A Multi-Feature Based Automatic Approach to Geospatial Record Linking

2019 ◽  
pp. 10-30
Author(s):  
Ying Zhang ◽  
Puhai Yang ◽  
Chaopeng Li ◽  
Gengrui Zhang ◽  
Cheng Wang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Information Systems ◽  
Geographic Information Systems ◽  
Geographic Information ◽  
Geospatial Data ◽  
Data Sources ◽  
Supervised Machine Learning ◽  
Multiple Features ◽  
Feature Based ◽  
Record Similarity

This article describes how geographic information systems (GISs) can enable, enrich and enhance geospatial applications and services. Accurate calculation of the similarity among geospatial entities that belong to different data sources is of great importance for geospatial data linking. At present, most research works use the name or category of the entity to measure the similarity of geographic information. Although the geospatial relationship is significant for geographic similarity measure, it has been ignored by most of the previous works. This article introduces the geospatial relationship and topology, and proposes an approach to compute the geospatial record similarity based on multiple features including the geospatial relationships, category and name tags. In order to improve the flexibility and operability, supervised machine learning such as SVM is used for the task of classifying pairs of mapping records. The authors test their approach using three sources, namely, OpenStreetMap, Google and Wikimapia. The results showed that the proposed approach obtained high correlation with the human judgements.

A Multi-Feature Based Automatic Approach to Geospatial Record Linking

2018 ◽  
Vol 14 (4) ◽  
pp. 73-91 ◽  
Author(s):  
Ying Zhang ◽  
Puhai Yang ◽  
Chaopeng Li ◽  
Gengrui Zhang ◽  
Cheng Wang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Geographic Information ◽  
Geospatial Data ◽  
Data Sources ◽  
Supervised Machine Learning ◽  
Accurate Calculation ◽  
Multiple Features ◽  
And Topology ◽  
Feature Based ◽  
Record Similarity

This article describes how geographic information systems (GISs) can enable, enrich and enhance geospatial applications and services. Accurate calculation of the similarity among geospatial entities that belong to different data sources is of great importance for geospatial data linking. At present, most research works use the name or category of the entity to measure the similarity of geographic information. Although the geospatial relationship is significant for geographic similarity measure, it has been ignored by most of the previous works. This article introduces the geospatial relationship and topology, and proposes an approach to compute the geospatial record similarity based on multiple features including the geospatial relationships, category and name tags. In order to improve the flexibility and operability, supervised machine learning such as SVM is used for the task of classifying pairs of mapping records. The authors test their approach using three sources, namely, OpenStreetMap, Google and Wikimapia. The results showed that the proposed approach obtained high correlation with the human judgements.

Hybrid Machine Learning and Geographic Information Systems Approach — A Case for Grade Crossing Crash Data Analysis

2020 ◽  
Vol 12 (01) ◽  
pp. 2050003
Author(s):  
Ahmed Lasisi ◽  
Pengyu Li ◽  
Jian Chen
Keyword(s):  
Machine Learning ◽  
Information Systems ◽  
Geographic Information Systems ◽  
The United States ◽  
Geographic Information ◽  
Supervised Machine Learning ◽  
Machine Learning Classification ◽  
Rail Network ◽  
Grade Crossing ◽  
Hybrid Machine

Highway-rail grade crossing (HRGC) accidents continue to be a major source of transportation casualties in the United States. This can be attributed to increased road and rail operations and/or lack of adequate safety programs based on comprehensive HRGC accidents analysis amidst other reasons. The focus of this study is to predict HRGC accidents in a given rail network based on a machine learning analysis of a similar network with cognate attributes. This study is an improvement on past studies that either attempt to predict accidents in a given HRGC or spatially analyze HRGC accidents for a particular rail line. In this study, a case for a hybrid machine learning and geographic information systems (GIS) approach is presented in a large rail network. The study involves collection and wrangling of relevant data from various sources; exploratory analysis, and supervised machine learning (classification and regression) of HRGC data from 2008 to 2017 in California. The models developed from this analysis were used to make binary predictions [98.9% accuracy & 0.9838 Receiver Operating Characteristic (ROC) score] and quantitative estimations of HRGC casualties in a similar network over the next 10 years. While results are spatially presented in GIS, this novel hybrid application of machine learning and GIS in HRGC accidents’ analysis will help stakeholders to pro-actively engage with casualties through addressing major accident causes as identified in this study. This paper is concluded with a Systems-Action-Management (SAM) approach based on text analysis of HRGC accident risk reports from Federal Railroad Administration.

scholarly journals Shared Data Sources in the Geographical Domain—A Classification Schema and Corresponding Visualization Techniques

2019 ◽  
Vol 8 (5) ◽  
pp. 242 ◽  
Author(s):  
Franz-Benjamin Mocnik ◽  
Christina Ludwig ◽  
A. Grinberger ◽  
Clemens Jacobs ◽  
Carolin Klonner ◽  
...  
Keyword(s):  
Information Systems ◽  
Geographic Information Systems ◽  
Public Participation ◽  
Geographic Information ◽  
Data Sources ◽  
Individual Data ◽  
Shared Data ◽  
Share Data ◽  
Visualization Techniques ◽  
Voluntary Basis

