Coseismic displacements of the 14 November 2016 &amp;lt;i&amp;gt;M&amp;lt;/i&amp;gt;&amp;lt;sub&amp;gt;w&amp;lt;/sub&amp;gt; 7.8 Kaikoura, New Zealand, earthquake using the Planet optical cubesat constellation

Kääb, Andreas; Altena, Bas; Mascaro, Joseph

doi:10.5194/nhess-17-627-2017

Cited by 48 publications

(23 citation statements)

References 28 publications

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“…However, new satellite constellations such as Sentinel-2 (5 days repeat; Kääb et al, 2016) or the Planet cubesat constellation (daily repeat, Kääb et al, 2017) will help to detect even short-term changes. The applicability of Sentinel-1 radar data (6 days repeat) for monitoring these lakes remains to be tested (Strozzi et al, 2012).…”

Section: Discussionmentioning

confidence: 99%

Large drainages from short-lived glacial lakes in the Teskey Range, Tien Shan Mountains, Central Asia

Narama¹,

Daiyrov²,

Duishonakunov³

et al. 2018

Nat. Hazards Earth Syst. Sci.

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Abstract. Four large drainages from glacial lakes occurred during 2006-2014 in the western Teskey Range, Kyrgyzstan. These floods caused extensive damage, killing people and livestock as well as destroying property and crops. Using satellite data analysis and field surveys of this area, we find that the water volume that drained at Kashkasuu glacial lake in 2006 was 194 000 m 3 , at western Zyndan lake in 2008 was 437 000 m 3 , at Jeruy lake in 2013 was 182 000 m 3 , and at Karateke lake in 2014 was 123 000 m 3 . Due to their subsurface outlet, we refer to these short-lived glacial lakes as the "tunnel-type", a type that drastically grows and drains over a few months. From spring to early summer, these lakes either appear, or in some cases, significantly expand from an existing lake (but non-stationary), and then drain during summer. Our field surveys show that the short-lived lakes form when an ice tunnel through a debris landform gets blocked. The blocking is caused either by the freezing of stored water inside the tunnel during winter or by the collapse of ice and debris around the ice tunnel. The draining then occurs through an opened ice tunnel during summer. The growth-drain cycle can repeat when the ice-tunnel closure behaves like that of typical supraglacial lakes on debris-covered glaciers. We argue here that the geomorphological characteristics under which such short-lived glacial lakes appear are (i) a debris landform containing ice (ice-cored moraine complex), (ii) a depression with water supply on a debris landform as a potential lake basin, and (iii) no visible surface outflow channel from the depression, indicating the existence of an ice tunnel. Applying these characteristics, we examine 60 depressions (> 0.01 km 2 ) in the study region and identify here 53 of them that may become short-lived glacial lakes, with 34 of these having a potential drainage exceeding 10 m 3 s −1 at peak discharge.

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Section: Discussionmentioning

confidence: 99%

Large drainages from short-lived glacial lakes in the Teskey Range, Tien Shan Mountains, Central Asia

Narama¹,

Daiyrov²,

Duishonakunov³

et al. 2018

Nat. Hazards Earth Syst. Sci.

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“…According to [27,29,30], among the main features of these satellites, properly named CubeSats, there are: (i) the general small size and weight (a single-unit of CubeSat normally measures 10 × 10 × 11 cm and typically weights less than 1.5 kg), (ii) high geometric resolution (~3-5 m/pixel) and (iii) daily/near-daily revisit time. CubeSats represent a cost-effective EO strategy, allowing unique chances for a wide variety of application fields [8,31].Planet Labs Inc. has recently made available a large constellation (> 130 units) of optical 3-U CubeSats (10 × 10 × 30 cm), also called PlanetScope or, more commonly, "Doves" [27,30,[32][33][34]. With an average orbit height of about 475 km a.s.l., the main CCD array sensor is able to collect images of 7000 × 2000 pixels, with a footprint of approximately 24 × 8 km 2 .…”

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“…Each Doves collects one image/second along his orbit with a slight overlapping between consecutive scenes. In this way, taking advantage of the whole constellation, images at a daily sampling rate are achievable, thus allowing to obtain long stacks of multi-temporal images in a short period [8,34].At present, only few authors used "Doves" images for the assessment of landslides [35] or earthquakes-induced displacement [8], while, no attempts of deriving time-series of displacements of landslides using stack of Doves images processed by Digital Image Correlation (DIC) are available in literature.Recently, different authors presented interesting results derived from the application of DIC analysis on a stack of satellite images for landslide displacement monitoring [22,24]. Specifically, they developed a workflow adapted for satellite optical images with the aim of achieving the best signal/noise ratio by taking advantage of the data redundancy.…”

