Image Processing on Geological Data in Vector Format and Multi-Source Spatial Data Fusion

The geological data are constructed in vector format in geographical information system (GIS) while other data such as remote sensing images, geographical data and geochemical data are saved in raster ones. This paper converts the vector data into 8 bit images according to their importance to mineralization each by programming. We can communicate the geological meaning with the raster images by this method. The paper also fuses geographical data and geochemical data with the programmed strata data. The result shows that image fusion can express different intensities effectively and visualize the structure characters in 2 dimensions. Furthermore, it also can produce optimized information from multi-source data and express them more directly.

Multi-Source Spatial Data Distribution Model and System Implementation

The Multi-source spatial data distribution is based on WebGIS, and it is an important part of multi-source geographic information management system. a new multi-source spatial data distribution model is proposed on the basis of multisource data storage model and by combining existing map distribution technology, The author developed a multi-source spatial data distribution system which based on MapGIS K9 by using this model and taking full advantage of interfacecode separating thinking and high efficiency characteristic of .net, so high-speed distribution of multi-source spatial data realized.

A spatial decomposition approach for accelerating buffer analysis of vector data

Parallel vector buffer analysis approaches can be classified into 2 types:algorithm-oriented parallel strategy and the data-oriented parallel strategy.These methods do not take its applicability on the existing geographic information systems(GIS)platforms into consideration.In order to address the problem,a spatial decomposition approach for accelerating buffer analysis of vector data is proposed.The relationship between the number of vertices of each feature and the buffer analysis computing time is analyzed to generate computational intensity transformation functions(CITFs).Then,computational intensity grids(CIGs)of polyline and polygon are constructed based on the relative CITFs.Using the corresponding CIGs,a spatial decomposition method for parallel buffer analysis is developed.Based on the computational intensity of the features and the sub-domains generated in the decomposition,the features are averagely assigned within the sub-domains into parallel buffer analysis tasks for load balance.Compared with typical regular domain decomposition methods,the new approach accomplishes greater balanced decomposition of computational intensity for parallel buffer analysis and achieves near-linear speedups.

Spatial data mining system for ore-forming prediction

The authors designed the spatial data mining system for ore-forming prediction based on the theory and methods of data mining as well as the technique of spatial database,in combination with the characteristics of geological information data.The system consists of data management,data mining and knowledge discovery,knowledge representation.It can syncretize multi-source geosciences data effectively,such as geology,geochemistry,geophysics,RS.The system digitized geological information data as data layer files which consist of the two numerical values,to store these files in the system database.According to the combination of the characters of geological information,metallogenic prognosis was realized,as an example from some area in Heilongjiang Province.The prospect area of hydrothermal copper deposit was determined.

ArcGIS Data Reviewer在林业矢量数据质量管理中的应用

介绍ArcGIS Data Reviewer基本功能和特性,对其应用于林业地理信息矢量数据质量检查,如图斑重复、重叠,图斑间有间隙、多部件、狭长面、急锐角化、漏绘等空间关系,以及属性字段之间的逻辑性检查等的方法和步骤,举例进行了详细叙述,可为该软件模块的使用提供参考。

一种曲线数据压缩的自编码器神经网络方法

矢量空间数据的压缩是减少存储空间及节省网络传输带宽最直接有效的途径。本文利用自编码器神经网络构建了一种面向矢量曲线数据的压缩和解压模型。该模型针对不同规模和复杂度的曲线数据,首先进行分段和重采样处理进而规范化输入向量,然后通过优化自编码器结构和调整损失函数实现了高精度的压缩解码模块,最后通过弧段数据的坐标闭合差分配确保了数据的稳定性。对山西、湖南、江西3省的1∶100万县级弧段进行了压缩和还原试验,分析发现:数据还原精度随压缩率变小而变小,当压缩率小于35%后,数据还原精度呈波动趋势,25%为满足精度要求的适宜压缩率。比较傅里叶级数及贝塞尔曲线拟合方法发现本文模型压缩精度和处理速度在一定的压缩率范围内存在优势,同时该模型说明了深度学习在提取空间要素几何特征方面有一定的潜力。

