Sentinel-1 for Monitoring Reservoirs: A Performance Analysis

Amitrano, Donato; Martino, Gerardo Di; Iodice, Antonio; Mitidieri, Francesco; Papa, Maria Nicolina; Riccio, Daniele; Ruello, Giuseppe

doi:10.3390/rs61110676

Cited by 63 publications

(38 citation statements)

References 23 publications

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“…Thanks to the launch of the Sentinel-1A &B satellites, as well as the free data policy of the European Space Agency (ESA), Sentinel-1 SAR observations are now regularly and freely accessible for scientific and educational purposes, over large parts of the globe. Similar to previous SAR instruments, Sentinel-1 instruments show strong potential for detecting open water bodies at high spatial resolution [18,19].…”

Section: Introductionmentioning

confidence: 73%

Surface Water Monitoring within Cambodia and the Vietnamese Mekong Delta over a Year, with Sentinel-1 SAR Observations

Pham-Duc

Prigent

Aires

2017

Water

116

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This study presents a methodology to detect and monitor surface water with Sentinel-1 Synthetic Aperture Radar (SAR) data within Cambodia and the Vietnamese Mekong Delta. It is based on a neural network classification trained on Landsat-8 optical data. Sensitivity tests are carried out to optimize the performance of the classification and assess the retrieval accuracy. Predicted SAR surface water maps are compared to reference Landsat-8 surface water maps, showing a true positive water detection of ∼90% at 30 m spatial resolution. Predicted SAR surface water maps are also compared to floodability maps derived from high spatial resolution topography data. Results show high consistency between the two independent maps with 98% of SAR-derived surface water located in areas with a high probability of inundation. Finally, all available Sentinel-1 SAR observations over the Mekong Delta in 2015 are processed and the derived surface water maps are compared to corresponding MODIS/Terra-derived surface water maps at 500 m spatial resolution. Temporal correlation between these two products is very high (99%) with very close water surface extents during the dry season when cloud contamination is low. This study highlights the applicability of the Sentinel-1 SAR data for surface water monitoring, especially in a tropical region where cloud cover can be very high during the rainy seasons.

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Section: Introductionmentioning

confidence: 73%

Surface Water Monitoring within Cambodia and the Vietnamese Mekong Delta over a Year, with Sentinel-1 SAR Observations

Pham-Duc

Prigent

Aires

2017

Water

116

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“…RADARSAT, JERS-1, ERS, or Sentinel-1) (Annor et al, 2009;Duan and Bastiaanssen, 2013;Amitrano et al, 2014). The latter has however been less used due to the difficulty in getting consistent results, as the required condition of a significantly lower phase coherence of water areas than of the surrounding land surface is not always met, with orbital repeat cycles of more than a few days, or with wind or rain (Alsdorf et al, 2007;Eilander et al, 2014).…”

Section: N Avisse Et Al: Monitoring Small Reservoirs' Storagementioning

confidence: 99%

Monitoring small reservoirs' storage with satellite remote sensing in inaccessible areas

Avisse

Tilmant

Müller³

et al. 2017

Hydrol. Earth Syst. Sci.

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Abstract. In river basins with water storage facilities, the availability of regularly updated information on reservoir level and capacity is of paramount importance for the effective management of those systems. However, for the vast majority of reservoirs around the world, storage levels are either not measured or not readily available due to financial, political, or legal considerations. This paper proposes a novel approach using Landsat imagery and digital elevation models (DEMs) to retrieve information on storage variations in any inaccessible region. Unlike existing approaches, the method does not require any in situ measurement and is appropriate for monitoring small, and often undocumented, irrigation reservoirs. It consists of three recovery steps: (i) a 2-D dynamic classification of Landsat spectral band information to quantify the surface area of water, (ii) a statistical correction of DEM data to characterize the topography of each reservoir, and (iii) a 3-D reconstruction algorithm to correct for clouds and Landsat 7 Scan Line Corrector failure. The method is applied to quantify reservoir storage in the Yarmouk basin in southern Syria, where ground monitoring is impeded by the ongoing civil war. It is validated against available in situ measurements in neighbouring Jordanian reservoirs. Coefficients of determination range from 0.69 to 0.84, and the normalized root-mean-square error from 10 to 16 % for storage estimations on six Jordanian reservoirs with maximal water surface areas ranging from 0.59 to 3.79 km 2 .

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“…Gravity data has been treated and analyzed in order to extract gravimetric lineaments which will be correlated and completed by the discontinuities deduced from sentinel 1A radar GRD type (Ground Range Detected) image analysis and filtering. This type of image is recognized as having a great potential, generally in geological applications and particularly in structural mapping [20,21,22]. Numerous examples in literature demonstrate the effectiveness of geophysical and satellite data coupling method in fractures detection and litho structural maps updating [23,24,25,26,27,28].…”

Section: Introductionmentioning

confidence: 99%

Contribution of gravity data and Sentinel-1 image for structural mapping. Case of Beni Mellal Atlas and Beni Moussa plain (Morocco).

et al. 2018

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Abstract. The present work is a combined study of gravity and Sentine-1 data for fracture mapping in the karstic massif of Beni Mellal Atlas and the adjacent plain of Beni Moussa. In order to locate the various faults that contribute to the study area structuring, the gravimetric contacts analysis method, based on the joint use of the horizontal gradient and the upward continuation at different altitudes, has been applied to the gravity data. To optimize the structural mapping in the study area, the gravimetric lineaments obtained were completed and correlated with the lineaments got from Sentinel-1 image. Four faults families of NE-SW; E-O; N-S and NW-SE directions have been highlighted. There fault families are perfectly combined with the studied area's surface water network, moreover, they corroborate with the previous geological and structural studies.

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Sentinel-1 for Monitoring Reservoirs: A Performance Analysis

Cited by 63 publications

References 23 publications

Surface Water Monitoring within Cambodia and the Vietnamese Mekong Delta over a Year, with Sentinel-1 SAR Observations

Surface Water Monitoring within Cambodia and the Vietnamese Mekong Delta over a Year, with Sentinel-1 SAR Observations

Monitoring small reservoirs' storage with satellite remote sensing in inaccessible areas

Contribution of gravity data and Sentinel-1 image for structural mapping. Case of Beni Mellal Atlas and Beni Moussa plain (Morocco).

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