Abstract
Many people use smartphone cameras to record their living environments through captured images, and share aspects of their daily lives on social networks, such as Facebook, Instagram, and Twitter. These platforms provide volunteered geographic information (VGI), which enables the public to know where and when events occur. At the same time, image-based VGI can also indicate environmental changes and disaster conditions, such as flooding ranges and relative water levels. However, little image-based VGI has been applied for the quantification of flooding water levels because of the difficulty of identifying water lines in image-based VGI and linking them to detailed terrain models. In this study, flood detection has been achieved through image-based VGI obtained by smartphone cameras. Digital image processing and a photogrammetric method were presented to determine the water levels. In digital image processing, the random forest classification was applied to simplify ambient complexity and highlight certain aspects of flooding regions, and the HT-Canny method was used to detect the flooding line of the classified image-based VGI. Through the photogrammetric method and a fine-resolution digital elevation model based on the unmanned aerial vehicle mapping technique, the detected flooding lines were employed to determine water levels. Based on the results of image-based VGI experiments, the proposed approach identified water levels during an urban flood event in Taipei City for demonstration. Notably, classified images were produced using random forest supervised classification for a total of three classes with an average overall accuracy of 88.05%. The quantified water levels with a resolution of centimeters (<3-cm difference on average) can validate flood modeling so as to extend point-basis observations to area-basis estimations. Therefore, the limited performance of image-based VGI quantification has been improved to help in flood disasters. Consequently, the proposed approach using VGI images provides a reliable and effective flood-monitoring technique for disaster management authorities.
Highlights
Much evidence shows that rainfall has intensified globally in recent years [1,2]
Within only a few hours, considerable amounts of rainfall can occur in an urban area, leading to large amounts of water in the drainage system
The proposed water level detection using volunteered geographic information (VGI) involves two processes: identifying water lines in an image-based VGI and measuring the water level based on photogrammetric principles
Summary
Much evidence shows that rainfall has intensified globally in recent years [1,2]. Within only a few hours, considerable amounts of rainfall can occur in an urban area, leading to large amounts of water in the drainage system. The characteristics of a flash flood can be estimated using simulation models for urban areas, such as SOBEK [3], SWMM [4], and Flash Flood Guidance [5,6] These models are computed based on their requisition of a small area, uniform rainfall, and an operating drainage system. Remote sensing data provide geographical identification of flooding areas, and combines with local hydrological monitoring data to effectively predict or restore flooding impacts. These satellite telemetry spatial data were mostly presented in meters of ground resolution. Satellite and airborne optical and radar images are not suitable for detecting the water level on a city road, especially under severe weather
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