People share data in different ways. Many of them contribute on a voluntary basis, while others are unaware of their contribution. They have differing intentions, collaborate in different ways, and they contribute data about differing aspects. Shared Data Sources have been explored individually in the literature, in particular OpenStreetMap and Twitter, and some types of Shared Data Sources have widely been studied, such as Volunteered Geographic Information (VGI), Ambient Geographic Information (AGI), and Public Participation Geographic Information Systems (PPGIS). A thorough and systematic discussion of Shared Data Sources in their entirety is, however, still missing. For the purpose of establishing such a discussion, we introduce in this article a schema consisting of a number of dimensions for characterizing socially produced, maintained, and used ‘Shared Data Sources,’ as well as corresponding visualization techniques. Both the schema and the visualization techniques allow for a common characterization in order to set individual data sources into context and to identify clusters of Shared Data Sources with common characteristics. Among others, this makes possible choosing suitable Shared Data Sources for a given task and gaining an understanding of how to interpret them by drawing parallels between several Shared Data Sources.

scholarly journals Paper on the conceptual definition of the geo-topographic support

Vojno delo ◽  
2021 ◽  
Vol 73 (1) ◽  
pp. 44-57
Author(s):  
Dejan Đorđević ◽  
Dragoljub Sekulović
Keyword(s):  
Information Systems ◽  
Geographic Information Systems ◽  
Armed Forces ◽  
Geographic Information ◽  
Information And Communications Technology ◽  
Geospatial Data ◽  
Conceptual Definition ◽  
The Republic ◽  
Support Principle ◽  
Definition Of

The Serbian Armed Forces support represents a part of the military activity aimed at creating conditions for the execution of missions and tasks. For successful support, it is necessary to establish the cooperation with relevant institutions of the Republic of Serbia. The conceptual definition of the geo-topographic support has been researched in the context of previous and current regulations, which have shown that the achievements of information and communications technology have influenced not only the development of the geographic information systems, but also directly the definition of this concept. The importance of the geographic information systems in the collection, processing, analysis and use of geospatial data has also determined the contents of the geo-topographic support. The continuous development of the geographic information systems in the direction of establishing a service-oriented approach to the distribution and use of geospatial data, will directly affect the future improvement of the content of the geo-topographic support. Such a process is accompanied by the establishment of the geo-topographic support principle, which should enable the construction and maintenance of a stable structure, in order to successfully carry out the assigned missions and tasks of the Serbian Armed Forces.

Characterizing and Mapping Health in Urban Areas

2020 ◽  
pp. 156-178
Author(s):  
Gina S. Lovasi ◽  
Steve Melly
Keyword(s):  
Information Systems ◽  
Geographic Information Systems ◽  
Needs Assessment ◽  
Urban Health ◽  
Urban Areas ◽  
Health Data ◽  
Geographic Information ◽  
Data Sources ◽  
Multiple Outcomes ◽  
Urban Context

This chapter highlights how the measurement and mapping of multiple outcomes in urban health can serve goals of local needs assessment and surveillance in cities. A range of data sources and associated issues within an urban context are described. In addition, geographic information systems terms are highlighted, including those relevant to visually representing geographically referenced health data.

The formation stages of information model of geo-objects

2020 ◽  
pp. 66-72
Author(s):  
G. G. Bikbulatova ◽  
E. N. Kupreeva
Keyword(s):  
Information Systems ◽  
Geographic Information Systems ◽  
Information Model ◽  
Geographic Information ◽  
Geospatial Data ◽  
Design System ◽  
Computer Design ◽  
Production Processes

The article discusses the stages of the formation of an information model of geospatial data using Autodesk Civil 3D. The peculiarity of the work and its practical signifi cance is based on the preparation of an information model of geo-objects in a computer design system in contrast to geographic information systems. The results of such models are more adapted for further use in geodetic support of various production processes.

scholarly journals SOME ASPECTS OF THE PBL MODEL WHEN TEACHING DISCIPLINES IN DIGITAL TERRAIN SIMULATION

2021 ◽  
pp. 178-181
Author(s):  
Tatyana A. Khlebnikova
Keyword(s):  
Information Systems ◽  
Spatial Analysis ◽  
Geographic Information Systems ◽  
Problem Based Learning ◽  
Geographic Information ◽  
Educational Process ◽  
Geospatial Data ◽  
Digital Terrain ◽  
Pbl Model

The article discusses aspects of the innovative form of the educational process - problem based learning. The examples of problem-based tasks in the study of the discipline "Modeling and Spatial Analysis in Geographic Information Systems" are given. The possibilities of using geoportals as the main source of open digital cartographic data for developing skills in working with geospatial data are considered.

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