Technological Advancements in Urban Remote Sensing
The continued unprecedented development and growth in the urban population has placed an emphasis on many aspects, such as environmental impact, sustainable development, and public services. Currently, urban environments around the world are actively involved in obtaining solutions to improve inhabitants’ quality of life as well as enrich the use of city infrastructure and resources while reducing the operational costs to do so. Urban remote sensing plays a vital role in the ability to map, monitor and control infrastructure. Benefiting from data-driven, model-driven or hybrid approaches, remote sensing can contribute significantly to future urban planning and management. Variant sensors mounted on mobile, airborne, and satellite platforms, along with devices with IoT capabilities, are required for effective coordination and control of urban infrastructure.
Urban remote sensing had its origins decades ago. However, the changes in technological advancements in sensors and methods, along with a considerable amount of data provided on a daily basis, give rise to the opportunity to investigate novel avenues of research in this area. Technological advancements in this field include improvements in imaging sensors as well as data processing methods, including learning systems (artificial intelligence and machine learning).
This updated collection of articles will drive the next generation of urban remote sensing. Submissions on the following sub-topics are encouraged:
- Advances in remote sensor Big Data analytics for urban environments and Smart Cities
- Frontiers in security, privacy, and trust in sensor-based urban environments and IoT
- Machine Learning and AI Techniques in urban Remote Sensing
- Change detection in urban areas using multi-sensor solutions
- 3D modelling of urban infrastructure and urban Digital Twins
- Multi-modal mapping systems and their applications in urban areas
- Application of imagery data from novel Remote Sensing sensors or platforms for urban land information extraction
Edited by
Prof. Shabnam Jabari(University of New Brunswick, Canada)
Prof. Gautam Srivastava(Brandon University, Canada)
Dr. Ying Zhang(Natural Resources Canada)