Chronology of the episode 54 eruption at Kilauea Volcano, Hawaii, from GOES‐9 satellite data

Harris, Andrew; Keszthelyi, L.; Flynn, Luke P.; Mouginis-Mark, P. J.; Thornber, Carl R.; Kauahikaua, James P.; Sherrod, David R.; Trusdell, Frank A.; Sawyer, Michael W.; Flament, Pierre

doi:10.1029/97gl03165

Cited by 47 publications

(29 citation statements)

References 6 publications

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“…Following the technique of Harris et al (1997aHarris et al ( , 1997b and Harris and Thornber (1999 ) we use volcanic radiance (R2volc), this being the channel 2 radiance of an anomalous pixel minus that of its immediate, non-anomalous background. Following Harris and Thornber (1999 ) we then sum R2volc for all anomalous pixels to give SR2volc.…”

Section: T Echniquesmentioning

confidence: 99%

“…Previously GOES data have been utilised to detect, track and analyse rapidly developing volcanic features such as dispersing volcanic ash plumes (Sawada 1987, Glaze et al 1989, Holasek and Self 1995, and to detect and monitor biomass burning (Menzel et al 1991, Prins andMenzel 1992 ). Until Harris et al (1997a) showed how GOES data could be used to produce a detailed chronology of an eVusive eruption, however, the potential of GOES for volcanic hot spot monitoring remained unexplored in the published literature.…”

Section: Introductionmentioning

confidence: 99%

“…Thermal data are available every 15 minutes which, although having a nominal spatial resolution of~4 km, are capable of detecting and monitoring rapidly developing hot spots associated with eVusive volcanic eruptions (Harris et al 1997a). Lava¯ows may be emplaced over a period of minutes to hours, and timely provision of details regarding event occurrence and development are essential for hazard assessment and mitigation.…”

Section: Introductionmentioning

confidence: 99%

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Automated, high temporal resolution, thermal analysis of Kilauea volcano, Hawai'i, using GOES satellite data

Harris

Pilger

Flynn

et al. 2001

International Journal of Remote Sensing

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Abstract. Thermal data are directly available from the Geostationary Operational Environmental Satellites (GOES) every 15 minutes at existing or inexpensively installed receiving stations. This data stream is ideal for monitoring high temperature features such as active lava¯ows and ® res. To provide a near-real-time hot spot monitoring tool, we have developed, tested and installed software to analyse GOES data on-reception and then make results available in a timely fashion via the web. Our software automatically: (1) produces hot spot images and movies; (2) uses a thresholding procedure to generate a hot spot map; (3) updates hot spot radiance and cloud index time series; and (4) issues a threshold-based e-mail alert. Results are added to http://volcano1.pgd.hawaii.edu/goes/ within~12 minutes of image acquisition and are updated every 15 minutes.Analysis of GOES data acquired for eVusive activity at Kilauea volcano (Hawai'i ) during 1997± 98 show that short (<1 hour long) events producing 100 m long (10 2 to 10 3 m 2 ) lava¯ows are detectable. This means that time constraints can be placed on sudden, rapidly evolving eƒ usive events with an accuracy of Ô 7.5 minutes. Changes in activity style and extent can also be documented using hot spot size, intensity and shape. From radiance time series we distinguish (1) tube-fed activity ( low radiance, <10 MW m 2 mÕ 1 ); (2) activity pauses (no radiance); (3) lava lake activity ( low radiance, <5 MW m 2 mÕ 1 ); (4) The ability of GOES to detect short-lived eVusive events, coupled with the speed with which GOES-based hot spot information can be processed and disseminated, means that GOES oVers a valuable additional volcano monitoring tool.

