Abstract:The analysis of remote sensing data to assess geohazards is being improved by web-based platforms and collaborative projects, such as the Geohazard Exploitation Platform (GEP) of the European Space Agency (ESA). This paper presents the evaluation of a surface velocity map that is generated by this platform. The map was produced through an unsupervised Multi-temporal InSAR (MTI) analysis applying the Parallel-SBAS (P-SBAS) algorithm to 25 ENVISAT satellite images from the South of Spain that were acquired between 2003 and 2008. This analysis was carried out using a service implemented in the GEP called "SBAS InSAR". Thanks to the map that was generated by the SBAS InSAR service, we identified processes not documented so far; provided new monitoring data in places affected by known ground instabilities; defined the area affected by these instabilities; and, studied a case where GEP could have been able to help in the forecast of a slope movement reactivation. This amply demonstrates the reliability and usefulness of the GEP, and shows how web-based platforms may enhance the capacity to identify, monitor, and assess hazards that are associated to geological processes.

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Earth Observation has proven to be a synoptic and objective source of information to derive crisis and damage maps. In case of flood events, often characterized by weather conditions which prevent the possibility of exploiting data acquired by optical sensors, synthetic aperture radar (SAR) sensors become the only space-born source of information due to their all-weather capability. In order to assure the delivery of damage maps as soon as possible after a disaster, the access and the exploitation of SAR data must be accelerated and simplified with respect to the current procedures. In this context, two issues needed to be addressed: fast access to large data archives, and provision of near real-time on demand processing services. This paper presents a near real-time SAR processing service to support the mapping of flooded areas. The service exploits Grid technology to manage large volumes of data and to provide the computational resources to cope with SAR processing demanding tasks. The algorithm for the implemented orthorectification of the final products is presented. The validation of the derived products shows a reliable accuracy for co-registration of half a pixel. The geolocation accuracy resulted below 100 m. The service makes a significant contribution to accelerating the access and exploitation of ESA SAR data.

Jakarta is the capital of Indonesia and is home to approximately 10 million people on the coast of the Java Sea. The subsidence due to groundwater extraction, increased development, natural consolidation of soil and tectonics in Jakarta has been known since the early part of the 20 th century. Evidence of land subsidence exists through monitoring with GPS, level surveys and preliminary InSAR investigations [1].World Bank studies conservatively estimate land subsidence in Jakarta occurring at an average rate of 5 cm per year, and in some areas, over 1 meter was already observed. Recent studies of land subsidence found that while typical subsidence rates were 7.5-10 cm a year, in localized areas of North Jakarta subsidence in the range 15-25 cm a year was occurring, which if sustained, would result in them sinking to 4 to 5 meters below sea level by 2025. Land subsidence will require major interventions, including increased pumping, dikes and most likely introducing major infrastructure investment for sea defence [1].With the increasing prevalence of Earth Observation (EO), the World Bank and the European Space Agency (ESA) have set up a partnership that aims at highlighting the potential of EO information to support the monitoring and management of World Bank projects. It in this framework that was defined the EOWorld projects [2]. Altamira Information, company specialized in ground motion monitoring, has managed one of those projects, focusing on the assessment of land subsidence in Jakarta.

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