器的设计与实现[J].计算机工程,2008,34(16)：274-276
[75]李丰丹,李超岭,李浩川等.地质空间信息元数据服务模式的实现[J].地质通报,2008,27(5)：700-707.
[76]Singer D A. Basic concepts in there-part quantitative assessments of undiscovered mineral resources [J]. Nonrenewable Resources,1993,2 (2): 69-81.
[77]Agterberg F P, Bonham-Carter G F, Cheng Q M, et al. Weights of evidence modeling and weighted logistic regression for mineral potential mapping[A], in Davis, J. C., and Herzfeld, U. C., Computers in Geology-25 Years of Progress:Oxford Univ. Press[C], New York,1993.13-32.
[78]成秋明.非线性成矿预测理论：多重分形奇异性-广义自相似性-分形谱系模型与方法[J].地球科学—中国地质大学学报,2006.31(3)：337-346.
[79]Cheng Yuqi.Chen Yuchuan and Zhao Yiming. Preliminary discussion on the problems of minerogenetic series of mineral deposits (in Chinese, with English abstract), Bull. Chinese Acad. Geol., Sc.,1979,1 (1)
[80]程裕淇,陈毓川,赵一鸣等.初论矿床的成矿系列问题[J].中国地质科学院院报,1979,1(1)：32-58.
[81]程裕淇,陈毓川,赵一鸣,等.再论矿床的成矿系列问题[J].中国地质科学院院报,1983,(6)：1-52.
[82]陈毓川,薛春纪,王登红等.华北陆块北缘区域矿床成矿谱系探讨[J].高校地质学报,2003,9(4),520-235.
[83]朱裕生.矿产预测理论—区域成矿学向矿产勘查延伸的理论体系[J].地质学报,2006,80(10),1518-1527.
[84]翟裕生.论成矿系统[J].地学前缘,1999,6(3)：13-27.
[85]陈毓川.矿床的成矿系列[J].地学前缘,1994,1(3)：90-99.
[86]王登红,陈毓川,徐志刚等.阿尔泰成矿省的成矿系列及成矿规律研究[M].北京：原子能出版社,2002,493.
[87]翟裕生,等.成矿系列研究[M].武汉：中国地质大学出版社,1996.
[88]陈毓川,裴荣富,宋天锐等.中国矿床成矿系列初论[M].北京：地质出版社,1998：20-100.
[89]王世称,陈永良,严光生等.大型、超大型金矿床综合信息成矿远景预测方法研究[M].北京：地震出版社,1998.
[90]王世称,陈永良.初论基于数字地球技术系统的巨型矿床统计评价[J].地球科学—中国地质大学学报,2001,26(2),157-160.
[91]赵鹏大,池顺都.初论地质异常[J].地球科学,1991,16(3)：241-248.
[92]赵鹏大,陈永清.地质异常矿体定位的基本途径[J].地球科学—中国地质大学学报,1998,23(2)：111-114.
[93]ZHAO Pengda, CHEN Jianping, CHEN Jianguo, et al. Introduction to "Three-step" Digital Mineral Prospecting and assessment [A]. Proceedings of the International Symposium[C].2001:1-5.
[94]Zhao P D, Chen J P, Zhang S T, et al. Mineral deposit s:geological anomalies wit h high economic value [C]//Cheng Q, Bonham2Carter G. Proceedings of IAMG 05,2005:1022-1027.
[95]ZHAO Pengda, CHEN Jianping, CHEN Jianguo, et al. Introduction to "Three-step" Digital Mineral Prospecting and assessment [A]. Proceedings of the International Symposium[C].2001,27(5):139-148.
[96]翟裕生.论成矿系统[J].地学前缘,1999,6(1)：13-26.
[97]谢学锦,用新观念与新技术寻找巨型矿床,科学中国人,1995,No.5。
[98]Xie Xuejing. Surfacial and superimposed geochemical exploration for giant ore deposits. Clark, A. H. (editor), Giant ore deposits II, Kingston, Canada, 1995, P475-485.
[99]李超岭,张克信,于庆文等.数字填图中不同阶段数据模型的继承技术[J].地球科学———中国地质大学学报.2004,29(6)：745-752.
[100]张庆合.基于SIG的地质图空间数据共享与服务[J].勘探地球物理进展.2006,29(1)：56-61.
