'Geovisual Analytics' represents a cross-disciplinary research that looks for innovative methods to interactively visualize and solve large spatio-temporal related visualization problems for multivariate data through a visual discovery, reasoning and collaborative process. The name emphasizes the link with the well-known research discipline of Visual Analytics and could be viewed as sub-area with its specific focus on space and time posing specific research problems.

This thesis focuses on the design, implementation and evaluation of interactive analytical spatio-temporal and multivariate representations demonstrated in several application scenarios which contributes to our understanding of how technology, people and spatial representations of information work effectively together. Data are analysed through the use of coordinated and time-linked views controlled by a time slider. Trends are detected through several visual representations simultaneously, each of which is best suited to highlight different patterns and can help stimulate the analytical visual thinking process so characteristic for geovisual analytics reasoning. Interactive features include tooltips, brushing, highlight, visual inquiry, and conditioned statistics filter mechanisms that can discover outliers and simultaneously update all views.

To support knowledge capture and the communication and publishing of gained insights from the data exploration process, a visual storytelling concept with snapshots is introduced where the author can capture the visual data exploration process and share it. Snapshots are memorized interactive visualization views that are captured and later on recreated, so that the reader of the story can see the same mental interactive scenario as the author of the story. These snapshots are then part of a story where the author writes an explanatory text and uses the snapshots to highlight key words. These highlights will allow the reader to recreate the data views used by the author and will guide the reader to the visual discoveries made.

The contributions of this thesis are divided into two parts, where the first part includes applications based on geovisual analytics methods for exploring complex weather data and finding patterns and relationships within the data. Earlier, the use of data visualization has been very limited and the introduction of geovisual analytics and the techniques used have significantly improved the visual analysis process as well as increased the flexibility. The results of this research are today used by SMHI to improve optimization and safety of voyages and monitoring of the weather along Swedish roads. Formative evaluations were performed with domain analysts with the purpose to explore qualitative usability issues with respect to visual representations and interactive representation.

Furthermore, this thesis contributes with a visual storytelling approach which aims at giving domain experts novel methods for capturing and sharing information discoveries in a way that the reader can follow the process of visual exploration. This approach has been tested and verified within the domain of public statistics, where national and regional statistics is published to the public through the use of embedded interactive visualizations and a story that can engage the reader. The concept of visual storytelling has also been introduced to educators, where stories are used as interactive teaching material for students to make national and regional statistics interactive and visually understandable to the students. It will also challenge the students to investigate new theories and then communicate them visually.