Urban Remote Sensing

Cities are focal points for economic activities and engines of economic growth. They are centers of excellence for technological innovation, education, communication, health care, culture, social services, government administration, entertainment, and entrepreneurship. They create opportunities for jobs, financial resources, and livelihood. They also serve as vital hubs for rural hinterlands to minimize or eradicate rural poverty. However, with increasing population pressure, especially in slums, urban environmental, climate, social, and health issues have become more and more problematic. In addition, there are serious transport challenges that are often related to urban areas and take place when transport systems are incapable of fulfilling the various necessities of urban mobility. Urban traffic congestion is one of the most prevalent transport problems in large urban agglomerations. For the above developments, urban pollution becomes one of the most drastic issues. In addition to mitigating urban emission, storm water effluence, noise pollution, controlling wastes, and managing the consumption of non-renewable resources have become serious concerns. Moreover, the capacity of cities to effectively and efficiently manage urban growth and development, including mitigation and preparedness to urban disasters, needs serious attention.

Urban Remote Sensing serves as a platform to provide evidence-based theoretical and practical knowledge that contributes to solving or better understanding the problems of urban issues and formulating relevant policies for sustainable urban systems.

The primary aim of Urban Remote Sensing is to encourage remote sensing and geospatial scientists to publish their theoretical and empirical research in connection to urban settings and their related environmental issues.

Topics may include, but are not limited to, the following:

• Urban object-analysis and identification
• Assessment and monitoring of urban emissions
• Urban spatial configuration and pattern analysis
• Unmanned Aerial Vehicle data processing and analysis
• Data mining and machine learning in urban applications
• 3D and 4D urban modeling from satellite, airborne, and terrestrial sensors
• Urban data-processing methods and algorithms
• Space-time analysis of urban environmental parameters
• Urban disaster-monitoring and change analysis
• Interdisciplinary urban case studies
• Multiscale sensors and systems: specific urban challenges
• Multispectral/SAR sensor data analysis and integration for urban classification
• Radar and LiDAR applications in urban settings
• Scale issues related to urbanscapes
• The urban heat island effect and thermal sensing
• Urban climate-change and variation
• Urban data-synthesis and analysis
• Urban visualization and virtual reality applications
• Urban applications of high-resolution optical sensors
• Geospatial cyberinfrastructure for cities