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1.
R数据统计分析软件是Linux平台下的一个优秀的数据统计软件,现在也已提供了在Windows平台下的安装版本并且具有简单的图形用户界面。它使用简单、功能强大且完全免费,因此与SPSS、SAS等较为流行的数据统计分析软件相比具有与一定的经济优势。同时,R语言的灵活性、可扩充性使得R能很容易地应用到GIS领域,在GIS空间数据分析、地统计分析以及图像处理等方面具有很好的应用前景。本文概要介绍了R语言的一些功能特点及其与GIS开源软件GRASS的集成。 相似文献
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GIS已广泛应用在人文社会学科,语言地理信息系统以地理空间数据库为基础,通过数据管理系统将地理空间数据与语言特征数据有机地结合在一起,可以便捷地进行数据检索、绘制语言特征地图和时空分析等操作,为语言学研究提供可视化的科学依据。本文梳理了GIS技术应用在语言学的研究现状,并借助GIS强大的时空分析功能,在语言地理信息系统中动态演示了锡伯语在空间上的历时演变,为锡伯语变迁研究提供了实证材料。 相似文献
3.
Anthony C. Robinson 《制图学和地理信息科学》2015,42(4):91-92
Current research in the Cartographic and Geographic Information Sciences at Penn State emphasizes map design, geovisual analytics, spatiotemporal pattern detection, spatial cognition, CyberGIS, geographic information retrieval, image analysis, and novel methods for geospatial education. Cartography and GIScience research and education at Penn State is organized through groups such as the GeoVISTA Center and the Peter R. Gould Center in the Department of Geography, the Institute for CyberScience, and the John A. Dutton e-Education Institute. Recent achievements in these units have included advances in extracting geographic information from social media, novel methods for pattern analysis from event data, and the development of the first massive open online course in geography. 相似文献
4.
Geospatial Ontology Development and Semantic Analytics 总被引：3，自引：0，他引：3
I Budak Arpinar Amit Sheth Cartic Ramakrishnan E Lynn Usery Molly Azami Mei-Po Kwan 《Transactions in GIS》2006,10(4):551-575
Geospatial ontology development and semantic knowledge discovery addresses the need for modeling, analyzing and visualizing multimodal information, and is unique in offering integrated analytics that encompasses spatial, temporal and thematic dimensions of information and knowledge. The comprehensive ability to provide integrated analysis from multiple forms of information and use of explicit knowledge make this approach unique. This also involves specification of spatiotemporal thematic ontologies and populating such ontologies with high quality knowledge. Such ontologies form the basis for defining the meaning of important relations terms, such as near or surrounded by, and enable computation of spatiotemporal thematic proximity measures we define. SWETO (Semantic Web Technology Evaluation Ontology) and geospatial extension SWETO‐GS are examples of these ontologies. The Geospatial Semantics Analytics (GSA) framework incorporates: (1) the ability to automatically and semi‐automatically tract metadata from syntactically (including unstructured, semi‐structured and structured data) and semantically heterogeneous and multimodal data from diverse sources; and (2) analytical processing that exploits these ontologies and associated knowledge bases, with integral support for what we term spatiotemporal thematic proximity (STTP) reasoning and interactive visualization capabilities. This paper discusses the results of our geospatial ontology development efforts as well as some new semantic analytics methods on this ontology such as STTP. 相似文献
5.
Ivan Henrico Susan Henrico Rikus le Roux Jacques Bezuidenhout 《Transactions in GIS》2023,27(1):105-114
Geographic Information Systems (GIS) consists of various tools to perform spatial analyses in a wide variety of disciplines, including radiometric analysis to characterize the distribution of natural radionuclide concentrations. Recently, open-source GIS has become popular among geospatial users because it can be freely used, and powerful tools are constantly developed to enhance software capabilities. Gamma-ray spectroscopy was used to measure the concentrations of these natural radionuclides by dragging a Delta Underwater Gamma System (DUGS) among the sediment in the Berg River estuary located in Velddrif, South Africa. In this study, QGIS was used to visually illustrate and interpret the distribution of natural radionuclides, that is, potassium (K40), thorium (Th232), and uranium (U238). These concentrations can be used to investigate various geographical and geological phenomena, which include sediment processes. The data were then interpreted to derive sediment characteristics. Various features of tidal estuaries were demonstrated by the results. 相似文献
6.
