Retrieving sand dune movements using sub-pixel correlation of multi-temporal optical remote sensing imagery, northwest Sinai Peninsula, Egypt

Hermas, ElSayed; Leprince, S.; El-Magd, Islam Abou

doi:10.1016/j.rse.2012.01.002

Cited by 63 publications

(41 citation statements)

References 17 publications

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“…Note that only offset differences, Δd, between both co-registered scenes become visible in such cases ( Figure 5). Also, we cannot completely rule out terrain movements between the two acquisitions such as from dune migration [18,19] or shadow movements, though visual image inspection does not support these possibilities. To our knowledge, future Sentinel-2 processor versions plan to register new scenes to a reference scene or scene composite from the same relative orbit (Ferran Gascon, personal communication, 2016).…”

Section: Co-registration Of Data From Repeat Orbitsmentioning

confidence: 91%

Glacier Remote Sensing Using Sentinel-2. Part I: Radiometric and Geometric Performance, and Application to Ice Velocity

et al. 2016

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Abstract:With its temporal resolution of 10 days (five days with two satellites, and significantly more at high latitudes), its swath width of 290 km, and its 10 m and 20 m spatial resolution bands from the visible to the shortwave infrared, the European Sentinel-2 satellites have significant potential for glacier remote sensing, in particular mapping of glacier outlines and facies, and velocity measurements. Testing Level 1C commissioning and ramp-up phase data for initial sensor quality experiences, we find a high radiometric performance, but with slight striping effects under certain conditions. Through co-registration of repeat Sentinal-2 data we also find lateral offset patterns and noise on the order of a few metres. Neither of these issues will complicate most typical glaciological applications. Absolute geo-location of the data investigated was on the order of one pixel at the time of writing. The most severe geometric problem stems from vertical errors of the DEM used for ortho-rectifying Sentinel-2 data. These errors propagate into locally varying lateral offsets in the images, up to several pixels with respect to other georeferenced data, or between Sentinel-2 data from different orbits. Finally, we characterize the potential and limitations of tracking glacier flow from repeat Sentinel-2 data using a set of typical glaciers in different environments: Aletsch Glacier, Swiss Alps; Fox Glacier, New Zealand; Jakobshavn Isbree, Greenland; Antarctic Peninsula at the Larsen C ice shelf.

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Section: Co-registration Of Data From Repeat Orbitsmentioning

confidence: 91%

Glacier Remote Sensing Using Sentinel-2. Part I: Radiometric and Geometric Performance, and Application to Ice Velocity

et al. 2016

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“…The Fast Fourier Transformation (FFT) correlation engine embedded in the algorithm of COSI-Corr [8][9][10][11][12][13][14][15] improves the traditional peak correlation algorithm, and its accuracy can reach 1/50 pixel [8]. Thus, we select COSI-Corr as the data processing platform.…”

Section: Experimental Design and Data Processingmentioning

confidence: 99%

“…The COSI-Corr is originally used to extract crustal deformation induced by earthquake released by Tectonics Observatory at Caltech in 2008 [8,9]. The technique is now widely used to monitor the earth surface changes and dynamics [8][9][10][11][12][13][14][15]. As richer and constantly updated satellite observation data become available, the application of optical images cross-correlation technique has been expanded to fields such as glacier flow velocity extraction [10][11][12], quantification of sand dune migration [13][14][15], terrain-deformation measurements of slow landslides [16], monitoring process of significant rift events [17], volcanic monitoring [18] and particularly extensive coseismic deformation extraction [19][20][21].…”

Section: Introductionmentioning

confidence: 99%

“…Many studies demonstrate that the Landsat 8 image cross-correlation technique has advantages in measuring surface deformation, such as mapping ice sheet velocity [26], coseismic deformation extraction [25,[27][28][29] and volcano deformation monitoring [30]. Many researchers have done a lot of analyses and error source correction of displacement measurement, but they mainly focused on a few data sources, such as SPOT, ASTER, HiRISE (High Resolution Imaging Science Experiment) and aerial imagery [3,8,11,[13][14][15][16][17][19][20][21]31,32]. In general, the deformation field obtained by different types of optical sensors with cross-correlation technique has disparities in error structure and magnitude level.…”