顾及多级空间索引结构的矢量地图局部加密方法

随着地理信息产业的蓬勃发展,地图与各类生活服务深度融合,地图从专业化应用逐步走向大众化应用。大数据时代的到来,为地图数据的分发、共享、获取与动态更新等提供了极大便利,但伴随而来的是地图数据传输过程中面临的信息泄露、窃取等安全隐患问题也日益严峻。现有的矢量地图加密方法大多是在经典密码学算法基础上扩展而来,虽然已有加密方法考虑到矢量地图的特征,但是现有方法大多仍以整个地图或图层为加密单元,在用户需要访问某个局部的感兴趣区域时需要对整个地图文件或图层进行解密,对于矢量地图的按需局部加密仍未提出有效方案,还难以满足大数据时代地图按需用图、众包地图数据采集与云端更新等应用场景对矢量地图局部加密的应用需求。为此,本文从矢量地图的数据结构特点出发,提出了一种顾及多级空间索引的矢量地图局部加密方法。通过点、线、面不同矢量地图数据的加密试验分析,结果表明:①本文方法可以有效实现矢量地图的局部加解密;②相比于现有加密方法,本文方法采用局部加密策略,且支持多级分块并行加密,具有更高的加密效率;③本文针对不同加密单元采用不同加密参数,显著提高了加密算法的抗攻击能力。

ArcGIS中栅格数据矢量化在林草工作中的应用

ArcGIS软件在林草工作中的应用越来越广泛,ArcGIS软件提供了丰富的图形属性数据,通过使用ArcGIS的栅格数据矢量化功能,可以将需要的图形属性数据进行提取并形成矢量化结果。ArcGIS提供了强大的栅格数据矢量化功能,可以将需要的图形属性数据进行提取,并将其以栅格形式存储到ArcGIS中,这样可以使用户以简单易懂的方式获得需要的图形属性数据。目前在林草工作中使用最多的就是矢量数据和栅格数据混合使用,对于空间范围大、属性结构复杂、空间位置和属性重叠复杂的矢量数据,通过简单操作就可以得到空间关系清晰、位置准确和内容丰富的矢量结果。

矢量空间数据文档存储模型研究

针对海量空间数据量PB级数据存储的问题,分析No SQL数据库中分布式文件存储数据库在海量数据的存储和访问上的优势,分析基于分布式文件存储的数据库MongoDB的存储格式,研究矢量空间数据文档存储模型。针对矢量空间数据的点、线、多边形等几何形态,设计基于文档存储的矢量空间数据存储模型,实现了矢量空间数据在文档存储数据库MongoDB中的存储。针对矢量空间数据在文件存储数据库中的应用效率问题,提出未来工作将围绕文件存储数据库中矢量空间数据拓扑查询及查询效率展开。

基于特征补全的无线传感器网络异常数据流检测

由于节点所感知数据有缺失或者错误的情况,使异常数据流检测受困,导致检测准确率、漏报率和能耗等方面存在问题,因此,提出基于特征补全的无线传感器网络异常数据流检测方法。根据传感网络内数据流间的相关性,在特定环境内对缺失和错误数据进行估计与补全;从补全后的无线传感器网络数据流中抽取数据,并完成数据特征挖掘,为之后的异常数据流检测做好准备;使用支持向量机将正常数据和异常数据分隔,从而实现对无线传感器网络异常数据流检测。结果表明:特征补全后的无线传感器网络异常数据检测,其检测的准确率维持在99%以上,漏报率在0.3%以下,能耗下降率最高可达到35.87%,检测用时在0.8 s以下,具有准确率高、漏报率低、能耗少且用时短的优势。

基于Oracle Spatial的矢量空间数据管理机制

分析了基于Oracle Spatial的对象关系模型来存储和管理矢量空间数据的机制,包括其采用的数据模型、元数据管理机制、空间索引机制及查询机制,并在此基础之上给出了一个典型的基于Oracle Spatial创建和操作GIS空间数据库的实例.

