Title: Urban waterlogging monitoring and early warning based on video images

Authors: Fengchang Xue; Juan Tian; Xiaoyi Song; Yan Yan

Addresses: School of Remote Sensing and Geomatics, Nanjing University of Information Science and Technology, No. 219, Ning Liu Road, Pukou District, 210044 Nanjing, China ' School of Remote Sensing and Geomatics, Nanjing University of Information Science and Technology, No. 219, Ning Liu Road, Pukou District, 210044 Nanjing, China ' School of Remote Sensing and Geomatics, Nanjing University of Information Science and Technology, No. 219, Ning Liu Road, Pukou District, 210044 Nanjing, China ' Meteorological Bureau of Liangyuan District, No. 66, East Huochang Road, Liangyuan District, 476000 Shangqiu, China

Abstract: Urban flood disaster causes serious loss to urban residents. Timely access to urban waterlogging conditions has great significance for disaster prevention and disaster relief. Owing to the time resolution limitation of data, the traditional monitoring of urban flood disasters using remote sensing imagery cannot realise real-time automatic monitoring and continuous monitoring of key disaster areas. This paper selects road monitoring video, uses image difference operation and support vector machine (SVM) algorithm to identify the waterlogging area, and uses the region growing method to extract the waterlogging area range. The research results show that this method can be used for continuous monitoring and early warning of urban waterlogging in real time.

Keywords: waterlogging monitoring; road monitoring video; support vector machine; SVM; region growing method.

DOI: 10.1504/IJES.2020.110648

International Journal of Embedded Systems, 2020 Vol.13 No.4, pp.380 - 386

Received: 11 Apr 2019
Accepted: 15 Aug 2019
Published online: 27 Oct 2020 *

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