Towards an automated SAR-based flood monitoring system: Lessons learned from two case studies

Matgen, Patrick; Hostache, Renaud; Schumann, Guy; Pfister, Laurent; Hoffmann, Lucien; Savenije, Hubert

doi:10.1016/j.pce.2010.12.009

Cited by 341 publications

(227 citation statements)

References 26 publications

Supporting

Mentioning

219

Contrasting

Unclassified

Order By: Relevance

“…Better results would require data with high spatial resolution. The detection of smaller water surfaces has been reported also in [18,20,35,51]. They can be detected by the use of images with higher spatial resolution, such as X band SAR data [20,29,31,32,36].…”

Section: Grassland Floods (Intra-field Scale)mentioning

confidence: 99%

Mapping and Characterization of Hydrological Dynamics in a Coastal Marsh Using High Temporal Resolution Sentinel-1A Images

Cazals¹,

Rapinel

Frison³

et al. 2016

Remote Sensing

View full text Add to dashboard Cite

Abstract:In Europe, water levels in wetlands are widely controlled by environmental managers and farmers. However, the influence of these management practices on hydrodynamics and biodiversity remains poorly understood. This study assesses advantages of using radar data from the recently launched Sentinel-1A satellite to monitor hydrological dynamics of the Poitevin marshland in western France. We analyze a time series of 14 radar images acquired in VV and HV polarizations from December 2014 to May 2015 with a 12-day time step. Both polarizations are used with a hysteresis thresholding algorithm which uses both spatial and temporal information to distinguish open water, flooded vegetation and non-flooded grassland. Classification results are compared to in situ piezometric measurements combined with a Digital Terrain Model derived from LiDAR data. Results reveal that open water is successfully detected, whereas flooded grasslands with emergent vegetation and fine-grained patterns are detected with moderate accuracy. Five hydrological regimes are derived from the flood duration and mapped. Analysis of time steps in the time series shows that decreased temporal repetitivity induces significant differences in estimates of flood duration. These results illustrate the great potential to monitor variations in seasonal floods with the high temporal frequency of Sentinel-1A acquisitions.

show abstract

Section: Grassland Floods (Intra-field Scale)mentioning

confidence: 99%

Mapping and Characterization of Hydrological Dynamics in a Coastal Marsh Using High Temporal Resolution Sentinel-1A Images

Cazals¹,

Rapinel

Frison³

et al. 2016

Remote Sensing

View full text Add to dashboard Cite

show abstract

“…They showed that SAR imagery offers the possibilities to obtain distributed remote-sensing-derived water levels over a large area with sufficient accuracy for calibration of a hydraulic model. Matgen et al (2011) proposed a hybrid approach to automatically extract flood extent from SAR images by estimating the statistical distribution of open water backscatter values from SAR images of floods, radiometric thresholding to extract the core of the water bodies, and region growing to extract all water bodies. They proposed a change detection procedure using pre-or post-flood SAR reference images to remove over-detection of inundated areas.…”

Section: Introductionmentioning

confidence: 99%

Flood occurrence mapping of the middle Mahakam lowland area using satellite radar

Hidayat

Hoekman

Vissers³

et al. 2012

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

Abstract. Floodplain lakes and peatlands in the middle Mahakam lowland area are considered as ecologically important wetland in East Kalimantan, Indonesia. However, due to a lack of data, the hydrological functioning of the region is still poorly understood. Among remote sensing techniques that can increase data availability, radar is well-suitable for the identification, mapping, and measurement of tropical wetlands, for its cloud unimpeded sensing and night and day operation. Here we aim to extract flood extent and flood occurrence information from a series of radar images of the middle Mahakam lowland area. We explore the use of Phased Array L-band Synthetic Aperture Radar (PALSAR) imagery for observing flood inundation dynamics by incorporating field water level measurements. Water level measurements were carried out along the river, in lakes and in peatlands, using pressure transducers. For validation of the open water flood occurrence map, bathymetry measurements were carried out in the main lakes. A series of PALSAR images covering the middle and lower Mahakam area in the years 2007 through 2010 were collected. A fully inundated region can be easily recognized on radar images from a dark signature. Open water flood occurrence was mapped using a threshold value taken from radar backscatter of the permanently inundated river and lakes areas. Radar backscatter intensity analysis of the vegetated floodplain area revealed consistently high backscatter values, indicating flood inundation under forest canopy. We used those values as the threshold for flood occurrence mapping in the vegetated area.

show abstract

“…O'Grady et al (2011) conclude that misclassification due to low backscatter values from non-flooded areas can be reduced via image differencing approaches. Matgen et al (2011) and Giustarini et al (2012) present a method relying on the calibration of a statistical distribution of "open water" backscatter values inferred from SAR images of floods. Given the many circumstances that can affect classification results, it is difficult to derive a consistent classification technique that, ideally, also includes an error or accuracy assessment, and for all incidence angles.…”

Section: Relative Advantages Of Sar and Optical Imagingmentioning

confidence: 99%

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

Westerhoff

Kleuskens

Winsemius

et al. 2013

Hydrol. Earth Syst. Sci.

150

View full text Add to dashboard Cite

Abstract. This paper presents an automated technique which ingests orbital synthetic-aperture radar (SAR) imagery and outputs surface water maps in near real time and on a global scale. The service anticipates future open data dissemination of water extent information using the European Space Agency's Sentinel-1 data. The classification methods used are innovative and practical and automatically calibrated to local conditions per 1 × 1 • tile. For each tile, a probability distribution function in the range between being covered with water or being dry is established based on a long-term SAR training dataset. These probability distributions are conditional on the backscatter and the incidence angle. In classification mode, the probability of water coverage per pixel of 1 km × 1 km is calculated with the input of the current backscatter -incidence angle combination. The overlap between the probability distributions of a pixel being wet or dry is used as a proxy for the quality of our classification. The service has multiple uses, e.g. for water body dynamics in times of drought or for urgent inundation extent determination during floods. The service generates data systematically: it is not an on-demand service activated only for emergency response, but instead is always up-to-date and available. We validate its use in flood situations using Envisat ASAR information during the 2011 Thailand floods and the Pakistan 2010 floods and perform a first merge with a NASA near real time water product based on MODIS optical satellite imagery. This merge shows good agreement between these independent satellite-based water products.

show abstract

Towards an automated SAR-based flood monitoring system: Lessons learned from two case studies

Cited by 341 publications

References 26 publications

Mapping and Characterization of Hydrological Dynamics in a Coastal Marsh Using High Temporal Resolution Sentinel-1A Images

Mapping and Characterization of Hydrological Dynamics in a Coastal Marsh Using High Temporal Resolution Sentinel-1A Images

Flood occurrence mapping of the middle Mahakam lowland area using satellite radar

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

Contact Info

Product

Resources

About