The possibilities of visual spatial data analysis methods on human migration data.
Journal Title
Journal ISSN
Volume Title
Insinööritieteiden korkeakoulu |
Master's thesis
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Author
Date
2020-01-20
Department
Major/Subject
Mcode
Degree programme
Master's Programme in Geoinformatics (GIS)
Language
en
Pages
45
Series
Abstract
The theme of this Master’s thesis is to research the possible methods for visual analysis of human migration. Precedents of analysis methods are considered as viable techniques that would successfully achieve a rewarding result if conducted on Finland´s migration database. Human migration phenomenon can be analyzed with the visualization of spatial data. Spatial data visualization components such as spatial data, maps and methods are discussed with focus on human migration. Human migration data are a type of spatial data that are georeferenced so as to give a context in relation to a location in real world. Maps are geographical presentation interfaces used for visual analysis of migration data. Special purpose and thematic maps or the combination of both are deemed suitable for this task as they are able to portray the information desired. Spatial data visualization techniques such as flow lines, flowstrates, map animation and space time cube are researched as tools for fully analyzing migration data. Flowstrates is a specialized visualization method that analyses the spatial and temporal dimensions of migration data by utilizing a combination technique of flow lines, timelines, and origin-destination matrices for the visualization of migration data. With this novel method, detailed information can be visualized on individual migration flow/route. The result of this thesis are the examples of the most fitting visual analysis methods for migration data. These examples serve as the possible methods for analyzing actual migration data in Finland.Description
Supervisor
Virrantaus, Kirsi KanervaThesis advisor
Virantaus, Kirsi KanervaKeywords
geospatial, migration, origin-destination, visualization, flowstrates, method