面向大规模地理矢量线数据的多层级实时可视化技术

针对主流方法难以满足多层级实时可视化的需求,提出面向大规模地理矢量线数据的多层级实时可视化技术。建立面向多层级瓦片绘制的自适应可视化模型,设计像元四叉R(pixel quad R, PQR)树空间索引和基于PQR树的自适应可视化算法,分别用于支撑模型的数据组织和可视绘制。在10亿规模数据集上的实验表明:该技术在0.57 s内可计算任一层级上的可视结果,并且计算耗时大幅小于主流方法。当数据规模急剧增长时,该技术在各显示层级上仍具有较好的可视性能,最低可视速率超过100张/s,大幅优于主流方法。该技术在单机条件下即可支撑大规模地理矢量线数据的多层级实时可视化,在空间大数据探索分析领域具备较好的应用前景。

Effect of human settlements on urban thermal environment and factor analysis based on multi-source data:A case study of Changsha city

In view of the lack of comprehensive evaluation and analysis from the combination of natural and human multi-dimensional factors,the urban surface temperature patterns of Changsha in 2000,2009 and 2016 are retrieved based on multi-source spatial data(Landsat 5 and Landsat 8 satellite image data,POI spatial big data,digital elevation model,etc.),and 12 natural and human factors closely related to urban thermal environment are quickly obtained.The standard deviation ellipse and spatial principal component analysis(PCA)methods are used to analyze the effect of urban human residential thermal environment and its influencing factors.The results showed that the heat island area increased by 547 km~2 and the maximum surface temperature difference reached 10.1℃during the period 2000–2016.The spatial distribution of urban heat island was mainly concentrated in urban built-up areas,such as industrial and commercial agglomerations and densely populated urban centers.The spatial distribution pattern of heat island is gradually decreasing from the urban center to the suburbs.There were multiple high-temperature centers,such as Wuyi square business circle,Xingsha economic and technological development zone in Changsha County,Wangcheng industrial zone,Yuelu industrial agglomeration,and Tianxin industrial zone.From 2000 to 2016,the main axis of spatial development of heat island remained in the northeast-southwest direction.The center of gravity of heat island shifted 2.7 km to the southwest with the deflection angle of 54.9°in 2000–2009.The center of gravity of heat island shifted to the northeast by 4.8 km with the deflection angle of 60.9°in 2009–2016.On the whole,the change of spatial pattern of thermal environment in Changsha was related to the change of urban construction intensity.Through the PCA method,it was concluded that landscape pattern,urban construction intensity and topographic landforms were the main factors affecting the spatial pattern of urban thermal environment of Changsha.The promotion effect of human factors on the formation of heat island effect was obviously greater than that of natural factors.The temperature would rise by 0.293℃under the synthetic effect of human and natural factors.Due to the complexity of factors influencing the urban thermal environment of human settlements,the utilization of multi-source data could help to reveal the spatial pattern and evolution law of urban thermal environment,deepen the understanding of the causes of urban heat island effect,and clarify the correlation between human and natural factors,so as to provide scientific supports for the improvement of the quality of urban human settlements.

Big spatial vector data management: a review

Spatial vector data with high-precision and wide-coverage has exploded globally,such as land cover,social media,and other data-sets,which provides a good opportunity to enhance the national macroscopic decision-making,social supervision,public services,and emergency capabilities.Simultaneously,it also brings great challenges in management technology for big spatial vector data(BSVD).In recent years,a large number of new concepts,parallel algorithms,processing tools,platforms,and applications have been proposed and developed to improve the value of BSVD from both academia and industry.To better understand BSVD and take advantage of its value effectively,this paper presents a review that surveys recent studies and research work in the data management field for BSVD.In this paper,we discuss and itemize this topic from three aspects according to different information technical levels of big spatial vector data management.It aims to help interested readers to learn about the latest research advances and choose the most suitable big data technologies and approaches depending on their system architectures.To support them more fully,firstly,we identify new concepts and ideas from numerous scholars about geographic information system to focus on BSVD scope in the big data era.Then,we conclude systematically not only the most recent published literatures but also a global view of main spatial technologies of BSVD,including data storage and organization,spatial index,processing methods,and spatial analysis.Finally,based on the above commentary and related work,several opportunities and challenges are listed as the future research interests and directions for reference.

