THESIS

The overall goal of the thesis is to analyze, describe and evaluate the spatial and geographic aspects of google cloud platforms. To achieve this broad goal, several objectives were developed. The first objective is the review the spatial and geospatial ecosystem of google cloud platforms. Extensive review of the entire ecosystem was performed but case studies developed in google data studio because it is free and offers great tools for visualization. The theoretical part was supplement with three case studies to demonstrate the spatial and visualization dimensions of google platforms. The study found out that the ecosystem of google cloud supports scalable and robust spatial data via its various cloud based services.

Case study approach was adopted for the study due to limited scope of academic literature on the topic. Also the second objective which seeks to investigate the visualization dimension of google cloud platform with emphasis on the general and cartographic methods, parameters, datasets and implementation approach requires a case study approach. Using three case studies, namely, covid-19 data visualization, Palacky University Olomouc department of Geoinformatics web Analytics, and World population and share of Air pollution death visualization various cartographic and general visualization methods were studied. It was realized that, Google’ data studio platform support multi spatial data integration via in-build or community connectors. Also basic map design considerations like scale, symbolization and visual variable are possible. The study found out that the interactive nature coupled with ability to customize layouts and support for visual hierarchy make is a great tool for cartographic visualization. SWOT analysis and heuristic evaluation was conducted for indebt expert opinion on the visualization, user, methodological and geoinformatical aspects. The study realized that data studio is better with visualization, user need and more economical. There are however, some limitation with methodological and geoinformatical aspects.

The study also seeks to analyze the general limitation and potential of google cloud platform and as well develop a workflow flow. The major potential identified is the scalability and ease of use whereas the uncertainty due to frequent product update was a limiting factor. A four process design framework was developed to for spatial data visualization in google studio. This include geospatial data source, map design considerations, cartographic method visualization and Evaluation. A major contribution of the study is exploring an alternative visual communication approach. A recommendation for further study is on comparing the spatial data visualization dimensions across multiple cloud GIS platforms.