Periodic Reporting for period 1 - MUSA (Monitoring built-Up area from SAtellite)
Berichtszeitraum: 2017-09-01 bis 2018-08-31
Ground displacements in the form of settlements, landslides and sudden collapses are frequent phenomena that occur as a response to natural features of the soil and the quality of the foundation, with the potential to cause significant damage to buildings and infrastructures. This is why the early detection and monitoring of such deformation patterns help to prevent and mitigate risk in densely inhabited areas, providing a valuable information to effectively take decisions. In advanced geomatics, Differential Synthetic Aperture Radar Interferometry (DInSAR) techniques provide a non-invasive instrument to remotely detect, map and monitor deformation phenomena affecting urban areas. Consequently, DInSAR techniques are used to generate velocity maps and displacements time-series for a large number of measurement points and long observation periods.
Survey Lab is a Spin-Off University of Rome that develops and commercializes innovative services for the mapping and monitoring of uninhabited areas, buildings and infrastructures. Recently, Survey Lab has worked in the I.MODI project (2016-2018), focused in developing a system to monitor ground displacements and model deformation of civil structures using EO data. In line with its mission, through the MUSA project, Survey Lab is aimed to obtain quantitative indicators on the data quality used for the detection and monitoring of displacements, as well as to the analysis of spatio-temporal deformation trends. To accomplish this, the MUSA project focus in the development of advanced geostatistics tools to model the spatial distribution of the information (displacements and displacement rates) generated by applying DInSAR techniques on data provided with different spatial and temporal resolutions.
Survey Lab is a Spin-Off University of Rome that develops and commercializes innovative services for the mapping and monitoring of uninhabited areas, buildings and infrastructures. Recently, Survey Lab has worked in the I.MODI project (2016-2018), focused in developing a system to monitor ground displacements and model deformation of civil structures using EO data. In line with its mission, through the MUSA project, Survey Lab is aimed to obtain quantitative indicators on the data quality used for the detection and monitoring of displacements, as well as to the analysis of spatio-temporal deformation trends. To accomplish this, the MUSA project focus in the development of advanced geostatistics tools to model the spatial distribution of the information (displacements and displacement rates) generated by applying DInSAR techniques on data provided with different spatial and temporal resolutions.
At end of the project the tool system contained different advanced statistic tools was completed. The system architecture, including the input data, output, system components, work flows, user interfaces and instructions were developed and delivered in D2.2 at the end of the project. These tools provide the implementation of the new processes in the value chain of Survey Lab, which can be performed in a simple and almost automatic way to generate new products in the form of reports and graphics to be delivered.
These products consist of:
- Quality maps of the DInSAR processing results
- Interpolation maps and with their quality report
- Decomposed time-series and short-term forecast
- Preliminary seismic vulnerability maps
- 1Preliminary seismic risk indicator maps
These products consist of:
- Quality maps of the DInSAR processing results
- Interpolation maps and with their quality report
- Decomposed time-series and short-term forecast
- Preliminary seismic vulnerability maps
- 1Preliminary seismic risk indicator maps
After MUSA, processes of high quality to extend the spatial information from discrete data are enabled and they can be nimbly and effectively applied. An advanced geostatistical module has been developed that permit the user to automatically apply various interpolation methods and validate them, giving reliability results and selecting the best method for the sampled information with the minimum time-consuming. The results of the interpolation process will also depend of the characteristics and quality of the input data which were also considered to be analysed by the development of an additional tool. Thus, the expert can gather major information about the quality of the base datasets and the expected processing results. In addition, considering the valuable time component of the SAR data, suitable technics for time-series analysis were scripted providing a convenient access to the modeling of time-series components (trend, seasonal and residual).
The findings after applying this type of analysis are necessary to understand and predict the evolution of natural and handmade-induced phenomena on built-up areas displacements. Further, for the case of seismic phenomena, a module to assess vulnerability and risk indicators (expected damage) by using a reduced number of needed variables has been developed. Altogether, the new toolset created through the development of the MUSA project enables useful procedures to evaluate the spatial-temporal evolution at several scales of displacement phenomena affecting urban areas. The tangible results and services to be offered after MUSA will have a noticeable impact for the society, allowing policy-makers to have a trustworthy source with relevant information to be used in risk assessment and management, as they will be enabled to take more convenient decisions on time. In the same way, the access to this information by the private sector or individual stakeholders will provide them with useful data to refine and improve their market strategies by considering risk factors related to the expected damage on properties and civil infrastructures.
The findings after applying this type of analysis are necessary to understand and predict the evolution of natural and handmade-induced phenomena on built-up areas displacements. Further, for the case of seismic phenomena, a module to assess vulnerability and risk indicators (expected damage) by using a reduced number of needed variables has been developed. Altogether, the new toolset created through the development of the MUSA project enables useful procedures to evaluate the spatial-temporal evolution at several scales of displacement phenomena affecting urban areas. The tangible results and services to be offered after MUSA will have a noticeable impact for the society, allowing policy-makers to have a trustworthy source with relevant information to be used in risk assessment and management, as they will be enabled to take more convenient decisions on time. In the same way, the access to this information by the private sector or individual stakeholders will provide them with useful data to refine and improve their market strategies by considering risk factors related to the expected damage on properties and civil infrastructures.