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Automated Indunation Mapping: Comparison of Methods | IEEE Conference Publication | IEEE Xplore

Automated Indunation Mapping: Comparison of Methods


Abstract:

High-resolution imagery is increasingly used to detect flooded areas during a crisis situation. The article presents a comparison of four image classification methods for...Show More

Abstract:

High-resolution imagery is increasingly used to detect flooded areas during a crisis situation. The article presents a comparison of four image classification methods for flood extent mapping. The methods include Random Forest (RF), support vector machine (SVM), fully convolutional network (FCN), and normalized difference water index (NDWI). High-resolution UAV imagery collected during Hurricane Matthew (2016) flood events were used to evaluate the classification methods for generating an accurate flood extent map. In this study, a fully convolutional network fine-tuned to segment the inundation areas. RF, SVM, and NDWI are implemented using the same dataset used for mapping flood extents. The results show that the FCN achieved an overall accuracy of 97.72%, followed by NDWI with 96.0%, SVM with 88.9%, and 87.8 % of RF. The results imply that FCN is more efficient than RF, SVM, and NDWI on generating real-time flood extent maps.
Date of Conference: 26 September 2020 - 02 October 2020
Date Added to IEEE Xplore: 17 February 2021
ISBN Information:

ISSN Information:

Conference Location: Waikoloa, HI, USA

1. Introduction

Flooding is a severe hazard, which poses a great threat to human life and property. Generating flood extent maps during extreme flood events is vital for planning and efficient management of affected areas [1]. Detecting non-inundation areas are also equally important because these areas can serve as temporary shelters for the nearby affected areas. Several jurisdictions have begun considering the feasibility of relocating residential, commercial, and municipal structures, and the flood extent maps help to better understanding potential sites where relocation might be feasible.

References

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