DALJINSKO ZAZNAVANJE TOPLOTNIH ANOMALIJ NA AKTIVNIH OGNJENIKIH
REMOTE SENSING OF THERMAL ANOMALIES ON ACTIVE VOLCANOES

Klemen Zakšek, Matthias Hort

DOI: 10.15292/geodetski-vestnik.2010.04.627-642

 

Izvleček:

Daljinsko zaznavanje v termičnem infrardečem spektru je sodobno orodje, ki nam omogoča opazovanje aktivnih ognjenikov. Z njim lahko zaznamo manjše toplotne anomalije, kot so vroči izviri ali fumarole, pa tudi večja telesa, kot so tokovi ali jezera lave. Vse anomalije imajo ne glede na temperaturo običajno manjšo površino od prostorske ločljivosti senzorjev (od 30 do 4000 m), ki so primerni za njihovo opazovanje. Da bi lahko anomalijo kljub temu zaznali in določili njene fizikalne parametre, moramo uporabiti podatke iz več kanalov v ustreznem spektru. Toplotno anomalijo najbolj robustno opišemo s toplotnim tokom. Za razumevanje aktivnosti ognjenika moramo spremljati
razvoj časovne vrste toplotnega toka. Ker so satelitski podatki podvrženi vplivom atmosfere, reliefa, itd., je v časovni vrsti vedno prisoten šum. Kot primer smo prikazali zmanjšanje šuma s kalmanovim filtrom, s katerim smo obdelali izbruh Etne jeseni 2002.

Ključne besede: termično daljinsko zaznavanje, ognjenik, toplotni tok, kalmanov filter

 

Abstract:

Thermal remote sensing is a valuable tool for monitoring active volcanoes. One can use it to detect smaller thermal anomalies, such as hot springs or fumaroles. It is successful also by detecting larger anomalies, such as lava flows or lava lakes. All these anomalies usually cover only a small area comparing to the ground sample distance of the sensors that are appropriate for their monitoring. This makes detecting and characterizing the thermal anomaly a difficult task that is solved by using more data from several bands covering the appropriate spectra. The most robust parameter to characterize a thermal anomaly is radiative heat flux. We need to analyse its time series in order to understand the volcano activity. Satellite data are influenced by the atmosphere, terrain, etc. Therefore, the time series always contains some noise. For a case study we applied Kalman filter to minimise the noise in the case study of Etna eruption in autumn 2002.

Keywords: thermal remote sensing, volcano, radiative heat flux, Kalman filter

 

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