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- Dokumenttyp:
- Masterarbeit
- Autor(en):
- Zhu, Lin
- Titel:
- User-centric geospatial analytics and visualization of catastrophe risk portfolio using the example of the insurance industry
- Abstract:
- Nowadays, visualization techniques, especially with Geo-spatial extension are playing a significant role in communicating the information between the dataset and end users from multi scales and multi variate aspects. For supporting the spatial data exploration process efficiently, visualization strategies implemented in a Geo-visualization application need to be designed based on the dataset and targeted users. Thus, there is no universal solution for all visualization problem. Proposing a comprehensive visualization strategy is still a challenge work. Point data is one of the typical spatial data types which indicates the certain location in the world. This thesis research focuses on the large point dataset and proposes a visualization strategy with a hierarchical visual prototype considering users’ information appetites for exploring the dataset in different granularities. To verify the effectiveness of proposed visualization strategy, this thesis implemented the proposed visualization strategy into the insurance industry using the catastrophe (CAT) portfolio dataset provided by Allianz Global Corporate & Specialty (AGCS). The workflow is guided by the concept of user-centred design which is started with assessing users’ requirements and ended with user test. In this thesis, a visualization strategy with multi-resolution global hexagon layers is proposed for supporting users to explore the large location datasets and assisting their decision-making process. In the studied case, the proposed visualization strategy is applied for the CAT portfolio dataset and realized into a web-based visualization application. The application can be used for facilitating two main working scenarios for users from AGCS. In the end, the usability of the visualization strategy in this thesis also be evaluated via testing the application.
- Stichworte:
- Geo-visualization, tessellation, spatial binning, Data Aggregation, Risk Management
- Fachgebiet:
- GEO Geowissenschaften
- DDC:
- 620 Ingenieurwissenschaften
- Betreuer:
- Dr.-Ing. Mathias Jahnke TU München
- Gutachter:
- Dr. Paulo Raposo (ITC)
- Kooperationspartner:
- Lars, Haider (Allianz Global Corporate & Speciality SE) Cosmin- Razvan, Tanasescu (Allianz Global Corporate & Speciality SE)
- Jahr:
- 2020
- Quartal:
- 3. Quartal
- Jahr / Monat:
- 2020-09
- Monat:
- Sep
- Seiten/Umfang:
- 92
- Sprache:
- en
- Hochschule / Universität:
- Technische Universität München
- TUM Einrichtung:
- Lehrstuhl für Kartographie
- Bearbeitungsende:
- 18.09.2020
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