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Mega-events imply several city transformations at different scales that could be challenging to be identified and documented. The impacts of such events like Universal Exhibitions are difficult to be identified and tracked in space and over a long period of time. This paper discusses the use of open-source geospatial technologies as innovative tools in support of urban planning and management of digital cities, analysing in particular the case of an international exhibition in the urban landscape. A GIS-based approach is used to design a spatially enabled database, which is essential for implementing advanced analytics in modern smart cities. The pilot project proposes the design and implementation of such georeferenced database for monitoring the urban transformations of the area used for Expo 2015 Milano (Italy). The potential of GIS environment in the consultation process, which allows to obtain different interactive views and to make selections and queries of the data, is explored. The paper also discusses the possibility of publishing such prototype on a shared platform, allowing a larger non-technical audience to follow the urban evolution of the area in a diachronic perspective.

MOCASS (Mass Observation with Cold Atom Sensors in Space) is a study project funded by the Italian Space Agency in the framework of preparatory activities for future missions and payloads of Earth Observation. The idea is to propose a GOCE mission follow-on, launching a unique spacecraft with an on-board gradiometer based on advanced cold atom interferometry (CAI) accelerometers and capable of measuring Earth’s gravity gradients along one or two orthogonal directions. The MOCASS project aims at investigating whether this mission concept can improve GOCE results in terms of accuracy and resolution of the estimated gravity field model, and the capability of detecting mass distribution and monitoring mass variations. To this purpose, firstly the instrument characteristics are defined in terms of long-term stability, accuracy, and spectral responses. Then simulations on gravity field recovery based on the space-wise approach already used for the GOCE data processing are implemented. Finally, an analysis on the geophysical signals that can be detected given the simulated mission performance is made. Simulations were assembled by considering real GOCE orbits at different altitudes, but assuming that a CAI gradiometer is on board the spacecraft. This allows a direct comparison between GOCE and MOCASS performances. Instrumental error spectra were defined depending on the orbit and the orientation of the CAI gradiometer arms, considering both a nadir-pointing satellite and an inertial-pointing one. For each configuration, the effect of the satellite angular velocity was computed from the time series of the GOCE orbit coordinates at different altitudes. The resulting instrumental error shows a flat spectrum in the low frequencies, differently from the one of the GOCE electrostatic accelerometers. On the other hand, the interferometer transfer function introduces a strong correlation between close observations. Given the error spectra and the interferometer integration spectral response, observations of gravity gradients were first simulated and then processed by the space-wise approach, which basically consists in a sequential application of a Wiener filter deconvolution, a local collocation gridding and a spherical harmonic analysis. From Monte Carlo sample statistics, the estimation error of the retrieved gravity field model was evaluated for the different mission configurations, showing an improvement in both accuracy and resolution with respect to GOCE. This estimation error was finally compared with the expected gravity signal from selected geophysical phenomena. In particular, the focus was on the India-Tibet region, which involves important and different movements of mass through time and comprises several different crustal structures. The results show that both time-varying gravity signals, like those due to the Tibet-Himalaya glacier melting and crustal uplift, and static gravity signals, like those due to the India seamounts, could be detected by the MOCASS mission.

MOCASS (Mass Observation with Cold Atom Sensors in Space) is an on-going study project funded by the Italian Space Agency in the framework of preparatory activities for future missions and payloads of Earth Observation. The object of the proposal is an innovative satellite gravity mission based on advanced cold atom interferometry (CAI) accelerometers, with the aim of modelling the static and time-variable gravity field of the Earth with high accuracy and resolution and of monitoring mass variations that occur on and below the Earth surface. The basic idea is a GOCE mission follow-on, launching a unique spacecraft with an on-board instrument capable of measuring some functionals of the Earth gravitational potential. The improvement with respect to the GOCE mission concept can only be achieved by going beyond the technology of electrostatic gradiometers, taking advan- tage of a new generation of sensors, such as cold atom interferometers. In the framework of the MOCASS study, the instrument characteristics are defined in terms of long-term stability, accuracy, and spectral responses. Then simulations on gravity field recovery based on the space-wise approach already used for the GOCE data processing are implemented. Finally an analysis on the geophysical signals that can be detected given the simulated mission performance are performed, with particular attention to hydrologic and tectonic modelling of changing masses. First simulations have already been performed by considering the GOCE orbit parameters but assuming that a CAI gradiometer is on board the spacecraft. This allows direct comparisons between GOCE and MOCASS per- formances. Instrument error spectra have been defined depending on the orbit and CAI configurations, all of them characterized by a flat error spectrum in the low frequencies, differently from the one of the GOCE electrostatic accelerometers. Given the error spectrum and the interferometer integration spectral response, simulated obser- vations have been produced and processed by the space-wise approach, which basically consists in a sequential application of a Wiener filter, a local collocation gridding and a spherical harmonic analysis. From sample statis- tics, the accuracy of the recoverable gravity field model can then be evaluated and compared with the expected gravity signal from selected geophysical phenomena, e.g. orogen geodynamics and glacier melting. Although the study is at this time not complete, these preliminary investigations show promising results.