Using picosatellites for 4-D imaging of volcanic clouds: Proof of concept using ISS photography of the 2009 Sarychev Peak eruption

Zakšek, Klemen; James, Michael; Hort, Matthias; Nogueira, Tiago; Schilling, Klaus

doi:10.1016/j.rse.2018.02.061

Cited by 14 publications

(6 citation statements)

References 66 publications

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“…In the near future, picosatellite capabilities are anticipated to offer 3-D video and synchronous multi-satellite imaging to capture the dynamics of rapidly evolving systems such as ascending eruption columns [e.g. Zakšek et al 2018].…”

Section: Measurement Requirements In Volcanologymentioning

confidence: 99%

Volcanological applications of unoccupied aircraft systems (UAS): Developments, strategies, and future challenges

James

Carr²,

D'Arcy³

et al. 2020

Volcanica

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Unoccupied aircraft systems (UAS) are developing into fundamental tools for tackling the grand challenges in volcanology; here, we review the systems used and their diverse applications. UAS can typically provide image and topographic data at two orders of magnitude better spatial resolution than space-based remote sensing, and close-range observations at temporal resolutions down to those of video frame rates. Responsive deployments facilitate dense time-series measurements, unique opportunities for geophysical surveys, sample collection from hostile environments such as volcanic plumes and crater lakes, and emergency deployment of ground-based sensors (and robots) into hazardous regions. UAS have already been used to support hazard management and decisionmakers during eruptive crises. As technologies advance, increased system capabilities, autonomy, and availabilitysupported by more diverse and lighter-weight sensors-will offer unparalleled potential for hazard monitoring. UAS are expected to provide opportunities for pivotal advances in our understanding of complex physical and chemical volcanic processes. Non-technical SummaryUnoccupied aircraft systems (UAS) are developing into essential tools for understanding and monitoring volcanoes. UAS can typically provide much more detailed imagery and 3-D maps of the Earth's surface, and more frequently, than satellites are able to. They can also make measurements and collect samples for geochemical analysis from hazardous regions such as volcanic plumes and near active vents. Through being quick to deploy, they offer key advantages during initial stages of volcano unrest as well as throughout eruptions. Data from UAS have already been used to support hazard management and decision-makers during crises. In the future, UAS will become increasingly capable of flying longer and more complex missions, more autonomously and with more sophisticated sensors, and are likely to become key components of broader sensor networks for monitoring and research.

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Section: Measurement Requirements In Volcanologymentioning

confidence: 99%

Volcanological applications of unoccupied aircraft systems (UAS): Developments, strategies, and future challenges

James

Carr²,

D'Arcy³

et al. 2020

Volcanica

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“…The entire processing and preparation step was also performed using several IDL routines and functions. For the preparation of the image data first, a Wallis filter [52] was applied to the input images (see SM-3), in order to improve the correlation analysis and image matching. The Wallis filter helps to locally enhance data contrast and texture in images [52], because the Wallis filter is a local image transform that approximates the gray mean and variance of different parts [53].…”

Section: Data Preparation and Preprocessingmentioning

confidence: 99%

“…For the preparation of the image data first, a Wallis filter [52] was applied to the input images (see SM-3), in order to improve the correlation analysis and image matching. The Wallis filter helps to locally enhance data contrast and texture in images [52], because the Wallis filter is a local image transform that approximates the gray mean and variance of different parts [53]. Namely, it increases the gray contrast of parts where the contrast is small and decreases gray contrast where the contrast is large.…”

Section: Data Preparation and Preprocessingmentioning

confidence: 99%

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Cloud Detection Based on High Resolution Stereo Pairs of the Geostationary Meteosat Images

et al. 2020

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Due to the considerable impact of clouds on the energy balance in the atmosphere and on the earth surface, they are of great importance for various applications in meteorology or remote sensing. An important aspect of the cloud research studies is the detection of cloudy pixels from the processing of satellite images. In this research, we investigated a stereographic method on a new set of Meteosat images, namely the combination of the high resolution visible (HRV) channel of the Meteosat-8 Indian Ocean Data Coverage (IODC) as a stereo pair with the HRV channel of the Meteosat Second Generation (MSG) Meteosat-10 image at 0° E. In addition, an approach based on the outputs from stereo analysis was proposed to detect cloudy pixels. This approach is introduced with a 2D-scatterplot based on the parallax value and the minimum intersection distance. The mentioned scatterplot was applied to determine/detect cloudy pixels in various image subsets with different amounts of cloud cover. Apart from the general advantage of the applied stereography method, which only depends on geometric relationships, the cloud detection results are also improved because: (1) The stereo pair is the HRV bands of the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) sensor, with the highest spatial resolution available from the Meteosat geostationary platform; and (2) the time difference between the image pairs is nearly 5 s, which improves the matching results and also decreases the effect of cloud movements. In order to prove this improvement, the results of this stereo-based approach were compared with three different reflectance-based target detection techniques, including the adaptive coherent estimator (ACE), constrained energy minimization (CEM), and matched filter (MF). The comparison of the receiver operating characteristics (ROC) detection curves and the area under these curves (AUC) showed better detection results with the proposed method. The AUC value was 0.79, 0.90, 0.90, and 0.93 respectively for ACE, CEM, MF, and the proposed stereo-based detection approach. The results of this research shall enable a more realistic modelling of down-welling solar irradiance in the future.

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“…Recent works have cited the need for, and theoretically described, 3-D tomographic techniques [25,26]. Similar 3-D retrievals have also been proposed using networks of small satellite systems [27]. Furthermore, computer vision and image processing techniques that have already been applied in 2-D [28,22,29,30] can be applied in 3-D to yield information regarding plume dynamics such as turbulence.…”

Section: Related Workmentioning

confidence: 99%

Measurement of three dimensional volcanic plume properties using multiple ground based infrared cameras

Wood

Thomas

Watson

et al. 2019

ISPRS Journal of Photogrammetry and Remote Sensing

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This study presents a method and a proof of principle system for the direct measurement of volcanic plume 3-D spatial properties. The shape of a plume is reconstructed in three dimensions using multi-view imagery collected from static ground-based cameras. The method was developed using data collected during an expedition to Volcán de Fuego in Guatemala, where four thermal infrared cameras were deployed to capture simultaneous images of the regular ash-rich eruptions. A space carving method was applied to the problem to estimate the volume of the plume at any moment in time. By successively applying the method to sequential sets of images, other quantitative measurements such as the drift direction, ascent rate, and dispersion rate can be deduced. The complete method work-flow is presented including data capture, calibration processes, image processing, the space-carving method, and practical implementation issues. The method is sensitive to the camera alignment, hence a novel technique for estimating the camera orientation angles, making use if a high-accuracy terrain model, is described. Other sources of error relating to the number, synchronisation and resolution of the cameras are also discussed. Preliminary results are presented using data collected at Volcán de Fuego in November 2017 over a period of 1.25 h including three distinct eruptions.

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Using picosatellites for 4-D imaging of volcanic clouds: Proof of concept using ISS photography of the 2009 Sarychev Peak eruption

Cited by 14 publications

References 66 publications

Volcanological applications of unoccupied aircraft systems (UAS): Developments, strategies, and future challenges

Volcanological applications of unoccupied aircraft systems (UAS): Developments, strategies, and future challenges

Cloud Detection Based on High Resolution Stereo Pairs of the Geostationary Meteosat Images

Measurement of three dimensional volcanic plume properties using multiple ground based infrared cameras

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