Measuring Sand Dune Migration Rates with COSI-Corr and Landsat: Opportunities and Challenges

Baird, Thomas R.; Bristow, Charlie S.; Vermeesch, Pieter

doi:10.3390/rs11202423

Cited by 37 publications

(26 citation statements)

References 59 publications

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“…This useful tool has been widely used and developed [42]. In recent years, the COSI-Corr has been widely used to compare the displacement of glacier surfaces using multitemporal images [16,17,26,33,43], including aerial, Landsat, and MODIS images.…”

Section: Cosi-corr For Glacier Velocitymentioning

confidence: 99%

Summer Mass Balance and Surface Velocity Derived by Unmanned Aerial Vehicle on Debris-Covered Region of Baishui River Glacier No. 1, Yulong Snow Mountain

Che

Wang

et al. 2020

Remote Sensing

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Glacier retreat is a common phenomenon in the Qinghai-Tibetan Plateau (QTP) with global warming during the past several decades, except for several mountains, such as the glaciers in the Karakoram and the western Kunlun Mountains. The dynamic nature of glaciers significantly influences the hydrologic, geologic, and ecological systems in the mountain regions. The sensitivity and dynamic response to climate change make glaciers excellent indicators of regional and global climate change, such as glacier melting and retreat with the rise of local air temperature. Long-term monitoring of glacier change is important to understand and assess past, current, and possible future climate environments. Some glacier surfaces are safe and accessible by foot, and are monitored using mass balance stakes and snow pits. Meanwhile, some glaciers with inaccessible termini may be surveyed using satellite remote images and Unmanned Aerial Vehicles (UAVs). Those inaccessible glaciers are generally covered by debris in the southeast QTP, which is hardly accessible due to the wide distribution of crevasses and cliffs. In this paper, we used the UAV to monitor the dynamic features of mass balance and velocity of the debris-covered region of Baishui River Glacier No. 1 (BRG1) on the Yulong Snow Mountain (YSM), Southeast QTP. We obtained the Orthomosaic and DEM with a high resolution of 0.10 m on 20 May and 22 September 2018, respectively. The comparison showed that the elevation of the debris-covered region of the BRG1 decreased by 6.58 m ± 3.70 m on average, and the mean mass balance was −5.92 m w.e. ± 3.33 m w.e. during the summer, correspondingly. The mean displacement of debris-covered glacier surface was 18.30 m ± 6.27 m, that is, the mean daily velocity was 0.14 m/d ± 0.05 m/d during the summer. In addition, the UAV images not only revealed the different patterns of glacier melting and displacement but also captured the phenomena of mass loss due to ice avalanches at the glacier front and the development of large crevasses. This study provides a feasible method for understanding the dynamic features of global debris-covered glaciers which are inaccessible and unobservable by other means.

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Section: Cosi-corr For Glacier Velocitymentioning

confidence: 99%

Summer Mass Balance and Surface Velocity Derived by Unmanned Aerial Vehicle on Debris-Covered Region of Baishui River Glacier No. 1, Yulong Snow Mountain

Che

Wang

et al. 2020

Remote Sensing

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“…The dunes in the first site we studied, located in the northern Sahara, are composed of beach sand and migrate towards the south-southwest. The second dune field is located in the Bodélé Depression, a ∼ 133, 500 km 2 paleolake in Chad [45]. The dunes in the depression are composed of low-density diatomite sand, mobilized by strong winds coming from the northeast.…”

Section: B Detecting Terrestrial Barchan Dunes Employing Our Model Trained On Marsmentioning

confidence: 99%

Automatic Detection and Segmentation of Barchan Dunes on Mars and Earth Using a Convolutional Neural Network

Rubanenko¹,

Pérez-López²,

Schull³

et al. 2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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The morphology of isolated barchan dunes on Mars and Earth may shed light on the dynamic conditions that form them, their migration direction and the physical properties of the sediments composing them. Prior to this study, dune fields have been largely analyzed manually from aerial and satellite imagery, as automatic detection techniques are often not sufficiently accurate in outlining dunes. Here, we employ an instance segmentation neural network to detect and outline isolated barchan dunes on Mars and Earth. We train and test the model on martian targets using Mars Reconnaissance Orbiter (MRO) Context Camera (CTX) images, and find it sufficiently accurate (mAP=77% on the test dataset) to characterize dune field dynamics. Using our trained model we detect and map the global distribution of barchan dunes relative to previously mapped dune fields, and find that barchan dunes are more abundant in the northern hemisphere than in the southern hemisphere. These contrasting abundances of barchans may reflect latitudinally dependent wind regimes, sediment supply, or sediment availability.

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“…In PGblur, the scarce illumination also introduced a slight blurring. The satellite dataset is composed of a pair of Sentinel 2B images (image codes: T33QZU_20191008T090849 and T33QZU_20201002T090719), which targeted the Bodélé Depression (BOD) in Chad [33]. We considered a portion of 400 km 2 centred approximately in 17.02 • N-18.02 • E. Such an area presents isolated sand dunes and clusters of small dunes and a homogeneous background (Figure 4).…”

Section: Real Imagesmentioning

confidence: 99%

“…We investigated this aspect considering the bias between the 1st, 2nd and 3rd quartiles of the distributions of the measured and theoretical displacements. The satellite dataset is composed of a pair of Sentinel 2B images (image codes T33QZU_20191008T090849 and T33QZU_20201002T090719), which targeted the Bodélé Depression (BOD) in Chad [33]. We considered a portion of 400 km 2 centred approxi mately in 17.02N-18.02°E.…”

Section: Criteria For the Comparisonmentioning

confidence: 99%

Comparison of Digital Image Correlation Methods and the Impact of Noise in Geoscience Applications

Dematteis

Giordan

2021

Remote Sensing

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Digital image correlation (DIC) is a commonly-adopted technique in geoscience and natural hazard studies to measure the surface deformation of various geophysical phenomena. In the last decades, several different correlation functions have been developed. Additionally, some authors have proposed applying DIC to other image representations, such as image gradients or orientation. Many works have shown the reliability of specific methods, but they have been rarely compared. In particular, a formal analysis of the impact of different sources of noise is missing. Using synthetic images, we analysed 15 different combinations of correlation functions and image representations and we investigated their performances with respect to the presence of 13 noise sources. Besides, we evaluated the influence of the size of the correlation template. We conducted the analysis also on terrestrial photographs of the Planpincieux Glacier (Italy) and Sentinel 2B images of the Bodélé Depression (Chad). We observed that frequency-based methods are in general less robust against noise, in particular against blurring and speckling, and they tend to underestimate the displacement value. Zero-mean normalised cross-correlation applied to image intensity showed high-quality results. However, it suffers variations of the shadow pattern. Finally, we developed an original similarity function (DOT) that proved to be quite resistant to every noise source.

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Measuring Sand Dune Migration Rates with COSI-Corr and Landsat: Opportunities and Challenges

Cited by 37 publications

References 59 publications

Summer Mass Balance and Surface Velocity Derived by Unmanned Aerial Vehicle on Debris-Covered Region of Baishui River Glacier No. 1, Yulong Snow Mountain

Summer Mass Balance and Surface Velocity Derived by Unmanned Aerial Vehicle on Debris-Covered Region of Baishui River Glacier No. 1, Yulong Snow Mountain

Automatic Detection and Segmentation of Barchan Dunes on Mars and Earth Using a Convolutional Neural Network

Comparison of Digital Image Correlation Methods and the Impact of Noise in Geoscience Applications

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