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Sliding Time Master Digital Image Correlation Analyses of CubeSat Images for landslide Monitoring: The Rattlesnake Hills Landslide (USA)

Caporossi

Muzi

2020

Remote Sensing

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Landslide monitoring is a global challenge that can take strong advantage from opportunities offered by Earth Observation (EO). The increasing availability of constellations of small satellites (e.g., CubeSats) is allowing the collection of satellite images at an incredible revisit time (daily) and good spatial resolution. Furthermore, this trend is expected to grow rapidly in the next few years. In order to explore the potential of using a long stack of images for improving the measurement of ground displacement, we developed a new procedure called STMDA (Slide Time Master Digital image correlation Analyses) that we applied to one year long stack of PlanetScope images for back analyzing the displacement pattern of the Rattlesnake Hills landslide occurred between the 2017 and 2018 in the Washington State (USA). Displacement maps and time-series of displacement of different portions of the landslide was derived, measuring velocity up to 0.5 m/week, i.e., very similar to velocities available in literature. Furthermore, STMDA showed also a good potential in denoising the time-series of displacement at the whole scale with respect to the application of standard DIC methods, thus providing displacement precision up to 0.01 pixels.The most common optical satellite missions (e.g., QuickBird, SPOT, LANDSAT, Sentinel-2, WorldView, Pléiades, just to mention few of them) are characterized by spatial resolution ranging between 0.3 and 30 m and a revisit time of some days [25][26][27], therefore, they are not fully adequate to detect landslides at a spatial and temporal scale suitable for continuous monitoring. However, as stated in [4,28], the fusion of images collected by different optical satellite sensors has certainly increased the opportunities for cloud-free surface investigation, thus allowing also a general improvement of the temporal resolution.In the last few years, EO has been affected by an astonishing sensor and platform development and improvement, thanks to small satellites. According to [27,29,30], among the main features of these satellites, properly named CubeSats, there are: (i) the general small size and weight (a single-unit of CubeSat normally measures 10 × 10 × 11 cm and typically weights less than 1.5 kg), (ii) high geometric resolution (~3-5 m/pixel) and (iii) daily/near-daily revisit time. CubeSats represent a cost-effective EO strategy, allowing unique chances for a wide variety of application fields [8,31].Planet Labs Inc. has recently made available a large constellation (> 130 units) of optical 3-U CubeSats (10 × 10 × 30 cm), also called PlanetScope or, more commonly, "Doves" [27,30,[32][33][34]. With an average orbit height of about 475 km a.s.l., the main CCD array sensor is able to collect images of 7000 × 2000 pixels, with a footprint of approximately 24 × 8 km 2 . Each Doves collects one image/second along his orbit with a slight overlapping between consecutive scenes. In this way, taking advantage of the whole constellation, images at a daily sampling rate are achievable, thus allowing to ...

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Two regions of seafloor deformation generated the tsunami for the 13 November 2016, Kaikoura, New Zealand earthquake

Bai

Lay

Cheung

et al. 2017

Geophysical Research Letters

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The 13 November 2016 Kaikoura, New Zealand, Mw 7.8 earthquake ruptured multiple crustal faults in the transpressional Marlborough and North Canterbury tectonic domains of northeastern South Island. The Hikurangi trench and underthrust Pacific slab terminate in the region south of Kaikoura, as the subdution zone transitions to the Alpine fault strike‐slip regime. It is difficult to establish whether any coseismic slip occurred on the megathrust from on‐land observations. The rupture generated a tsunami well recorded at tide gauges along the eastern coasts and in Chatham Islands, including a ~4 m crest‐to‐trough signal at Kaikoura where coastal uplift was about 1 m, and at multiple gauges in Wellington Harbor. Iterative modeling of teleseismic body waves and the regional water‐level recordings establishes that two regions of seafloor motion produced the tsunami, including an Mw ~7.6 rupture on the megathrust below Kaikoura and comparable size transpressional crustal faulting extending offshore near Cook Strait.

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Coseismic displacements of the 14 November 2016 <i>M</i><sub>w</sub> 7.8 Kaikoura, New Zealand, earthquake using the Planet optical cubesat constellation

Cited by 48 publications

References 28 publications

Large drainages from short-lived glacial lakes in the Teskey Range, Tien Shan Mountains, Central Asia

Large drainages from short-lived glacial lakes in the Teskey Range, Tien Shan Mountains, Central Asia

Sliding Time Master Digital Image Correlation Analyses of CubeSat Images for landslide Monitoring: The Rattlesnake Hills Landslide (USA)

Two regions of seafloor deformation generated the tsunami for the 13 November 2016, Kaikoura, New Zealand earthquake

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