2015 Multi-Scale Remote Sensing Information System Data Establishment, Expansion and Maintenance

ABSTRACT

Taiwan, with special geological feature, is located at the area where is easy attacked by earthquakes, typhoons and torrential rains. To protect people’s life and property, it is necessary to positively integrate all kinds of remote sensing data and geospatial information, as well as efficiently use them upon disaster prevention and rescue. This project has continuously updated the latest data to “Multi-Stage Remote Sensing GIS System” and “Historical Debris Flow Database,” and maintained both platforms’ functions in the past five years.

After attacked by torrential rain event on May 20th, Typhoon LINFA and CHAN-HOM, Typhoon SOUDELOR and Typhoon DUJUAN, the imagery 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 Zhulun of Sanxia District in New Taipei City, Quchi of Xindian District in New Taipei City, Guangsing of Xindian District in New Taipei City, Zhongzhi of Wulai District in New Taipei City, Hsinsien of Wulai District in New Taipei City, Dashin of Guangfu Township in Hualien County, Jianhe of Taitung City in Taitung County, and these photos were orthorectified and published. Hereafter, “Multi-Stage Remote Sensing GIS System” and “Historical Debris Flow Database” were integrated and upgraded, with intention to combine advantages of both platforms and provide more completed services.

Moreover, historical data and landslide susceptibility method is used to building a landslide hazard model (LHM) for landslide hazard nowcast research in this project. Two historical events of landslide occurred in Shenmu Villiage in Nantou county were used to derive and validate the LHM. For the cases of Typhoon Linfa, Typhoon Soudelor and Typhoon Dujuan in this year, rainfall forecast data were used to provide nowcasting of landslide in Shenmu Villiage. The accuracy of LHM was assessed in details using the case of Wu-Lai area after Typhoon Soudelor, which validate this approach of LHM analysis. 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 GIS platform on the issue of disaster prevention.

Keywords: multi-stage remote sensing, geospatial information system, historical disaster dayabase, debris flow, Formosat-2, UAV, landslide susceptibility analysis