Browsing by Author "Li, Mingke"
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- ItemOpen AccessHexagonal Discrete Global Grid Systems in Topographical and Hydrological Modeling(2023-03-13) Li, Mingke; Stefanakis, Emmanuel; McGrath, Heather; Liang, Steve; Pietroniro, Alain; Kershaw, JohnGeographic Information Systems (GIS) have dominated geospatial analysis since the 1960s, where spatial phenomena were normally represented by individual thematic layers at a specific resolution, and commonly projected to a two-dimensional Cartesian coordinate system for analysis. Discrete Global Grid Systems (DGGS), as a “congruent geography”, hierarchically partition the Earth’s surface into nearly uniform cells at various resolutions to provide great opportunities for innovation of legacy GIS. In the past few decades, the development of DGGS focused on fundamental implementations, such as polyhedral projections, indexing mechanisms, and generation of hierarchical grids, while limited efforts were given to the applicability studies in real-world scenarios. This dissertation aimed to bridge the gap between the existing DGGS implementations and DGGS-driven decision-making in the real world, and specifically, demonstrate the applicability of hexagonal DGGS in the domain of topographical and hydrological modeling. To achieve the above goal, this dissertation first reviewed the functional operations in a DGGS environment and compared them to those in the traditional GIS. This dissertation then focused on the terrain data integration, management, and analysis in the Icosahedral Snyder Equal Area Aperture 3 Hexagonal Grid (ISEA3H) DGGS. Specifically, the integration process, including quantization and aggregation, of multi-source terrain data at various granularities was demonstrated. Various topographical and hydrological functions, including slope and aspect, flow direction, flow accumulation, etc., were developed and experimented with various terrain types at different resolutions. Finally, external machine learning algorithms were incorporated into the DGGS and used to predict future flood risks under multiple climate change scenarios. This dissertation promotes the adoption of DGGS in real-world decision-making, particularly in topographical and hydrological modeling. The proposed methodology for heterogenous data integration can facilitate the development of a national elevation data service in the future. The developed spatial operations can enhance the analytical functionality of hexagonal DGGS. The application in flood mapping indicated the feasibility of DGGS as the standard data fabric for multi-source data integration and multi-scale data mining.