Discrete Global Grid Systems as scalable geospatial frameworks for characterizing coastal environments. (December 2021)

• Record Type: Journal Article
• Authors: Bousquin, Justin
• Is Part Of: Environmental modelling & software. Volume 146(2021)
• Publication Date: 2021-12
• Subjects: Discrete Global Grid System -- Coastal -- Water quality -- Geospatial framework -- Big data; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2021.105210
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Data portals and services have increased coastal water quality data availability and accessibility. However, tools to process this data are limited – geospatial frameworks at the land-sea interface are either adapted from open-water frameworks or extended from watershed frameworks. This study explores use of a geospatial framework based on hexagons from a Discrete Global Grid System (DGGS) in a coastal area. Two DGGS implementations are explored, dggridR and H3. The geospatial frameworks are compared based on their ability to aggregate data to scales from existing frameworks, integrate data across frameworks, and connect flows across the land-sea interface. dggridR was simpler with more flexibility to match scales and use smaller units. H3 was more performant, identifying neighbors and moving between scales more efficiently. Point, line and grid data were aggregated to H3 units to test the implementation's ability to model and visualize coastal data. H3 performed these additional tasks well.