Remote sensing as tool for development of landslide databases: The case of the Messina Province (Italy) geodatabase

Landslide geodatabases, including inventories and thematic data, today are fundamental tools for national and/or local authorities in susceptibility, hazard and risk management. A well organized landslide geo-database contains different kinds of data such as past information (landslide inventory maps), ancillary data and updated remote sensing (space-borne and ground based) data, which can be integrated in order to produce landslide susceptibility maps, updated landslide inventory maps and hazard and risk assessment maps. Italy is strongly affected by landslide phenomena which cause victims and significant economic damage to buildings and infrastructure, loss of productive soils and pasture lands. In particular, the Messina Province (southern Italy) represents an area where landslides are recurrent and characterized by high magnitude, due to several predisposing factors (e.g. morphology, land use, lithologies) and different triggering mechanisms (meteorological conditions, seismicity, active tectonics and volcanic activity). For this area, a geodatabase was created by using different monitoring techniques, including remote sensing (e.g. SAR satellite ERS1/2, ENVISAT, RADARSAT-1, TerraSAR-X, COSMO-SkyMed) data, and in situ measurements (e.g. GBInSAR, damage assessment). In this paper a complete landslide geodatabase of the Messina Province, designed following the requirements of the local and national Civil Protection authorities, is presented. This geo-database was used to produce maps (e.g. susceptibility, ground deformation velocities, damage assessment, risk zonation) which today are constantly used by the Civil Protection authorities to manage the landslide hazard of the Messina Province

Soil threats in Europe

Although there is a large body of knowledge available on soil threats in Europe, this knowledge is fragmented and incomplete, in particular regarding the complexity and functioning of soil systems and their interaction with human activities. The main aim of RECARE is to develop effective prevention, remediation and restoration measures using an innovative trans-disciplinary approach, actively integrating and advancing knowledge of stakeholders and scientists in 17 Case Studies, covering a range of soil threats in different bio-physical and socio-economic environments across Europe. Existing national and EU policies will be reviewed and compared to identify potential incoherence, contradictions and synergies. Policy messages will be formulated based on the Case Study results and their integration at European level. A comprehensive dissemination and communication strategy, including the development of a web-based Dissemination and Communication Hub, will accompany the other activities to ensure that project results are disseminated to a variety of stakeholders at the right time and in the appropriate formats to stimulate renewed care for European soils.JRC.H.5-Land Resources Managemen

Applications of Satellite Earth Observations section - NEODAAS: Providing satellite data for efficient research

The NERC Earth Observation Data Acquisition and Analysis Service (NEODAAS) provides a central point of Earth Observation (EO) satellite data access and expertise for UK researchers. The service is tailored to individual users’ requirements to ensure that researchers can focus effort on their science, rather than struggling with correct use of unfamiliar satellite data

Satellite monitoring of harmful algal blooms (HABs) to protect the aquaculture industry

Harmful algal blooms (HABs) can cause sudden and considerable losses to fish farms, for example 500,000 salmon during one bloom in Shetland, and also present a threat to human health. Early warning allows the industry to take protective measures. PML's satellite monitoring of HABs is now funded by the Scottish aquaculture industry. The service involves processing EO ocean colour data from NASA and ESA in near-real time, and applying novel techniques for discriminating certain harmful blooms from harmless algae. Within the AQUA-USERS project we are extending this capability to further HAB species within several European countries

