Using Space-Based Downstream Services for Urban Management in Smart Cities

Data collected through remote sensing (for instance geo-satellite) provides necessary stimulus for developing smart solutions for climate change & public health, energy efficiency and land monitoring in an urban environment. The velocity, variety, volume and veracity of high resolution data produced by geo-satellites provide big opportunity for planning and decision making in a smart city context. However, processing and integrating remote sensing data with auxiliary data sources require proper data management and elastic computational resources to derive necessary information intelligence (or knowledge) for decision making. This paper presents prototype of selected Decumanus services and highlights strengths & weaknesses of climate change, energy efficiency and land monitoring applications for the different European cities. The analysis of the early results indicate that the amount of computation resources required to process data for above applications make cloud computing a suitable technology but also face challenges in adopting it due to its recency, impact on green computing and reluctance to transform from legacy computing systems to new paradigms like cloud computing. We critically discuss these challenges and suggest possible solutions.