数字地球及其对地震科学的影响

本文综述和探讨了数字地球概念的起源、内涵及其相关的关键技术,以及数字地球对地震科学发展的作用和影响。     

云南惠民铁矿遥感近矿找矿标志及成矿预测

分析总结惠民铁矿区赋矿地层惠民组火山岩、弧形构造内缘北西向构造交汇部位、铁染羟基异常等成矿、控矿条件的遥感影纹、色调等标志,根据矿化遥感异常信息圈定3处找矿远景地段。     

滇东北及毛坪铅锌矿遥感地质与成矿预测

根据遥感构造、含矿岩性地层、岩石蚀变异常等多种遥感地质信息,采用地质异常单元统计预测方法,对毛坪铅锌矿进行多元信息成矿预测,明确了找矿方向。     

数字城市:智能城市的初级阶段

针对国内外数字城市研究和建设中的主要问题,介绍了全球化进程中正在兴起和汇聚的新技术———物联网与传感器网络、空间信息网格等为数字城市的演进提供的可行性。提出数字城市的发展必然导向智能城市,并将数字城市作为智能城市的初级阶段进行重新诠释;提出为了适应数字城市向智能城市进化,数字城市系统的构建必须满足开放性、易拓展性、可重用性、可动态适应的智能性等特征。     

用信息通讯网络平台构筑灌溉管理新模式

随着信息化、网络化的进程不断加快,信息通信技术迅速普及,其对经济社会发展形成了具大的推动力,通信网络已成为经济发展的一种战略性资源和高科技手段,利用信息产业新技术、新业务、新成果和新服务做为灌溉管理工作的一个新平台,形成一个网络型、管理型、服务型的灌溉管理新体制,在灌溉管理上可拓宽管理服务区域,加快灌溉信息的传速和反馈,达到与农户的互动,加强灌溉情况的勾通。使灌溉管理单位和农户之间的沟通和联系越来越紧密。可以促进灌溉管理流程更加简便高效,提高灌溉管理效率,减少管理工作中间环节,降低灌溉管理成本,全面提高灌溉管理服务质量。利用通讯信息网络平台来组建灌溉管理组织,通过在灌区的试运行,管理单位与农户联系迅速,灌溉及时,费用降低,作用显著,应运效果好。信息化、网络化与水利灌溉管理工作的融合。对灌溉管理乃至水利工作的全面发展将具有深远的影响,     

乌拉山地区遥感蚀变信息提取研究

根据研究区蚀变岩在ETM图像上的光谱特征,利用比值增强、主成分分析及比值增强后主成分分析等方法,对内蒙古乌拉山地区蚀变岩信息进行增强,进而采用均值加标准差与最优密度分割相结合的方法对蚀变信息进行提取和分析。通过多层次的筛选和评估,划出真异常区,制作遥感异常图。     

江苏省矿业权监督管理信息系统开发与应用

针对目前矿业权监督管理的现状,梳理矿业权监督管理流程,建立矿业权监督管理的业务数据库与基础数据库,建立江苏省矿业权监督管理系统,使矿业权监督管理的全过程实现计算机化管理,达到规范管理工作、提高工作效率的目的。     

Non-Linear Theory and Power-Law Models for Information Integration and Mineral Resources Quantitative Assessments

Singular physical or chemical processes may result in anomalous amounts of energy release or mass accumulation that, generally, are confined to narrow intervals in space or time. Singularity is a property of different types of non-linear natural processes including cloud formation, rainfall, hurricanes, flooding, landslides, earthquakes, wildfires, and mineralization. The end products of these non-linear processes can be modeled as fractals or multifractals. Hydrothermal processes in the Earth’s crust can result in ore deposits characterized by high concentrations of metals with fractal or multifractal properties. Here we show that the non-linear properties of the end products of singular mineralization processes can be applied for prediction of undiscovered mineral deposits and for quantitative mineral resource assessment, whether for mineral exploration or for regional, national and global planning for mineral resource utilization. In addition to the general theory and framework for the non-linear mineral resources assessment, this paper focuses on several power-law models proposed for characterizing non-linear properties of mineralization and for geoinformation extraction and integration. The theories, methods, and computer system discussed in this paper were validated using a case study dealing with hydrothermal Au mineral potential in southern Nova Scotia, Canada.     

关于城市交通地理信息系统模型设计的思考与改进

GIS—T模型是建立城市交通地理信息系统的主体,本文对现有GIS—T模型进行了简单的分析与评价,并且为了增加政府与公众做出决策的正确性,提出了路径畅通可靠度模型、城市交通综合指数模型、交通出行指数模型三个数学模型,以达到量化城市交通与完善GIS—T模型的目的。     

A novel index to evaluate discretization methods:A case study of flood susceptibility assessment based on random forest

The selection of a suitable discretization method(DM)to discretize spatially continuous variables(SCVs)is critical in ML-based natural hazard susceptibility assessment.However,few studies start to consider the influence due to the selected DMs and how to efficiently select a suitable DM for each SCV.These issues were well addressed in this study.The information loss rate(ILR),an index based on the informa-tion entropy,seems can be used to select optimal DM for each SCV.However,the ILR fails to show the actual influence of discretization because such index only considers the total amount of information of the discretized variables departing from the original SCV.Facing this issue,we propose an index,infor-mation change rate(ICR),that focuses on the changed amount of information due to the discretization based on each cell,enabling the identification of the optimal DM.We develop a case study with Random Forest(training/testing ratio of 7:3)to assess flood susceptibility in Wanan County,China.The area under the curve-based and susceptibility maps-based approaches were presented to compare the ILR and ICR.The results show the ICR-based optimal DMs are more rational than the ILR-based ones in both cases.Moreover,we observed the ILR values are unnaturally small(＜1％),whereas the ICR values are obviously more in line with general recognition(usually 10％-30％).The above results all demonstrate the superiority of the ICR.We consider this study fills up the existing research gaps,improving the ML-based natural hazard susceptibility assessments.