Enviromental data visualisation using Delaunay triangulation
Abstract
Graphical data representation is very helpful when analyzing environmental data. It allows for discovering trends in data and analysis of phenomena occurring in the area. There are many possibilities to represent such values graphically. This article contains visualizations generated using Delauney triangulation to represent data on a map. Strengths and weaknesses, comparative analysis with another solution, performance, and usage suggestions will be presented.
References
J. Lelieveld,Cardiovascular disease burden from ambient air pollution in Europe reassessed using novel hazard ratio functions, Eur Heart J, t. 40, nr 20, s.1590–1596, maj 2019, doi: 10.1093/eurheartj/ehz135.
D.W. Dockery, C.A. Pope, Acute respiratory effects of particulate air pollution, Annual review of public health, t. 15, nr 1, s. 107–132, 1994.
L. Guibas, J. Stolfi, Primitives for the manipulation of general subdivisions and the computation of Voronoi, ACM Trans. Graph., t. 4, nr 2, s. 74–123, kwi. 1985, doi: 10.1145/282918.282923.
D. Fichter, What is a mashup, Library Mashups. Exploring new ways to deliver library data. Medford, NJ: Information Today, Inc, 2009.
V. Subramanian, Pro MERN Stack: Full Stack Web App Development with Mongo, Express, React, and Node. Apress, 2017.
M. Pieniążek, B. Szejgiec, M. Zych, A. Ajdyn, G. Nowakowska, Graficzna prezentacja danych statystycznych Wykresy, mapy, GIS. Warszawa: Główny Urząd Statystyczny Departament Badań Regionalnych i Środowiska, 2014.
„Stack Overflow Developer Survey 2020”, Stack Overflow. https://insights.stackoverflow.com/survey/2020/?utm˙source=social-share&utm˙medium=social&utm˙campaign=dev-survey-2020, (udostępniono cze. 25, 2020).
Poland
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
