Abstract
Monitoring of rivers is of major scientific and societal importance due to the crucial resource they provide to human activities and the threats caused by flood events. Rapid revisit synthetic aperture radar (SAR) sensors such as Sentinel-1 or the future surface water and ocean topography (SWOT) mission are indispensable tools to achieve all-weather monitoring of water bodies at the global scale. Unfortunately, at the spatial resolution of these sensors, the extraction of narrow rivers is extremely difficult without resorting to exogenous knowledge. This article introduces an innovative river segmentation method from SAR images using a priori databases such as the global river widths from Landsat (GRWL). First, a recently proposed linear structure detector is used to produce a map of likely line structures. Then, a limited number of nodes along the prior river centerline are extracted from the exogenous database and used to reconstruct the full river centerline from the detection map. Finally, an innovative conditional random field approach is used to delineate accurately the river extent around its centerline. The proposed method has been tested on several Sentinel-1 images and on simulated SWOT data. Both visual and qualitative evaluations demonstrate its efficiency.
Highlights
I N THE last five years, two major research works have provided comprehensive worldwide maps of continental water surfaces: the global surface water masks of Pekel et al [1] and global river widths from Landsat (GRWL) of Allen and Pavelsky [2]
Our method has been tested on Sentinel-1 GRD images and on simulated surface water and ocean topography (SWOT) high rate (HR) images
The proposed technique consists of three phases: First, computing the response of a linear feature detector, detecting the centerline using the response and the prior river nodes, and, segmenting the river around the previously detected centerline using a conditional random field (CRF) approach
Summary
I N THE last five years, two major research works have provided comprehensive worldwide maps of continental water surfaces: the global surface water masks of Pekel et al [1] and global river widths from Landsat (GRWL) of Allen and Pavelsky [2] They are based on multispectral Landsat optical images over decades. The Ka-band radar interferometer (KaRIn) of the future surface water and ocean topography (SWOT) mission [3], scheduled for launch in 2022, is an interferometric SAR system that is able to measure water elevation as well Thanks to their short revisit time, these freely available SAR data are expected to play a crucial role in river monitoring in the coming years. Robust and efficient methods to detect narrow rivers in such images are needed
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