[101]陈毓川主编.中国主要成矿区(带)矿产资源远景评价.北京：地质出版社,1999.
[102]陈毓川,朱裕生等.中国矿床成矿模式.地质出版社,1993,北京.
[103]徐善法,陈建平,叶继华.证据权法在三江北段铜金矿床成矿预测中的应用研究[J].地质与勘探,2006,42(2)：54-59.
[104]陈毓川等.中国主要成矿区带矿产资源远景评价[M].北京：地质出版社.1999.
[105]常印佛等.安徽沿江地区铜金多金属矿床地质[M].北京：地质出版社.1998.
[2]赵鹏大.当代矿产资源勘查评价的理论和方法[M].地震出版社.1999,283-292。
[3]陈建平,张寿廷,汤军等.非传统矿产资源定量预测的理论思考[J].地球物理学进展,2002,17(2)：342-347.
[4]叶天竺等.固体矿产预测评价技术方法[M].北京：中国地大出版社,2004。
[5]肖克炎,张晓华,王四龙等.矿产资源GIS评价系统[M].北京：地质出版社.2000.1-3。
[6]朱裕生.矿产资源潜力评价在我国的发展[J].中国地质,1999,270(20)：31-33.
[7]薛顺荣,胡光道,丁俊.成矿预测研究现状及发展趋势[J].云南地质,2001,20(4)：411-416
[8]朱裕生.矿产预测方法学导论(M).北京：地质出版社,1984.
[9]BOTBOL J M. An Application of Characteristic Analysis to Mineral Exploration [J]. Procgth Int,1971.
[10]Bonham-Carter G. f., Chung C. f. Integration of mineral resources data for Kasmere Lake area, Northwest Manitoba, with emphasis on uranium[J]. Computer & Geosciences 15.1983.25-45
[11]Bonham-Carter G. f, Agterberg F. P., Wright D.F.. Integration of geological datasets for gold exploration in Nova Scotia [J]. Photogrammertric Engineering and Remote Sensing,54(11).1988.1585-1592
[12]Bonham-Carter. G.F., Agterberg. F. P and Wright. D. F. Weights of Evidence Modeling:A New Approach to Mapping mineral potential [A]. In Ag terberg. F. P and Bonham-Carter.G. F. Statistical Applications in the Earth Sciences:Geol [C]. Survey of Canada Paper.1990.171-183.
[13]Agterberg. F. P. Computer Programs for Mineral Exploration [J]. Science.1989. 245:76-81.
[14]F. P. Agterberg, G.F. Bonham-Carter, Q. Cheng etal. Weights of Evidence Modeling and Weighted Logistic Regression for Mineral Potential Mapping [A]. In:Davis. J. C. and Herzfeld. U. C. (eds.). Computers in Geology,25 Years of Progress [C]. London:Oxford University Press,1993.13-32.
[15]Campbell A. N., Holloster V. f., Duda R.0.. Recognition of a hidden mineral deposits by an artificial intelligence program. Science.1982.217(3):929-972
[16]Burrough P. A. Principles of Geographical Information Systems for land resources assessment. Oxford:Oxford University Press.1982
[17]赵鹏大,”三联式”资源定量预测与评价—数字找矿理论与实践探讨[J].地球科学,2002年第05期.
[18]赵鹏大、胡旺亮,地质异常理论与矿产预测,新疆第二届天山地质矿产讨论会论文集,1991,241-248
[19]王世称,陈永良,夏立显.综合信息矿产预测理论与方法[M].北京：科学出版社.2000.
[20]徐道一等.数学地质引论[M].北京：地质出版社,1977.
[21]刘承祚. 地质专家系统与成矿预测(M).当代矿产资源勘查评价的理论与方法,北京：地震出版社,1999.
[22]李新中、赵鹏大、胡光道.基于规则知识表示的模型单元选择专家系统的实现(J).地球科学——中国地质大学学报,1995,20(2)：173-178.
[23]王世称、叶水盛等.综合信息成矿系列预测专家系统(M).长春出版社,1999.
[24]美国国家空间数据基础设施计划.ACSM Bulletin.1999.7.8
[25]美国地质调查局,美国本土矿产资源评价计划系列报告之一(M).地理信息系统及其在地学领域中的应用译文集,地矿部科技司计算机办公室,1993.