Alessandro Frigeri Costanzo Federico Cristina Pauselli Giorgio Minelli 《Transactions in GIS》2004,8(2):255-262
During the past few decades, numerous missions to Mars have sent information about the red planet. The missions have shown that Mars has ice on its poles and that ice could be present all over the planet subsurface. The presence of ice on the subsurface could drive particular geological structures called ‘wrinkle ridges’. In this work, Viking image data and the latest Mars Global Suveyor (MGS) data have been imported and stored in a common geospatial database using GRASS GIS as a tool for planetary geology. This study has focused on a subregion of Solis Planum where wrinkle ridges have been localised and both Viking images and MGS altimetry and imagery data are available. Raster data at different resolutions and with different projection parameters have been imported into GRASS GIS and projected in a common reference system. Raw, unprojected data have been processed and rectified using the GRASS image modules. Imagery data have been used to detect planimetric features, whereas basic morphometrical analysis has been performed from the gridded elevation data coming from MGS Mars Orbiter Laser Altimeter. 相似文献
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Adaptable User Profiles for Intelligent Geospatial Queries 总被引：1，自引：0，他引：1
The geospatial information user community is becoming increasingly diverse, with numerous users accessing distributed datasets for various types of applications. Currently in GIS, unlike traditional databases, there is a lack of machine learning algorithms to customize information retrieval results. Thus the particular interests of individual users are not taken into account in traditional geospatial queries. In this paper we present a system that adjusts query results based on user requirements and needs. It does so by using a collection of fuzzy functions that express user preference specifically in GIS environments. The focus of this work is on preference learning for one‐dimensional, quantitative attributes, and on the customization of geospatial queries using this information. The model used to express user preferences adjusts gradually to the underlying complexity during a training process, starting with fairly simple linear functions and progressing to complex non‐linear ones as needed. Our advanced modeling capabilities are demonstrated through an applicability example, and statistical simulations show the robustness of our system. 相似文献
8.
Yikang Wang Yuhao Kang Haokun Liu Ce Hou Bing Zhou Shan Ye Yuyan Liu Jinmeng Rao Zhenghao Pei Xiang Ye Song Gao 《Transactions in GIS》2023,27(2):450-475
With the increasing demands for geospatial analytics in industry and academia, the need for Geographic Information Systems/Science (GIS) education is on the rise. A growing number of departments in geography have launched or expanded their GIS graduate programs. However, the factors influencing students choosing GIS programs have not been examined yet. In this study, we looked at Chinese students applying for overseas GIS programs and examined factors influencing their decision-making. We distributed the survey in GISphere, one of the largest GIS international student communities, and 84 valid questionnaires were returned. We analyzed the spatial and demographic patterns of Chinese students applying for overseas GIS programs. We identify five main factors that affect their choices of GIS programs: (1) education quality and awareness, (2) physical, social, and political environments, (3) improved employment prospects, (4) personal recommendations, and (5) the application process. Our study offers implications for the development of GIS graduate programs. We anticipate that the conclusions drawn from this research will benefit and advance geography and GIS education globally. 相似文献
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Apache Spark分布式计算框架可用于空间大数据的管理与计算,为实现云GIS提供基础平台。针对Apache Spark的数据组织与计算模型,结合Apache HBase分布式数据库,从分布式GIS内核的理念出发,设计并实现了分布式空间数据存储结构与对象接口,并基于某国产GIS平台软件内核进行了实现。针对点、线、面数据的存储与查询,与传统空间数据库系统PostGIS进行了一系列对比实验,验证了提出的分布式空间数据存储架构的可行性与高效性。 相似文献
10.
现代信息技术的变革使网络技术与GIS的结合日益紧密 ,从而促进了开放GIS技术的研究。开放式GIS研究的目的是提供一套具有开放界面规范的通用组件 ,开发者根据这些规范开发出交互式组件 ,从而实现不同种类地理数据和地理处理方法间的透明访问。文中主要讨论了基于CORBA的开放式GIS的网络系统构建技术 ,使用户能在分布式的多服务器且存在异构的网络环境中共享地理空间数据。 相似文献
11.
