Abstract
Abstract. After large flood incidents in Norway, The Norwegian Water Resources and Energy Directorate (NVE), has the responsibility for documenting the flooded areas. This has so far mainly been performed by utilising aerial images and visual interpretation. Satellite images are a valuable source of additional information as they are able to cover vast areas in each satellite pass. In this paper a fully automated system for detecting and delineating floods with the use of Synthetic Aperture Radar (SAR) images from the Sentinel-1 satellites is presented. In SAR images wet areas and water bodies usually show lower backscatter than dry areas. The flood detection system is thus based on comparing a reference image acquired before the flood with the flood event image. A Sentinel-1 training dataset has been obtained and manually annotated by NVE from three flood events in Norway. This training set has been used to train a random forest (RF) classifier, which outputs a score for each pixel in the SAR image. This score image is thresholded in order to obtain a crude flood detection. Unfortunately, changes in the backscatter may also be triggered by other events such as melting snow and harvested fields of crops. To mitigate such lookalikes, several techniques have been implemented and tested. This includes masking based on size, slope and height above nearest drainage (HAND). The experiments presented show that the system performance is very good. Of the 179 manually labelled flood objects, 168 are detected. The system is being applied operationally at NVE.
Highlights
Every year thousands of lives are affected and billions of dollars are lost in disasters caused by flood events around the world
The largest flood object had an area of 755 pixels, i.e. 0.3 km2, and occurred in the “Inland” flood event
When we evaluated the results with respect to the flood objects, we observe that we are able to detect 168 of 179 flood objects (Table 5)
Summary
Every year thousands of lives are affected and billions of dollars are lost in disasters caused by flood events around the world. Accurate monitoring systems have the potential greatly reducing causalities and economic losses by providing up-to-date information for disaster managers and the population at large. Europe and Norway in particular, have invested substantially in a new European Earth observation program, Copernicus, wherein emergency management is a critical component. This service is based on timely and accurate geospatial information derived from satellite remote sensing. The major benefits of including analysis of satellite data in emergency management is the huge spatial coverage of satellite data, providing better overview of an ongoing emergency situation, and assessment of the potential damages. The information provided by satellite data may be utilised for e.g. resource allocation in the early phases of clean-up work
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