[26]美国地质调查局,美国本土矿产资源评价计划系列报告之二(M).地理信息系统及其在地学领域中的应用译文集,地矿部科技司计算机办公室,1993.
[27]G. F. Bonham, F. P. Agterberg, D. F. Wright. Nova Scotia地区金矿勘探地质资料的综合利用(M).地理信息系统及其在地学领域中的应用译文集,地矿部科技司计算机办公室,1993.
[28]G.P.Watson, A. N. Rencz, G. F. Bonham, Geographic information system are being applied to mineral re-source assessment in Northern New Brunswick (J). GEOS 1989,18(1).
[29]Lesley Wyborn et all. Using GIS for mineral potential evalution in Areas with few know mineral occurences (J). The second forum on GIS in the geosciences, AGSO,1995,199-211.
[30]Lyle A.Burgess, Recent applications and research into mineral prospective mapping using GIS (J). Proceeding of third national forum on GIS in the geosciences, AGSO,1997,121-129.
[31]C. M. Knox-Robinson, L.A. I. Wyborn, Towards a holistic exploration strategy Using geographic information systems as a tool to enhance exploration (J) Australian journal of earth sciences,1997,44:453-463.
[32]胡光道,陈建国.金属矿产资源评价分析系统设计[J].地质科技情报,1998,17(1)：45-49.
[33]池顺都、周顺平、吴新林.GIS支持下的地质异常分析及金属矿产经验预测(J).地球科学—中国地质大学学报,1997,22(1)：99-103.
[34]池顺都、赵鹏大、刘粤湘.应用GIS研究矿产资源潜力—以云南澜沧江流域为例(J).地球科学—中国地质大学学报,1999,24(5)：493-497.
[35]肖克炎张晓华. “区域矿产资源综合信息评价系统(MRAS)培训班”获得圆满成功[J].矿床地质,2003,22(4),376
[36]向运川,任天祥,杨竹溪.开发利用地理信息系统(GIS)综合分析地学信息进行矿产预测[J].物探与化探,1996,20(1)：1-13.
[37]陈述彭,鲁学军,周成虎.地理信息系统导论[M].北京：科学出版社,2000.1-240.
[38]陈小云,胡光道.GIS在矿产资源预测中的现状和研究思路[J].资源环境与工程,2006,20(1)：56-59
[39]李德仁,朱欣焰,龚健雅.从数字地图到空间信息网格—空间信息多级网格理论思考[J].武汉大学学报.2003,28(6)：642-649.
[40]肖志坚,左爱利,班宜忠等.矿产资源评价的新探索[J].地质与勘探,2006,42(3)：86-90.
[41]F. P. Agterberg and Qiuming Cheng. Conditional Independence Test for Weights-of-Evidence Modeling [J]. Natural Resources Research,2002,11(4): 249-255.
[42]杜鹃,关泽群.空间信息网格的框架体系和关键技术[J].地理空间信息.2005,3(2)：27-29.
[43]骆剑承,周成虎,蔡少华等.基于中间件技术的网格GIS体系结构[J].地球信息科学,2002,(3)：17-25
[44]Foster I, Kesselman C, Tuecke S. The Anatomy of theGrid:Enabling Scalable Virtual Organizations. International Journal Supercomputer Applications, 2001,15 (3):200-222
[45]Ian Foster, Carl Kesselman.网格计算(第二版)[M].北京：电子工业出版社,2005：35-106.
[46]董立平,陈丽萍.网格计算技术研究动向[J].高性能计算技术,2005,17(2)：74-78.
[47]I. Foster, C. Kesselman. The Grid:Blueprint for a Future Computing Infrastructure. San Francisco.USA:Morgan Kaufmann Publishers.1999.
[48]Guting R H.An Introduction to Spatial Database System[A]. VLDB Journal. Special issue on Spatial Database System[C]. Santiago de Chile, Chile,1994,3 (4):357-399.
[49]Gong J Y Foundation of Geographical Information System[M]. Beijing:Science Press,2001.
[50]Foster I, Kesselman C, Nick J M, et al. The Physiology of the Grid:An Open Grid Services Architecture for Distributed Systems Integration [R].2002.
