Automated global water mapping based on wide-swath orbital synthetic aperture radar

Westerhoff, Rogier; Kleuskens, M. P. H.; Winsemius, Hessel; Huizinga, H. J.; Brakenridge, G. Robert

doi:10.5194/hessd-9-7801-2012

Cited by 12 publications

(16 citation statements)

References 29 publications

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“…A representative index in the drainage based group is the Height Above Nearest Drainage (HAND) index, which was presented by Rennó et al [27] and implemented by Nobre et al [28]. This index also attracted a lot of attention and has been applied in many water detection studies [5,[29][30][31]. This study aims to conduct a comprehensive comparison on MrVBF and HAND indices, especially on their ability to assist surface water mapping using Sentinel-1A dual-polarized SAR data.…”

Section: Study Sitesmentioning

confidence: 99%

“…Synthetic Aperture Radar (SAR) sensors have been widely applied in detecting and monitoring water bodies due to their suitable spatial resolution, as well as the ability to penetrate cloud and vegetation cover [5,6]. Until recently, SAR sensors had a relatively low temporal frequency (about 24-35 days for acquisitions in the same geometric configuration) [7], which hinders the intensive monitoring of surface water variation.…”

Section: Introductionmentioning

confidence: 99%

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A Comparison of Terrain Indices toward Their Ability in Assisting Surface Water Mapping from Sentinel-1 Data

Huang

Nguyen

Zhang

et al. 2017

IJGI

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Abstract:The Sentinel-1 mission provides frequent coverage of global land areas and is hence able to monitor surface water dynamics at a fine spatial resolution better than any other Synthetic Aperture Radar (SAR) mission before. However, SAR data acquired by Sentinel-1 also suffer from terrain effects when being used for mapping surface water, just as other SAR data do. Terrain indices derived from Digital Elevation Models (DEMs) are easy but effective approaches to reduce this kind of interference, considering the close relationship between surface water movement and topography. This study compares two popular terrain indices, namely the Multi-resolution Valley Bottom Flatness (MrVBF) and the Height Above Nearest Drainage (HAND), toward their performance on assisting surface water mapping using Sentinel-1 SAR data. Four study sites with different terrain characteristics were selected to cover a very wide range of topographic conditions. For two of these sites that are floodplain dominated, both normal and flooded scenarios were examined. MrVBF and HAND values for the whole study areas, as well as statistics of these values within water areas were compared. The sensitivity of applying different thresholds for MrVBF and HAND to mask out terrain effect was investigated by adopting quantity disagreement and allocation disagreement as the accuracy indicators. It was found that both indices help improve water mapping, reducing the total disagreement by as much as 1.6%. The HAND index performs slightly better in most of the study cases, with less sensitivity to thresholding. MrVBF classifies low-lying areas with more details, which sometimes makes it more effective in eliminating false water bodies in rugged terrain. It is therefore recommended to use HAND for large scale or global scale water mapping. However, for water detection in complex terrain areas, MrVBF also performs very well.

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Section: Study Sitesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Comparison of Terrain Indices toward Their Ability in Assisting Surface Water Mapping from Sentinel-1 Data

Huang

Nguyen

Zhang

et al. 2017

IJGI

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“…Water monitoring using Synthetic Aperture Radar (SAR) has been the object of study for many researchers [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19]. Due to its all-weather capabilities, and its image acquisition capacity during day or night or in cloudy conditions, SAR imagery offers better alternatives for water mapping than optical imagery [5].…”

Section: Introductionmentioning

confidence: 99%

“…Segmentation algorithms are quite successful but computationally expensive. In many cases, statistical information is combined with digital elevation models [8,14,16], where pixels likely to contain water are first determined based on topographic data and the probability of water is based on histograms of water vs. land pixels in the image, but this requires a coarse water mask to determine the statistics of water pixels. This dependence on a pre-determined water mask and high-resolution digital elevation models makes these methods unusable for mapping small ephemeral water bodies.…”