Despite advancements in geographic information system (GIS) technology, the efficient and effective utilization of GIS to solve geospatial problems is a daunting process requiring specialized knowledge and skills. Two of the most important and burdensome tasks in this process are interpretation of geospatial queries and mapping the interpreted results into geospatial data models and geoprocessing operations. With the current state of GIS, there exists a gap between the knowledge user's possess and the knowledge and skills they need to utilize GIS for solving problems. Currently, users resort to training and practice on GIS technology or involving GIS experts. Neither of these options is optimal and there is a need for a new approach that automates geoprocessing tasks using GIS technology. This paper presents an ontological engineering methodology that uses multiple ontologies and the mappings among them to automate certain tasks related to interpretation of geospatial queries and mapping the interpreted results into geospatial data models and geoprocessing operations. The presented methodology includes conceptualization of geospatial queries, knowledge representation for queries, techniques for relating elements in different ontologies, and an algorithm that uses ontologies to map queries to geoprocessing operations. 相似文献
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Shinji Masumoto Venkatesh Raghavan Go Yonezawa Tatsuya Nemoto Kiyoji Shiono 《Transactions in GIS》2004,8(2):211-223
The present work aims at introducing a basic theory, implementing methodology and algorithms for 3‐D modeling, and visualizing a geologic model using the Open Source Free GIS GRASS environment. A 3‐D geologic model is constructed from the boundary surfaces of geologic units and the logical model of geologic structure. The algorithms for construction and visualization of the proposed model are based on the geologic function g . The geologic function g assigns a unique geologic unit to every point in the objective 3‐D space. The boundary surface that divides the objective space into two subspaces is estimated using data from field survey. The logical model showing the hierarchical relationship between these boundary surfaces and geologic units can be automatically generated based on the stratigraphic sequence and knowledge of geologic structures. Based on these algorithms, a 3‐D geologic model can be constructed virtually in the GRASS GIS. Applying this model, various geologic surfaces and section models can be visualized in the GRASS GIS environment. “Nviz” was used for dynamic visualization of geologic cross‐sections and generation of animated image sequences. Further, the described algorithms and methods are applied and an online 3‐D geologic modeling system is developed. 相似文献
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基于开源平台的中小型WebGIS应用研究 总被引：2，自引：0，他引：2
侧重分析了开源WebGIS平台的技术特点,并根据其成本低廉和良好的扩展性、部署的灵活性,提出采用开源平台构建中小型WebGIS应用的解决方案,对于普及GIS应用,促进地理空间信息共享具有借鉴意义。 相似文献
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Spatial cloud computing: how can the geospatial sciences use and help shape cloud computing? 总被引：1，自引：0，他引：1
《International Journal of Digital Earth》2013,6(4):305-329
Abstract The geospatial sciences face grand information technology (IT) challenges in the twenty-first century: data intensity, computing intensity, concurrent access intensity and spatiotemporal intensity. These challenges require the readiness of a computing infrastructure that can: (1) better support discovery, access and utilization of data and data processing so as to relieve scientists and engineers of IT tasks and focus on scientific discoveries; (2) provide real-time IT resources to enable real-time applications, such as emergency response; (3) deal with access spikes; and (4) provide more reliable and scalable service for massive numbers of concurrent users to advance public knowledge. The emergence of cloud computing provides a potential solution with an elastic, on-demand computing platform to integrate – observation systems, parameter extracting algorithms, phenomena simulations, analytical visualization and decision support, and to provide social impact and user feedback – the essential elements of the geospatial sciences. We discuss the utilization of cloud computing to support the intensities of geospatial sciences by reporting from our investigations on how cloud computing could enable the geospatial sciences and how spatiotemporal principles, the kernel of the geospatial sciences, could be utilized to ensure the benefits of cloud computing. Four research examples are presented to analyze how to: (1) search, access and utilize geospatial data; (2) configure computing infrastructure to enable the computability of intensive simulation models; (3) disseminate and utilize research results for massive numbers of concurrent users; and (4) adopt spatiotemporal principles to support spatiotemporal intensive applications. The paper concludes with a discussion of opportunities and challenges for spatial cloud computing (SCC). 相似文献
16.