[51]A Chervenak, I Foster et al. The data grid:Towards an architecture for the distributed management and analysis of large scientific datasets. Journal of Network and Computer Applications,2001,23:187-200.
[52]K Czajkowski,S Fitzgerald, I Foster et al. Grid information service for distributed resource sharing. In:Proc of the 10th IEEE Intl Symp on High-Performance Distributed Computer (hpdc-10). San Francisco: IEEEPress,2001.
[53]World Wide Web Consortium. Web Services Architecture, Draft 14[R].2002.
[54]Buehler K, Mckee L. The OpenGIS Guide:An introduction to Iteroperable Geoprocessing and the OpenGIS Specification [M]. Wayland. USA:OpenGIS Consortium Inc.1998.
[55]OpenGIS Abstract Specification, OpenGIS Consortium, version4.2[S].2001. http://www. opengis. org.
[56]OpenGIS Consortium. The OpenGIS Abstract Specification Topic 0:Abstract Specification Overview, version 4.0[R].1999.
[57]钟志农,李军,景宁等.数字图书馆中地理信息系统的设计与实现[J].国防科技大学学报.2002,24(6)：87-90.
[58]国家高技术研究发展计划(863计划).基于SIG的资源环境空间信息共享与应用服务研究报告[R].北京：2005,
[59]唐宇,陈荦,何凯涛等.空间信息栅格SIG框架体系与关键技术研究[J].遥感学报,2004,8(5)：425-433。
[60]Data Grid Requirements specification (EO application requirements for grid)[R].EO WP9,2001
[61]叶天竺,肖克炎,严光生.矿床模型综合地质信息预测技术研究[J].地学前缘,2007,14(5)：11-19.
[62]肖克炎,张晓华,李景朝等.全国重要矿产总量预测方法[J].地学前缘,2007,14(5)：20-26
[63]叶天竺.空间信息网格及其在地质工作中的应用.地球信息科学,2006,8(4)：4-7.
[64]S Tuecke, K Czajkowski, I Foster, et al. Open Grid Service Infrastructure (OGSI) Version 1.0[R].2003.
[65]Foster I,Kesseleman C,Nick J M. Grid services for distributed systems integration[C]. IEEE Computer,2002,35 (6):37-46.
[66]于雷易.GIS网格体系结构探讨[J].武汉大学学报,2004.29(2)：153-156.
[67]Karl Czajkowski, Donald F Ferguson, Ian Foster, et al. From Open Grid Service Infrastructure to WS-Resource Framework:Refactoring & Evolution Version 1.0[R].Globus Alliance,2004.
[68]Karl Czajkowski, Donald F Ferguson, Ian Foster, et al. The WS-Resource Framework Version 1.0[R].Globus Alliance,2004.
[69]Ian Foster, Carl Kesselman. The Grid 2:Blueprint for a New Computing Infrastructure Morgan Kaufmann.2006.
[70]朱民,张德贤.网格体系结构综述[J].网络安全技术与应用,2009-02：69-71.
[71]唐宇,何凯涛,肖侬等.国家地质调查应用网格体系及关键技术研究[J].计算机研究与发展,2003,40(12)：1682-1688。
[72]肖志坚,左爱利,班宜忠等.基于SIG框架下的矿产资源评价[J].地质通报,2006,25(5)：630-638.
[73]李超岭,李丰丹,罗显刚. 国家地质空间信息网格结点计算池构架及其实现[J].国土资源信息化,2006(6)：1-8.
[74]李丰丹,李超岭,罗显刚等.分布式空间数据注册容器的设计与实现[J].计算机工程,2008,34(16)：274-276
[75]李丰丹,李超岭,李浩川等.地质空间信息元数据服务模式的实现[J].地质通报,2008,27(5)：700-707.
[76]Singer D A. Basic concepts in there-part quantitative assessments of undiscovered mineral resources [J]. Nonrenewable Resources,1993,2 (2): 69-81.
[77]Agterberg F P, Bonham-Carter G F, Cheng Q M, et al. Weights of evidence modeling and weighted logistic regression for mineral potential mapping[A], in Davis, J. C., and Herzfeld, U. C., Computers in Geology-25 Years of Progress:Oxford Univ. Press[C], New York,1993.13-32.