Section: Introductionmentioning

confidence: 99%

Operational Surface Water Detection and Monitoring Using Radarsat 2

et al. 2016

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Traditional on-site methods for mapping and monitoring surface water extent are prohibitively expensive at a national scale within Canada. Despite successful cost-sharing programs between the provinces and the federal government, an extensive number of water features within the country remain unmonitored. Particularly difficult to monitor are the potholes in the Canadian Prairie region, most of which are ephemeral in nature and represent a discontinuous flow that influences water pathways, runoff response, flooding and local weather. Radarsat-2 and the Radarsat Constellation Mission (RCM) offer unique capabilities to map the extent of water bodies at a national scale, including unmonitored sites, and leverage the current infrastructure of the Meteorological Service of Canada to monitor water information in remote regions. An analysis of the technical requirements of the Radarsat-2 beam mode, polarization and resolution is presented. A threshold-based procedure to map locations of non-vegetated water bodies after the ice break-up is used and complemented with a texture-based indicator to capture the most homogeneous water areas and automatically delineate their extents. Some strategies to cope with the radiometric artifacts of noise inherent to Synthetic Aperture Radar (SAR) images are also discussed. Our results show that Radarsat-2 Fine mode can capture 88% of the total water area in a fully automated way. This will greatly improve current operational procedures for surface water monitoring information and impact a number of applications including weather forecasting, hydrological modeling, and drought/flood predictions.

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“…Several studies showed that SAR images acquired at the higher C-band frequency can also be used for detecting floods in less vegetated areas e.g., [14][15][16][17]. SAR images acquired in Wide Swath (WS) mode by the Advanced SAR (ASAR) onboard ENVISAT, at a spatial resolution of 150 m, were widely used for the monitoring of flood dynamics from local to regional scales [16][17][18][19]. Only 29 ASAR images were acquired in WS mode between November 2002 and March 2012 and just 14 during the rainy seasons due to acquisitions in other modes.…”

Section: Introductionmentioning

confidence: 99%

Monitoring of the Spatio-Temporal Dynamics of the Floods in the Guayas Watershed (Ecuadorian Pacific Coast) Using Global Monitoring ENVISAT ASAR Images and Rainfall Data

Frappart

Bourrel

Brodu³

et al. 2017

Water

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Abstract:The floods are an annual phenomenon on the Pacific Coast of Ecuador and can become devastating during El Niño years, especially in the Guayas watershed (32,300 km 2 ), the largest drainage basin of the South American western side of the Andes. As limited information on flood extent in this basin is available, this study presents a monitoring of the spatio-temporal dynamics of floods in the Guayas Basin, between 2005 and 2008, using a change detection method applied to ENVISAT ASAR Global Monitoring SAR images acquired at a spatial resolution of 1 km. The method is composed of three steps. First, a supervised classification was performed to identify pixels of open water present in the Guayas Basin. Then, the separability of their radar signature from signatures of other classes was determined during the four dry seasons from 2005 to 2008. In the end, standardized anomalies of backscattering coefficient were computed during the four wet seasons of the study period to detect changes between dry and wet seasons. Different thresholds were tested to identify the flooded areas in the watershed using external information from the Dartmouth Flood Observatory. A value of −2.30 ± 0.05 was found suitable to estimate the number of inundated pixels and limit the number of false detection (below 10%). Using this threshold, monthly maps of inundation were estimated during the wet season (December to May) from 2004 to 2008. The most frequently inundated areas were found to be located along the Babahoyo River, a tributary in the east of the basin. Large interannual variability in the flood extent is observed at the flood peak (from 50 to 580 km 2 ), consistent with the rainfall in the Guayas watershed during the study period.

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Automated global water mapping based on wide-swath orbital synthetic aperture radar

Cited by 12 publications

References 29 publications

A Comparison of Terrain Indices toward Their Ability in Assisting Surface Water Mapping from Sentinel-1 Data

A Comparison of Terrain Indices toward Their Ability in Assisting Surface Water Mapping from Sentinel-1 Data

Operational Surface Water Detection and Monitoring Using Radarsat 2

Monitoring of the Spatio-Temporal Dynamics of the Floods in the Guayas Watershed (Ecuadorian Pacific Coast) Using Global Monitoring ENVISAT ASAR Images and Rainfall Data

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