The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLIV-M-2-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIV-M-2-2020, 25–28, 2020
https://doi.org/10.5194/isprs-archives-XLIV-M-2-2020-25-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIV-M-2-2020, 25–28, 2020
https://doi.org/10.5194/isprs-archives-XLIV-M-2-2020-25-2020

  17 Nov 2020

17 Nov 2020

A METHOD TO GENERATE FLOOD MAPS IN 3D USING DEM AND DEEP LEARNING

A. Gebrehiwot1 and L. Hashemi-Beni2 A. Gebrehiwot and L. Hashemi-Beni
  • 1Applied Science and Technology Ph.D. Program, Department of Built Environment, North Carolina A&T State University, USA
  • 2Geomatics Program, Department of Built Environment, North Carolina A&T State University, USA

Keywords: Floods, Remote Sensing, Convolutional Neural Networks, UAV, Structure from Motion, LiDAR

Abstract. High-resolution remote sensing imagery has been increasingly used for flood applications. Different methods have been proposed for flood extent mapping from creating water index to image classification from high-resolution data. Among these methods, deep learning methods have shown promising results for flood extent extraction; however, these two-dimensional (2D) image classification methods cannot directly provide water level measurements. This paper presents an integrated approach to extract the flood extent in three-dimensional (3D) from UAV data by integrating 2D deep learning-based flood map and 3D cloud point extracted from a Structure from Motion (SFM) method. We fine-tuned a pretrained Visual Geometry Group 16 (VGG-16) based fully convolutional model to create a 2D inundation map. The 2D classified map was overlaid on the SfM-based 3D point cloud to create a 3D flood map. The floodwater depth was estimated by subtracting a pre-flood Digital Elevation Model (DEM) from the SfM-based DEM. The results show that the proposed method is efficient in creating a 3D flood extent map to support emergency response and recovery activates during a flood event.