All Outputs (3)

Copernicus for urban resilience in Europe (2023)
Journal Article
Chrysoulakis, N., Ludlow, D., Mitraka, Z., Somarakis, G., Khan, Z., Lauwaet, D., …Holt Andersen, B. (2023). Copernicus for urban resilience in Europe. Scientific Reports, 13(1), Article 16251. https://doi.org/10.1038/s41598-023-43371-9

The urban community faces a significant obstacle in effectively utilising Earth Observation (EO) intelligence, particularly the Copernicus EO program of the European Union, to address the multifaceted aspects of urban sustainability and bolster urban... Read More about Copernicus for urban resilience in Europe.

Deep learning-based multi-target regression for traffic-related air pollution forecasting (2023)
Journal Article
Akinosho, T. D., Bilal, M., Hayes, E. T., Ajayi, A., Ahmed, A., & Khan, Z. (2023). Deep learning-based multi-target regression for traffic-related air pollution forecasting. Machine Learning with Applications, 12, Article 100474. https://doi.org/10.1016/j.mlwa.2023.100474

Traffic-related air pollution (TRAP) remains one of the main contributors to urban pollution and its impact on climate change cannot be overemphasised. Experts in developed countries strive to make optimal use of traffic and air qua... Read More about Deep learning-based multi-target regression for traffic-related air pollution forecasting.

SIGNED: Smart cIty diGital twiN vErifiable data framework (2023)
Journal Article
Pervez, Z., Khan, Z., Ghafoor, A., & Soomro, K. (2023). SIGNED: Smart cIty diGital twiN vErifiable data framework. IEEE Access, 11, 29430-29446. https://doi.org/10.1109/ACCESS.2023.3260621

Smart city digital twins can provide useful insights by making effective use of multidisciplinary urban data from diverse sources. Whilst these insights provide new information that helps cities in decision making, verifying the authenticity, integri... Read More about SIGNED: Smart cIty diGital twiN vErifiable data framework.