Satellite‐based flood mapping in the boreal region for improving situational awareness

Abstract Space‐borne remote sensing techniques enable near real‐time mapping of floods cost‐efficiently. Synthetic aperture radar (SAR) and optical sensors are the most suitable for flood detection. However, SAR has become more popular, due to the independence of sunlight and weather conditions, and...

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Bibliographic Details
Published in:Journal of Flood Risk Management
Main Authors: Juval Cohen, Kirsikka Heinilä, Mikko Huokuna, Sari Metsämäki, Jyri Heilimo, Mikko Sane
Format: Article in Journal/Newspaper
Language:English
Published: Wiley 2022
Subjects:
boreal forest
Copernicus Emergency Management Service
flood monitoring
flood risk management
remote sensing
synthetic aperture radar (SAR)
River protective works. Regulation. Flood control
TC530-537
Disasters and engineering
TA495
The Sentinel
Tornio
Northern Finland
Online Access:https://doi.org/10.1111/jfr3.12744
https://doaj.org/article/27013d4d9ecc4502b678803eb45a824e
Description
Summary:Abstract Space‐borne remote sensing techniques enable near real‐time mapping of floods cost‐efficiently. Synthetic aperture radar (SAR) and optical sensors are the most suitable for flood detection. However, SAR has become more popular, due to the independence of sunlight and weather conditions, and the increasing data availability. Typical spring floods occurred in northern Finland during 2018. Various remote sensing sources were utilised for monitoring and damage estimation of the flooding. Floods were mapped with the SAR‐based Finnish Flood Centre's Flood Detection Algorithm (FC‐FloDA), a standard threshold‐based approach applied to Sentinel‐1, and a visual interpretation of Sentinel‐2 images. In addition, flood maps from the Copernicus Emergency Management Service (EMS) and aerial photographs from the city of Tornio were ordered. The flood products and interpretations were compared, and a deeper accuracy assessment was conducted on the FC‐FloDA maps. FC‐FloDA was, in general, the most successful in detecting floods within the test areas. The EMS product and the Sentinel‐1 interpretation worked well in open areas, but did not detect floods in forests. The superiority of Flood Centre's product is mainly based on the adaptation of the algorithm to northern boreal environments and the selection of an optimal polarisation for detecting floods also under tree canopies.

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