Smart City Gnosys
Smart city article details
| Title | Remote Sensing And Ai For Building Climate Adaptation Applications |
|---|---|
| ID_Doc | 45021 |
| Authors | Sirmacek B.; Vinuesa R. |
| Year | 2022 |
| Published | Results in Engineering, 15 |
| DOI | http://dx.doi.org/10.1016/j.rineng.2022.100524 |
| Abstract | Urban areas are not only one of the biggest contributors to climate change, but also they are one of the most vulnerable areas with high populations who would together experience the negative impacts. In this paper, we address some of the opportunities brought by satellite remote sensing imaging and artificial intelligence (AI) in order to measure climate adaptation of cities automatically. We propose a framework combining AI and simulation which may be useful for extracting indicators from remote-sensing images and may help with predictive estimation of future states of these climate-adaptation-related indicators. When such models become more robust and used in real-life applications, they may help decision makers and early responders to choose the best actions to sustain the well-being of society, natural resources and biodiversity. We underline that this is an open field and an on-going area of research for many scientists, therefore we offer an in-depth discussion on the challenges and limitations of data-driven methods and the predictive estimation models in general. © 2022 The Authors |
| Author Keywords | Artificial intelligence; Climate change; Remote sensing; Smart cities; Sustainable development goals (SDGs) |
Similar Articles
| Id | Similarity | Authors | Title | Published |
|---|---|---|---|---|
60296  | 0.87 | Ge L. | Urbanization Trend Prediction And Spatial Resource Optimization Using Optical Remote Sensing And Machine Learning | Proceedings of SPIE - The International Society for Optical Engineering, 13682 (2025) |
| 7201 | 0.868 | Sitthi A.; Hassan S.-U. | Al-Based Remoted Sensing Model For Sustainable Landcover Mapping And Monitoring In Smart City Context | Springer Proceedings in Complexity (2023) |
| 35862 | 0.866 | Diodati D.; Cruciani A.; Natale A. | Machine And Deep Learning Using Remote Sensing To Reach Zero Emission Cities: A Survey | ISC2 2022 - 8th IEEE International Smart Cities Conference (2022) |
| 7454 | 0.866 | Wen Z.; Chen L. | An Ai-Driven Planning Framework For Ice And Snow Towns: Integrating Optical Remote Sensing And Machine Learning | Proceedings of SPIE - The International Society for Optical Engineering, 13682 (2025) |
| 2457 | 0.86 | Furuya M.T.G.; Furuya D.E.G.; de Oliveira L.Y.D.; da Silva P.A.; Cicerelli R.E.; Gonçalves W.N.; Junior J.M.; Osco L.P.; Ramos A.P.M. | A Machine Learning Approach For Mapping Surface Urban Heat Island Using Environmental And Socioeconomic Variables: A Case Study In A Medium-Sized Brazilian City | Environmental Earth Sciences, 82, 13 (2023) |
| 58170 | 0.852 | Rickens B.; Tonekaboni N.H. | Towards High Resolution Urban Heat Analysis: Incorporating Thermal Drones To Enhance Satellite Based Urban Heatmaps | ACM Web Conference 2023 - Companion of the World Wide Web Conference, WWW 2023 (2023) |