Data from Chinese Academy of Sciences Provide New Insights into Flood Risk Management (Automatic Identification of Buildings Vulnerable To Debris Flows In Sichuan Province, China, By Gis Analysis and Deep Encoding Network Methods): Risk Management – Flood Risk Management

2022 JUL 08 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- Current study results on Risk Management - Flood Risk Management have been published. According to news reporting out of Chengdu, People’s Republic of China, by NewsRx editors, research stated, “Debris flows commonly cause tremendous damage to buildings in mountainous areas. The identification of buildings susceptible to debris flows is vital for settlement risk management.”

Funders for this research include National Natural Science Foundation of China (NSFC), Research on Intelligent Monitoring and Early Warning Technology of Debris Flow on Sichuan-Tibet Railway.

Our news journalists obtained a quote from the research from the Chinese Academy of Sciences, “The efficient identification method is a major issue limiting the targeted regional policy setting. By combining geographic information system (GIS) and Deep Encoding Network (DE-Net) methods, we proposed an automatic identification method for buildings highly susceptible to debris flows with large-scale digital elevation data and high-resolution remote sensing imagery. The judgment criteria were based on a vulnerability matrix containing different threshold values of the horizontal distance (HD) and vertical distance (VD) between buildings and channels obtained from the statistics of 362 buildings destroyed by 23 debris flows and the maximum debris flow depths of 26 events, respectively. Five steps, which are debris flow channel extraction, building extraction, building cluster segmentation, distance calculation, and building classification, were implemented in the method. A case study in Puge County, Sichuan Province, demonstrated the high identification potential of the method for buildings susceptible to debris flows in large areas with only scarce information available.”

According to the news editors, the research concluded: “The identification results provide valuable information regarding high-risk residential areas to governments and facilitate targeted measure design in these areas in the initial planning stage.”

For more information on this research see: Automatic Identification of Buildings Vulnerable To Debris Flows In Sichuan Province, China, By Gis Analysis and Deep Encoding Network Methods. Journal of Flood Risk Management, 2022. Journal of Flood Risk Management can be contacted at: Wiley, 111 River St, Hoboken 07030-5774, NJ, USA. (Wiley-Blackwell - http://www.wiley.com/; Journal of Flood Risk Management - http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1753-318X)

Our news journalists report that additional information may be obtained by contacting Kaiheng Hu, Chinese Academy of Sciences, Key Lab Mt Hazards & Earth Surface Proc, Chengdu, People’s Republic of China. Additional authors for this research include Li Wei and Jin Liu.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.1111/jfr3.12830. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.

(Our reports deliver fact-based news of research and discoveries from around the world.)