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

Citation
Ajl. Harris et al., Automated, high temporal resolution, thermal analysis of Kilauea volcano, Hawai'i, using GOES satellite data, INT J REMOT, 22(6), 2001, pp. 945-967
Citations number
31
Categorie Soggetti
Earth Sciences
Journal title
INTERNATIONAL JOURNAL OF REMOTE SENSING
ISSN journal
01431161 → ACNP
Volume
22
Issue
6
Year of publication
2001
Pages
945 - 967
Database
ISI
SICI code
0143-1161(200104)22:6<945:AHTRTA>2.0.ZU;2-Z
Abstract
Thermal data are directly available from the Geostationary Operational Envi ronmental Satellites (GOES) every 15 minutes at existing or inexpensively i nstalled receiving stations. This data stream is ideal for monitoring high temperature features such as active lava flows and fires. To provide a near -real-time hot spot monitoring tool, we have developed, tested and installe d software to analyse GOES data on-reception and then make results availabl e 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 similar to 12 minutes of image acquisi tion and are updated every 15 minutes. Analysis of GOES data acquired for effusive activity at Kilauea volcano ( H awai'i) during 1997-98 show that short (<1 hour long) events producing 100 m long ( 10(2) to 10(3) m(2)) lava flows are detectable. This means that ti me constraints can be placed on sudden, rapidly evolving effusive events wi th an accuracy of <plus/minus>7.5 minutes. Changes in activity style and ex tent 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) m(-1)); (2) activity pauses (no radiance); ( 3) lava lake activ ity ( low radiance, <5 MW m(2) m(-1)); ( 4) short (<3 km long) flow extensi on (moderate radiance, 10-20 MW m(2) m(-1)); and (5) 12 km long flow extens ion ( high radiance, 15-30 MW m(2) m(-1)). The ability of GOES to detect short-lived effusive events, coupled with the speed with which GOES-based hot spot information can be processed and diss eminated, means that GOES offers a valuable additional volcano monitoring t ool.