Spaceborne InSAR for dam stability

PhD ThesisThis study evaluates the feasibility of the use of satellite radar for dam deformation monitoring. Spaceborne Interferometric Synthetic Aperture Radar (InSAR) has long been used to monitor geohazards, including earthquakes, landslides, and volcanos. However, few studies have recently investigated its feasibility for localised deformation monitoring such as of earth dams. Here two case studies are presented of the monitoring of dams in Iraq. Mosul dam is one of the most dangerous dams in the world. Previous studies have reported that over a million human lives would be potentially at risk should dam failure occur. Therefore, investigation of its health using precise and continuous observations is crucial. This was achieved with two independent geodetic datasets from levelling and InSAR, and the results show continuous vertical displacements on the dam crest due to the dissolution of foundations. Vertical displacement rate estimates from levelling and InSAR for the period 2003-2010 are in good agreement, with a correlation of 0.93 and an RMSE of ± 1.7 mm. For the period 2014- 2017, the correlation is 0.95 and the RMSE is ± 0.9 mm. The movement of the dam was evaluated using settlement index which is not referring to critical instability of the dam. However, the spatial and temporal displacement anomalies emphasize that a careful monitoring and remedial work should continue. The continuous displacement in the dam foundation could loosen the compaction of the embankment and result in internal erosion. In a separate study, Darbandikhan dam was monitored using a global positioning system (GPS), levelling, and Sentinel-1 data to evaluate its stability after the 2017 Mw 7.3 Sarpol-e Zahab earthquake. The large gradient of the dam’s displacements on its crest hindered the estimation of co-seismic displacements using medium-resolution SAR data. However, Sentinel-1 images were sufficient to examine the dam’s stability before and after the earthquake. The results show that the dam was stable between October 2014 and November 2017, but after the earthquake continuous subsidence on the dam crest occurred between November 2017 and March 2018. For the first time the stability of the Mosul and Darbandikhan dams has been assessed using an integration of InSAR and in-situ observations. Different types of deformations were recognized, which helped in interpreting the dam’s deformation mechanismsMinistry of Higher Education (MOHE) and the State Commission of Surveys (SCOS) in Ira

Earthquake damage analysis and mapping with the use of satellite remote sensing

After a seismic event a rapid and accurate evaluation of the impact of the damages is extremely important. Such evaluation may support rescue team operations and identify the actual dimensions of the event and its potential impact on the territory and on the population. The use of Earth Observation (EO) data has been significantly increasing in the last years, particularly the use of Very High Resolution (VHR) optical images, which are able to provide detailed information at single building level. However, most of the existing approaches mainly rely on the use of remote sensing data, either optical or SAR (Synthetic Aperture Radar), and perform a classification based on change detection techniques. In this work we aim at creating a flexible tool that is able to perform a damage classification taking into account, not only EO available data, but also additional information that is supposed to be available even before the occurrence of any seismic event (a-priori data). This data includes soil vulnerability, which can play a very important role on local amplification effects as well as structural information of the individual building. Such approach, pursued within the framework of the EC-FP7 funded project APhoRISM (Advanced Procedures for Volcanic and Seismic Monitoring- grant agreement n. 606738) aims at generating maps of damage caused by a seism using both satellite remote sensing data (SAR and/or optical sensors) and ground and structural data. The basic idea is to integrate both satellite remote sensing data (SAR and/or optical sensors) with structural and ground data to improve the accuracy and limit false alarms that derive by the use of EO data only. In order to do this, we first review the general approach and methods to data fusion and we identify what is the level of information that is better to merge referring to our goals. We also examine how the structural information is evaluated and we then focus on the description of Bayesian approaches and, more specifically, of Bayesian networks. Such type of graphical approach for our data fusion tool is implemented to assess post-earthquake building damage. We validate our Bayesian networks against the real test case based on L’ Aquila (Italy) earthquake which took place on April 6, 2009. In this case, we have a set of data available to build the Ground Truth validation test set. For what concerns remote sensing data, for this event, both COSMO-Skymed Radar and Quickbird VHR optical sensors were available thus allowing a complete remote sensing dataset. The in-situ information, though fragmentary, was built using data coming from different sources, mainly from INGV (Italian Geophysical and Volcano Institute) and the Italian Civil Protection Department. The promising results of different Bayesian networks are presented showing the step-by-step approach adopted, which aims at generalising the methodology in order to further implement the network in future cases