Carbon Emission Evaluation in Jinan Western New District based on Multi-source Data Fusion

Carbon emissions caused by human activities are closely related to the process of urbanization,and urban land utilization,function vitality and traffic systems are three important factors that may influence the emission levels.For clarifying the space structure of a low-carbon eco-city,and combining the concept of"Combining Assessment with Construction"to track and contrast the construction of the low-carbon eco-city,this research selects quantifiable low-carbon eco-city spatial characteristics as indicators,and evaluates and analyzes the potential carbon emissions.Taking the Jinan Western New District as an example,diversity of construction land,travel carbon emission potential,and density and accessibility of adjacent road networks in the overall urban planning were measured.After the completion of the new urban area,the evaluation mainly reflected certain factors,such as the mixed degree of urban functions,the density of urban functions,the walking distance to bus stops and the density and number of bus stops.Dividing the levels and adding equal weights after index normalization,the carbon emission potential is evaluated at the two levels of the overall and fragmented areas.The results show that:(1)The low-carbon emission potential areas in the planning scheme basically reached the planned goals.(2)There is inconsistency between districts and indicators in the planning scheme.The diversity of construction land and the accessibility of the adjacent road network are relatively small;however,there is a large difference between the travel carbon emission potential and the road network accessibility.(3)Carbon emission potential after completion did not reach the planned expectation,and the low-carbon emission potential plots were concentrated in the Changqing Old City Area and Central Area of Dangjia Town Area.(4)The carbon emission indicators varied greatly in different areas,and there were serious imbalances in the density of public transportation lines and the mixed degree of urban functions.

基于ENVI和ArcGIS对空间栅格数据矢量化与拓扑分析

在科学研究与工程设计领域中,时常需要将原始收集到包含空间栅格数据的图像进行矢量化后再加以分析利用,而传统处理过程多采用人工手动进行,耗时费力。推荐利用ENVI的遥感图像处理功能结合ArcGIS的空间地理信息拓扑分析功能,实现自动批量将图像中空间栅格数据进行矢量化提取并依此展开拓扑分析。以云南省水土流失时空分布特性研究为例介绍该方法的应用与成果,以点及面,使得方法在应用深度与广度上得到进一步拓展,提高科研与设计的工作效率。

市级国土空间总体规划数据库建设与报批内容研究

市级国土空间总体规划数据库是市级总规成果的组成部分,是规划实施的重要依据。通过借鉴原土总规和城总规数据库建设和报批方法,在分析国家已公布的市级总规数据库规范的基础上,结合市级总规编制实际,按照“管什么就批什么”的思路,从优化完善矢量数据入库、明确矢量数据的规划效力、规定规划图件与矢量数据的关系、依规划事权实施差异化的审批规则等方面研究了市级总规数据库建设和报批内容,提出了市级总规矢量数据入库、审批、管理、更新等全流程解决方案,以期为国家制定市级总规成果上报工作提供参考。

基于Cressman优化算法的海洋矢量数据插值方法研究

随着海洋监测技术的发展,多源、异构、多维的海洋数据成指数激增。当前用于海洋数据的插值技术存在处理速度慢、读取效率低等问题,难以满足数据处理的需要。针对具有空间分布特性的海洋矢量数据,本文旨在研究一种高效的插值方法,首先基于Moran's I对矢量数据进行空间相关性分析,根据数据间的聚类程度对数据集进行冗余度处理,然后基于Cressman插值算法对处理后的矢量数据进行插值展示。最后,以某区域的流场数据进行仿真,验证了基于Cressman插值优化算法的合理性和可行性。

基于面向对象数据库的空间数据管理

当前,关系型数据库与面向对象程序设计语言之间不匹配,造成了数据存取效率低下.为此,提出一种基于面向对象空间数据库的空间数据管理方案.分析现有的空间数据类型,设计矢量空间数据结构、栅格空间数据结构和影像数据结构分别表达矢量、栅格和影像数据,并阐述了矢量、栅格和影像数据的面向对象数据库管理方案.基于开源的面向对象数据库db4o,开发了空间数据管理原型系统,实现了矢量、栅格和影像空间数据的一体化管理,并对空间数据进行可视化.因此,基于面向对象数据库能够实现多源、异构的空间数据管理.

空间数据融合的基本框架

本文就空间数据融合的基本理论和问题进行了阐述。空间数据分为矢量数据和栅格数据,由于矢量数据的融合比较简单,本文就矢量数据的图形数据和属性数据的融合加以简单论述;主要研究了栅格数据,目前对于栅格空间数据而言主要是影像数据,本文对影像数据的融合的层次,步骤和方式等问题进行了系统研究;而且对空间数据融合存在的问题和解决的途径进行了论述。