2016 Multi-Scale Remote Sensing Information System Data Establishment, Expansion and Maintenance

ABSTRACT

Taiwan, with complex geological conditions, is located in the region where natural disasters happen frequently, like typhoons. Therefore, it is necessary to positively integrate all kinds of remote sensing data and geospatial information to protect people’s life and property, as well as efficiently use them upon disaster prevention and rescue. In this project Soil and sand disaster spatial information system has been set up properly and run well. In the past five years, the system has been updated and maintained routinely. Furthermore, mobile platform system and emergency task planning system have been built up for providing information about debris flow hazard forecast and alert for disaster emergency response during a disaster. After a disaster, data from satellite and UAV imagery has been used to generate spatial information in disaster areas.

Because of Formosat-2 retired unexpectedly, Landsat-8, SPOT-6, SPOT-7, GeoEye-1 and THEOS satellite data have been used in this year. After attacked by 0206 earthquake and other events, the images and analysis from Formosat-2 satellite of landscape variations were resulted in reports. Meanwhile, UAV was applied in acquiring photos of main disaster areas, such as Guangsing of Xindian District in New Taipei City, and these photos were orthorectified and published. Three places with early and late of digital surface model provided the volume of earthmoving.

Hereafter, “Multi-Stage Remote Sensing GIS System” and “Historical Debris Flow Database” have been integrated and upgraded, with intention to combine advantages of both platforms and provide more complete services. At the same time, many of disaster-related personnel must go to the disaster site during disaster investigation, in order to improve the efficiency of disaster prevention information transmission, the establishment of soil and sand disaster spatial information system mobile version, based on OpenLayer layer processing technology, excluding Google API limitations. And the allocation of human resources is also an important part of disaster prevention. Disaster response task integration module can help to provide integration and transmission of event information. The most important thing is to integrate human resource allocation and reduce the repetition of disaster investigation.

Moreover, historical data and landslide susceptibility method have been used to build a landslide hazard model (LHM) for landslide hazard nowcast research in this project. For the cases such as Typhoon Meranti this year, Central Weather Bureau quantitative precipitation forecast data have been used to provide nowcasting of landslide. The accuracy of LHM was assessed in details using the case of Wu-Lai area after Typhoon Saola and Typhoon Soulik, which validated this approach of LHM analysis. The average accuracy of these events is about 75 %. Through integrating and applying data of disaster prediction, this study attempts to enhance the ability of disaster analysis and interpretation and also make the most of internet spatiotemporal platform on the issue of disaster prevention.

Keywords:multi-stage remote sensing, geospatial information system, debris flow, satellite, UAV, landslide susceptibility analysis