Rapidmap – rapid mapping and information dissemination for disasters using remote sensing and geoinformation
- 1ETH Zurich, Institute of Geodesy and Photogrammetry, Wolfgang-Pauli-Str. 15, 8093, Zurich, Switzerland
- 2Tokai University, School of Information and Science & Technology, 4-1-1 Kitakaname Hiratsuka, Kanagawa 259-1292, Japan
- 3Bruno Kessler Foundation, 3D Optical Metrology unit, via Sommarive 18, 38123, Trento, Italy
- 4Leibniz Universität Hannover, Institute of Photogrammetry and GeoInformation, Nienburgerstrasse 1, 30167 Hannover, Germany
- 5Nihon University, College of Engineering, I Computer Science, 1 Nakagawara, Tokusada, Tamura-machi, Koriyama, Fukushima, 963-8642 Japan
Keywords: Multi-modal data, Hazards, Change Detection, Data Fusion, Data Co-registration, Pattern Recognition, Near-Real- Time monitoring, Decision Support Systems
Abstract. FP7 INCO project frame for enhancing research cooperation between European countries and Japan on two topics, one of which is Resilience Against Disasters. The project started in June 2013 and has a duration of 2 years. In the paper, we will outline the aims of the project, methodologies and techniques to be developed and some test data.
Remote Sensing (RS) and Geographic Information System (GIS) are powerful technologies for collecting useful information on the damages of disasters in short time. However, since many different types of RS data are available (satellite, aerial, UAV, terrestrial), data co-registration, information integration and feature extraction need reliable and advanced methodologies. In the RAPIDMAP project, we will develop practical ways to integrate RS data processing tools in near-real-time and allow users to use this data soon after the disasters by means of WebGIS tools. This will help not only decision makers but also end-users in the disaster area. The key components of this project are:
(1) Near-real-time monitoring: the procedure of near-real-time monitoring with satellites as well as Unmanned Airborne Vehicles (UAV) will be set up and demonstrated.
(2) Data co-registration: in disasters, various images as well as maps come from different sources. The co-registration of multiple images is a key technology for information integration. In this project, a system to co-register multiple images in near-real-time will be developed.
(3) Data fusion and change detection: one of the advantages of RS is to collect information with multiple sensors. Various methods for fusing optical with active microwave (SAR) sensor data for information extraction and change detection will be developed.
(4) Decision Support System (DSS) based on WebGIS technologies: the collected and integrated information has to be easily accessible and visible by decision makers and end-users in near-real-time and worldwide. By using WebGIS technologies, wireless networks and portable terminals, a DSS will allow easy access, retrieval and visualization of all information (fused data, images, maps, etc.) in very short time after data collection and processing.
The project will be practically tested and demonstrated at the Tohoku area in Japan and another test site, which were recently affected by large disasters.