Section: Introductionmentioning

confidence: 99%

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Spatio-Temporal Error Sources Analysis and Accuracy Improvement in Landsat 8 Image Ground Displacement Measurements

et al. 2016

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Abstract:Because of the advantages of low cost, large coverage and short revisit cycle, Landsat 8 images have been widely applied to monitor earth surface movements. However, there are few systematic studies considering the error source characteristics or the improvement of the deformation field accuracy obtained by Landsat 8 image. In this study, we utilize the 2013 Mw 7.7 Balochistan, Pakistan earthquake to analyze error spatio-temporal characteristics and elaborate how to mitigate error sources in the deformation field extracted from multi-temporal Landsat 8 images. We found that the stripe artifacts and the topographic shadowing artifacts are two major error components in the deformation field, which currently lack overall understanding and an effective mitigation strategy. For the stripe artifacts, we propose a small spatial baseline (<200 m) method to avoid the stripe artifacts effect on the deformation field. We also propose a small radiometric baseline method to reduce the topographic shadowing artifacts and radiometric decorrelation noises. Those performances and accuracy evaluation show that these two methods are effective in improving the precision of deformation field. This study provides the possibility to detect subtle ground movement with higher precision caused by earthquake, melting glaciers, landslides, etc., with Landsat 8 images. It is also a good reference for error source analysis and corrections in deformation field extracted from other optical satellite images.

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“…On two images acquired at different times and ortho-rectified (geometrically corrected from the topographic effect), homologous points are detected by correlation methods with a theoretical sensitivity of one-tenth of a pixel [17,18].The shift detected between the homologous points on the two images corresponds to the displacement that occurred between the acquisition of the two images. The correlation of ortho-rectified optical images has been applied to measure the co-seismic displacement fields [19,20], the displacement of glaciers [21,22], of landslides [23], and of dunes [24]. One advantage of the image correlation technique is its capability to measure displacements larger than a few pixels on long time baselines.…”

Section: Introductionmentioning

confidence: 99%

Potential and Limitation of SPOT-5 Ortho-Image Correlation to Investigate the Cinematics of Landslides: The Example of “Mare à Poule d’Eau” (Réunion, France)

et al. 2017

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Over the last 10 years, the accessibility of high spatial resolution remote sensing images has strongly increased. These images are available in ortho-rectified format which do not necessitate any further geometrical processing to be analyzed. In parallel, image correlation software has become more efficient and friendly. In this paper, image correlation methods are tested to evaluate their potential and limitations to measure the surface displacements in a complex case of a landslide located in a tropical environment. This studied landslide, called "Mare à Poule d'Eau", is located in the Salazie erosion watershed in Réunion Island (France). This landslide is monitored daily by a DGPS station which registers the south-north displacements. Two pairs of ortho-rectified SPOT-5 images at 2. The displacement can be estimated by applying a correction factor extracted from the ICP located in the stable areas. The potential and limits of the image correlation in such complex environments is discussed. A strategy is proposed to evaluate the quality of the results and to extract the displacement signal from the shift measurements.

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Retrieving sand dune movements using sub-pixel correlation of multi-temporal optical remote sensing imagery, northwest Sinai Peninsula, Egypt

Cited by 63 publications

References 17 publications

Glacier Remote Sensing Using Sentinel-2. Part I: Radiometric and Geometric Performance, and Application to Ice Velocity

Glacier Remote Sensing Using Sentinel-2. Part I: Radiometric and Geometric Performance, and Application to Ice Velocity

Spatio-Temporal Error Sources Analysis and Accuracy Improvement in Landsat 8 Image Ground Displacement Measurements

Potential and Limitation of SPOT-5 Ortho-Image Correlation to Investigate the Cinematics of Landslides: The Example of “Mare à Poule d’Eau” (Réunion, France)

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