[78]成秋明.非线性成矿预测理论：多重分形奇异性-广义自相似性-分形谱系模型与方法[J].地球科学—中国地质大学学报,2006.31(3)：337-346.
[79]Cheng Yuqi.Chen Yuchuan and Zhao Yiming. Preliminary discussion on the problems of minerogenetic series of mineral deposits (in Chinese, with English abstract), Bull. Chinese Acad. Geol., Sc.,1979,1 (1)
[80]程裕淇,陈毓川,赵一鸣等.初论矿床的成矿系列问题[J].中国地质科学院院报,1979,1(1)：32-58.
[81]程裕淇,陈毓川,赵一鸣,等.再论矿床的成矿系列问题[J].中国地质科学院院报,1983,(6)：1-52.
[82]陈毓川,薛春纪,王登红等.华北陆块北缘区域矿床成矿谱系探讨[J].高校地质学报,2003,9(4),520-235.
[83]朱裕生.矿产预测理论—区域成矿学向矿产勘查延伸的理论体系[J].地质学报,2006,80(10),1518-1527.
[84]翟裕生.论成矿系统[J].地学前缘,1999,6(3)：13-27.
[85]陈毓川.矿床的成矿系列[J].地学前缘,1994,1(3)：90-99.
[86]王登红,陈毓川,徐志刚等.阿尔泰成矿省的成矿系列及成矿规律研究[M].北京：原子能出版社,2002,493.
[87]翟裕生,等.成矿系列研究[M].武汉：中国地质大学出版社,1996.
[88]陈毓川,裴荣富,宋天锐等.中国矿床成矿系列初论[M].北京：地质出版社,1998：20-100.
[89]王世称,陈永良,严光生等.大型、超大型金矿床综合信息成矿远景预测方法研究[M].北京：地震出版社,1998.
[90]王世称,陈永良.初论基于数字地球技术系统的巨型矿床统计评价[J].地球科学—中国地质大学学报,2001,26(2),157-160.
[91]赵鹏大,池顺都.初论地质异常[J].地球科学,1991,16(3)：241-248.
[92]赵鹏大,陈永清.地质异常矿体定位的基本途径[J].地球科学—中国地质大学学报,1998,23(2)：111-114.
[93]ZHAO Pengda, CHEN Jianping, CHEN Jianguo, et al. Introduction to "Three-step" Digital Mineral Prospecting and assessment [A]. Proceedings of the International Symposium[C].2001:1-5.
[94]Zhao P D, Chen J P, Zhang S T, et al. Mineral deposit s:geological anomalies wit h high economic value [C]//Cheng Q, Bonham2Carter G. Proceedings of IAMG 05,2005:1022-1027.
[95]ZHAO Pengda, CHEN Jianping, CHEN Jianguo, et al. Introduction to "Three-step" Digital Mineral Prospecting and assessment [A]. Proceedings of the International Symposium[C].2001,27(5):139-148.
[96]翟裕生.论成矿系统[J].地学前缘,1999,6(1)：13-26.
[97]谢学锦,用新观念与新技术寻找巨型矿床,科学中国人,1995,No.5。
[98]Xie Xuejing. Surfacial and superimposed geochemical exploration for giant ore deposits. Clark, A. H. (editor), Giant ore deposits II, Kingston, Canada, 1995, P475-485.
[99]李超岭,张克信,于庆文等.数字填图中不同阶段数据模型的继承技术[J].地球科学———中国地质大学学报.2004,29(6)：745-752.
[100]张庆合.基于SIG的地质图空间数据共享与服务[J].勘探地球物理进展.2006,29(1)：56-61.
[101]陈毓川主编.中国主要成矿区(带)矿产资源远景评价.北京：地质出版社,1999.
[102]陈毓川,朱裕生等.中国矿床成矿模式.地质出版社,1993,北京.
[103]徐善法,陈建平,叶继华.证据权法在三江北段铜金矿床成矿预测中的应用研究[J].地质与勘探,2006,42(2)：54-59.
[104]陈毓川等.中国主要成矿区带矿产资源远景评价[M].北京：地质出版社.1999.
[105]常印佛等.安徽沿江地区铜金多金属矿床地质[M].北京：地质出版社.1998.