Working towards an Improved Monitoring Infrastructure to support Disaster Management, Humanitarian Relief and Civil Security

Within this paper experiences and results from the work in the context of the European Initiative on Global Monitoring for Environment and Security (GMES) as they were gathered within the German Remote Sensing Data Center (DFD) are reported. It is described how data flows, analysis methods and information networks can be improved to allow better and faster access to remote sensing data and information in order to support the management of crisis situations. This refers to all phases of a crisis or disaster situation, including preparedness, response and recovery. Above the infrastructure and information flow elements, example cases of different crisis situations in the context of natural disasters, humanitarian relief activities and civil security are discussed. This builds on the experiences gained during the very active participation in the network of Excellence on Global Monitoring for Stability and Security (GMOSS), the GMES Service Element RESPOND, focussing on Humanitarian Relief Support and supporting the International Charter on Space and Major Disasters as well as while linking closely to national, European and international entities related to civil human security. It is suggested to further improve the network of national and regional centres of excellence in this context in order to improve local, regional and global monitoring capacities. Only when optimum interoperability and information flow can be achieved among systems and data providers on one hand side and the decision makers on the other, efficient monitoring and analysis capacities can be established successfully

NON-PARAMETRIC STATISTICAL APPROACH TO CORRECT SATELLITE RAINFALL DATA IN NEAR-REAL-TIME FOR RAIN BASED FLOOD NOWCASTING

Floods resulting from intense rainfall are one of the most disastrous hazards in many regions of the world since they contribute greatly to personal injury and to property damage mainly as a result of their ability to strike with little warning. The possibility to give an alert about a flooding situation at least a few hours before helps greatly to reduce the damage. Therefore, scores of flood forecasting systems have been developed during the past few years mainly at country level and regional level. Flood forecasting systems based only on traditional methods such as return period of flooding situations or extreme rainfall events have failed on most occasions to forecast flooding situations accurately because of changes on territory in recent years by extensive infrastructure development, increased frequency of extreme rainfall events over recent decades, etc. Nowadays, flood nowcasting systems or early warning systems which run on real- time precipitation data are becoming more popular as they give reliable forecasts compared to traditional flood forecasting systems. However, these kinds of systems are often limited to developed countries as they need well distributed gauging station networks or sophisticated surface-based radar systems to collect real-time precipitation data. In most of the developing countries and in some developed countries also, precipitation data from available sparse gauging stations are inadequate for developing representative aerial samples needed by such systems. As satellites are able to provide a global coverage with a continuous temporal availability, currently the possibility of using satellite-based rainfall estimates in flood nowcasting systems is being highly investigated. To contribute to the world's requirement for flood early warning systems, ITHACA developed a global scale flood nowcasting system that runs on near-real-time satellite rainfall estimates. The system was developed in cooperation with United Nations World Food Programme (WFP), to support the preparedness phase of the WFP like humanitarian assistance agencies, mainly in less developed countries. The concept behind this early warning system is identifying critical rainfall events for each hydrological basin on the earth with past rainfall data and using them to identify floodable rainfall events with real time rainfall data. The individuation of critical rainfall events was done with a hydrological analysis using 3B42 rainfall data which is the most accurate product of Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) dataset. These critical events have been stored in a database and when a rainfall event is found in real-time which is similar or exceeds the event in the database an alert is issued for the basin area. The most accurate product of TMPA (3B42) is derived by applying bias adjustments to real time rainfall estimates using rain gauge data, thus it is available for end-users 10-15 days after each calendar month. The real time product of TMPA (3B42RT) is released approximately 9 hours after real-time and lacks of such kind of bias adjustments using rain gauge data as rain gauge data are not available in real time. Therefore, to have reliable alerts it is very important to reduce the uncertainty of 3B42RT product before using it in the early warning system. For this purpose, a statistical approach was proposed to make near real- time bias adjustments for the near real time product of TMPA (3B42RT). In this approach the relationship between the bias adjusted rainfall data product (3B42) and the real-time rainfall data product (3B42RT) was analyzed on the basis of drainage basins for the period from January 2003 to December 2007, and correction factors were developed for each basin worldwide to perform near real-time bias adjusted product estimation from the real-time rainfall data product (3B42RT). The accuracy of the product was analyzed by comparing with gauge rainfall data from Bangladesh and it was found that the uncertainty of the product is less even than the most accurate product of TMPA dataset (3B42

A low cost mobile mapping system (LCMMS) for field data acquisition: a potential use to validate aerial/satellite building damage assessment

Among the major natural disasters that occurred in 2010, the Haiti earthquake was a real turning point concerning the availability, dissemination and licensing of a huge quantity of geospatial data. In a few days several map products based on the analysis of remotely sensed data-sets were delivered to users. This demonstrated the need for reliable methods to validate the increasing variety of open source data and remote sensing-derived products for crisis management, with the aim to correctly spatially reference and interconnect these data with other global digital archives. As far as building damage assessment is concerned, the need for accurate field data to overcome the limitations of both vertical and oblique view satellite and aerial images was evident. To cope with the aforementioned need, a newly developed Low-Cost Mobile Mapping System (LCMMS) was deployed in Port-au-Prince (Haiti) and tested during a five-day survey in FebruaryMarch 2010. The system allows for acquisition of movies and single georeferenced frames by means of a transportable device easily installable (or adaptable) to every type of vehicle. It is composed of four webcams with a total field of view of about 180 degrees and one Global Positioning System (GPS) receiver, with the main aim to rapidly cover large areas for effective usage in emergency situations. The main technical features of the LCMMS, the operational use in the field (and related issues) and a potential approach to be adopted for the validation of satellite/aerial building damage assessments are thoroughly described in the articl

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio