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Vital, D., Mariano, P., Almeida, S. M. & Santana, P. (2022). Knowledge-based generation of plausible air quality maps in the absence of sensor data. International Journal of Creative Interfaces and Computer Graphics. 13 (1), 1-17

D. Vital et al.,  "Knowledge-based generation of plausible air quality maps in the absence of sensor data", in Int. Journal of Creative Interfaces and Computer Graphics, vol. 13, no. 1, pp. 1-17, 2022

@article{vital2022_1724520011038,
	author = "Vital, D. and Mariano, P. and Almeida, S. M. and Santana, P.",
	title = "Knowledge-based generation of plausible air quality maps in the absence of sensor data",
	journal = "International Journal of Creative Interfaces and Computer Graphics",
	year = "2022",
	volume = "13",
	number = "1",
	doi = "10.4018/IJCICG.311836",
	pages = "1-17",
	url = "https://www.igi-global.com/gateway/article/311836"
}

TY  - JOUR
TI  - Knowledge-based generation of plausible air quality maps in the absence of sensor data
T2  - International Journal of Creative Interfaces and Computer Graphics
VL  - 13
IS  - 1
AU  - Vital, D.
AU  - Mariano, P.
AU  - Almeida, S. M.
AU  - Santana, P.
PY  - 2022
SP  - 1-17
SN  - 1947-3117
DO  - 10.4018/IJCICG.311836
UR  - https://www.igi-global.com/gateway/article/311836
AB  - Industrialization increased air pollution sources, which is a cause of major health problems. As such, air pollution became a growing concern and there is a need to monitor and easily visualize air pollution data. There are thousands of air quality monitoring stations throughout the world that are used to measure air quality. Moreover, there are plenty of applications that have been developed to visualize air pollution that use information gathered by these air quality monitoring stations as well as other sources of information, such as traffic intensity or weather forecasts. This paper introduces a novel graphical tool that taps on a new source of information: expert knowledge of air pollution sources. This tool allows experts to represent air pollution sources and their dynamics, and to assign them to different map elements. The authors have performed tool's usability and viability tests with 30 participants of which 6 are environmental experts. The obtained results and the provided feedback show that the proposed approach is a promising complement to sensor-based mapping approaches.
ER  -