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Section: T Echniquesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Automated, high temporal resolution, thermal analysis of Kilauea volcano, Hawai'i, using GOES satellite data

Harris

Pilger

Flynn

et al. 2001

International Journal of Remote Sensing

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“…The results are posted on the Internet (http://goes.higp.hawaii.edu) usually within 15 min of initial image acquisition. The GOES-based system has provided valuable insights into the development of lava flow-fields and eruption timings at Kilauea Volcano in Hawaii (Harris, Keszthelyi, et al, 1997;Harris & Thornber, 1999) and Fernandina Volcano in the Galapagos Islands (Mouginis-Mark, Snell, & Ellisor, 2000). It has also been used to elucidate processes governing the behaviour of potentially explosive silicic lava domes at Popocatépetl, Mexico (Wright, de la Cruz-Reyna, Flynn, Harris, & Gomez-Palacios, in press) and Lascar .…”

Section: Introductionmentioning

confidence: 99%

Automated volcanic eruption detection using MODIS

Wright¹,

Flynn²,

Garbeil³

et al. 2002

Remote Sensing of Environment

241

159

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The moderate resolution imaging spectroradiometer (MODIS) flown on-board NASA's first earth observing system (EOS) platform, Terra, offers complete global data coverage every 1 -2 days at spatial resolutions of 250, 500, and 1000 m. Its ability to detect emitted radiation in the short (4 Am)-and long (12 Am)-wave infrared regions of the electromagnetic spectrum, combined with the excellent geolocation of the image pixels ( f 200 m), makes it an ideal source of data for automatically detecting and monitoring high-temperature volcanic thermal anomalies. This paper describes the underlying principles of, and results obtained from, just such a system. Our algorithm interrogates the MODIS Level 1B data stream for evidence of high-temperature volcanic features. Once a hotspot has been identified, its details (location, emitted spectral radiance, satellite observational parameters) are written to an ASCII text file and transferred via file transfer protocol (FTP) to the Hawaii Institute of Geophysics and Planetology (HIGP), where the results are posted on the Internet (http:// modis.higp.hawaii.edu). The global distribution of volcanic hotspots can be examined visually at a variety of scales using this website, which also allows easy access to the quantitative data contained in the ASCII files themselves. We outline how the algorithm has proven robust as a hotspot detection tool for a wide range of eruptive styles at both permanently and sporadically active volcanoes including Soufriere Hills (Montserrat), Popocatépetl (Mexico), Bezymianny (Russia), and Merapi (Java), amongst others. We also present case studies of how the system has allowed the onset, development, and cessation of discrete eruptive events to be monitored at Nyamuragira (Congo), Piton de la Fournaise (Réunion Island), and Shiveluch (Russia). D

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“…Since 1998, an automated system at the Hawai'i Institute of Geophysics and Planetology, has been operational, with the task of processing GOES data for monitoring global volcanic activity, and since this time various studies have also confirmed the utility of GOES for determining volcanic activity chronologies (e.g. 47,48). SEVERI, the instrument onboard the most recent Meteosat with infrared imaging capabilities, has similarly been used for such purposes and indeed, has formed part of an automated volcano monitoring system, HOTSAT, which is implemented, along with higher resolution MODIS data, for rapid activity detection and monitoring 49, 50. In 1986, NASA announced its plans for the development of an Earth Observation System (EOS) 51 that would acquire low-Earth orbit observations.…”

Section: Historical Perspective On Sensors Used For Volcanic Observationmentioning

confidence: 99%

Progress in the Infrared Remote Sensing of Volcanic Activity

Blackett

2016

Preprint

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Volcanic activity essentially consists of the transfer of heat from the Earth' interior to the surface. The precise signature of this heat transfer relates directly to the processes underway at and within a particular volcano and this can be observed, at a safe distance, remotely, using infrared sensors that are present on Earth-orbiting satellites. For over 50 years, scientists have perfected this art using sensors intended for other purposes, and they are now in a position to determine the particular sort of activity that characterizes different volcanoes. This review will describe the theoretical basis of the discipline and then discuss the sensors available for the task and the history of their use. Challenges and opportunities for future development in the discipline are then discussed.

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Chronology of the episode 54 eruption at Kilauea Volcano, Hawaii, from GOES‐9 satellite data

Cited by 47 publications

References 6 publications

Automated, high temporal resolution, thermal analysis of Kilauea volcano, Hawai'i, using GOES satellite data

Automated, high temporal resolution, thermal analysis of Kilauea volcano, Hawai'i, using GOES satellite data

Automated volcanic eruption detection using MODIS

Progress in the Infrared Remote Sensing of Volcanic Activity

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