Cumulative spatial impact layers: A novel multivariate spatio‐temporal analytical summarization tool
Lucy Romeo Jake Nelson Patrick Wingo Jennifer Bauer Devin Justman Kelly Rose 《Transactions in GIS》2019,23(5):908-936
Scientific inquiry often requires analysis of multiple spatio‐temporal datasets, ranging in type and size, using complex multi‐step processes demanding an understanding of GIS theory and software. Cumulative spatial impact layers (CSIL) is a GIS‐based tool that summarizes spatio‐temporal datasets based on overlapping features and attributes. Leveraging a recursive quadtree method, and applying multiple additive frameworks, the CSIL tool allows users to analyze raster and vector datasets by calculating data, record, or attribute density. Providing an efficient and robust method for summarizing disparate, multi‐format, multi‐source geospatial data, CSIL addresses the need for a new integration approach and resulting geospatial product. The built‐in flexibility of the CSIL tool allows users to answer a range of spatially driven questions. Example applications are provided in this article to illustrate the versatility and variety of uses for this CSIL tool and method. Use cases include addressing regulatory decision‐making needs, economic modeling, and resource management. Performance reviews for each use case are also presented, demonstrating how CSIL provides a more efficient and robust approach to assess a range of multivariate spatial data for a variety of uses. 相似文献
17.
Integrating spatial data analysis functionalities in a GIS environment: Spatial Analysis using ArcGIS Engine and R (SAAR) 
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下载免费PDF全文 Spatial data analysis (SDA) tools to efficiently handle and explore spatial data have become readily available. Although these SDA tools have their own strengths and purposes, they suffer from limited support in terms of a development environment offering easy customization and high extensibility, a strength of open source software. This article presents a standalone software package for SDA in a geographic information system (GIS) environment, called Spatial Analysis using ArcGIS Engine and R (SAAR), which provides an integrated GIS and SDA environment. A set of SDA tools in SAAR utilizes functions in R using R.NET, while other tools were developed in .NET independent of R. SAAR provides an efficient working environment for both general and advanced GIS users. For general GIS users with limited programming skills, SAAR furnishes advanced SDA tools in a popular ArcGIS environment with graphical user interfaces. For advanced GIS users, SAAR offers an extensible GIS platform to help them customize and implement SDA functions with relatively little development effort. This article demonstrates some functionalities of SAAR using census data for Texas counties. 相似文献
18.
Yongyao Jiang Yun Li Fei Hu Edward M. Armstrong Thomas Huang 《International Journal of Digital Earth》2018,11(9):956-971
Current search engines in most geospatial data portals tend to induce users to focus on one single-data characteristic dimension (e.g. popularity and release date). This approach largely fails to take account of users’ multidimensional preferences for geospatial data, and hence may likely result in a less than optimal user experience in discovering the most applicable dataset. This study reports a machine learning framework to address the ranking challenge, the fundamental obstacle in geospatial data discovery, by (1) identifying a number of ranking features of geospatial data to represent users’ multidimensional preferences by considering semantics, user behavior, spatial similarity, and static dataset metadata attributes; (2) applying a machine learning method to automatically learn a ranking function; and (3) proposing a system architecture to combine existing search-oriented open source software, semantic knowledge base, ranking feature extraction, and machine learning algorithm. Results show that the machine learning approach outperforms other methods, in terms of both precision at K and normalized discounted cumulative gain. As an early attempt of utilizing machine learning to improve the search ranking in the geospatial domain, we expect this work to set an example for further research and open the door towards intelligent geospatial data discovery. 相似文献
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John Samuel Vincent Jaillot Clément Colin Diego Vinasco Alvarez Eric Boix Sylvie Servigne Gilles Gesquière 《Transactions in GIS》2023,27(3):841-858
With the widespread availability of a large volume of urban data, stakeholders from different domains require advanced tools to manage, visualize and understand cities and their evolution. During the last few years, researchers have proposed numerous research works and applications to illustrate the cities of the past and possible scenarios of the future under different conditions. However, many of these approaches are one-time solutions and not based on standards, making them obsolete and unusable for reproducible research. In this article, we present UD-SV: an Urban data-Services and Visualization open-source framework for multidisciplinary research to handle complex processing, analysis, and visualization of urban data. However, our goal is not to present a one-time monolithic software solution for urban data management and analysis, but we demonstrate the design and development of an open and interoperable software framework driven by use cases from diverse users to solve applied research challenges. The main contribution of UD-SV is that it uses open standards and open data with documented and reproducible processes with a particular emphasis on the reuse of existing open-source software components. We also show an enhanced use of standards to enable a shift toward components that are interchangeable or composable with other existing components in the GIS community. 相似文献