Time series analysis of infrared satellite data for detecting thermal anomalies: a hybrid approach
- 297 Downloads
We developed and tested an automated algorithm that analyzes thermal infrared satellite time series data to detect and quantify the excess energy radiated from thermal anomalies such as active volcanoes. Our algorithm enhances the previously developed MODVOLC approach, a simple point operation, by adding a more complex time series component based on the methods of the Robust Satellite Techniques (RST) algorithm. Using test sites at Anatahan and Kīlauea volcanoes, the hybrid time series approach detected ~15% more thermal anomalies than MODVOLC with very few, if any, known false detections. We also tested gas flares in the Cantarell oil field in the Gulf of Mexico as an end-member scenario representing very persistent thermal anomalies. At Cantarell, the hybrid algorithm showed only a slight improvement, but it did identify flares that were undetected by MODVOLC. We estimate that at least 80 MODIS images for each calendar month are required to create good reference images necessary for the time series analysis of the hybrid algorithm. The improved performance of the new algorithm over MODVOLC will result in the detection of low temperature thermal anomalies that will be useful in improving our ability to document Earth’s volcanic eruptions, as well as detecting low temperature thermal precursors to larger eruptions.
KeywordsMODIS Time series analysis MODVOLC GOES Kilauea volcano Anatahan volcano Cantarell oil field
This work was funded by NASA grant NNX08AF08G and the MASINT Consortium to RW. The authors thank Harold Garbeil for writing the georeferencing software used in this work. The manuscript was improved by thoughtful reviews from Matthew Patrick, Martin Wooster, and Andrew Harris. This is HIGP publication 1876 and SOEST publication 8057.
- Cuomo V, Lasaponara R, Tramutoli V (2001) Evaluation of a new satellite-based method for forest fire detection. Int J Remote Sens 22(9):1799–1826Google Scholar
- Di Bello G, Filizzola C, Lacava T, Marchese F, Pergola N, Pietrapertosa C, Piscitelli S, Scaffidi I, Tramutoli V (2004) Robust satellite techniques for volcanic and seismic hazards monitoring. Ann Geophys 47(1):49–64Google Scholar
- Flynn L, Wright R, Garbeil H, Harris A, Pilger E (2002) A global thermal alert system using MODIS: initial results from 2000–2001. Adv Environ Monit Model 1(1):37–69Google Scholar
- Heliker C, Swanson DA, Takahashi TJ (2003) The Pu‘u ‘Ö‘ö-Küpaianaha eruption of Kïlauea volcano, Hawai‘i: the first 20 Years. USGS Prof Paper 1676Google Scholar
- Mouginis-Mark PJ, Francis PW, Friedman T, Garbeil H, Gradie J, Self S, Wilson L, Crisp JA, Glaze L, Jones K, Kahle AB, Pieri DC, Zebker H, Krueger A, Walter L, Wood C, Rose W, Adams J, Wolff R (1991) Analysis of active volcanoes from the earth observing system. Remote Sens Environ 36:1–12CrossRefGoogle Scholar
- Pergola N, Pietrapertosa C, Lacava T, Tramutoli V (2001) Robust satellite techniques for volcanic eruptions monitoring. Ann Geophys 44(2):167–177Google Scholar
- Pergola N, Marchese F, Tramutoli V, Filizzola C, Ciampa M (2008) Advanced satellite technique for volcanic activity monitoring and early warning. Ann Geophys 51(1):287–301Google Scholar
- Pergola N, Giuseppe DA, Lisi M, Marchese F, Mazzeo G, Tramutoli V (2009) Time domain analysis of robust satellite techniques (RST) for near real-time monitoring of active volcanoes and thermal precursor identification. Phys Chem Earth 34:380–385Google Scholar
- Tramutoli V (1998) Robust AVHRR Techniques (RAT) for environmental monitoring theory and applications. In: Checchi G, Zilioli E (eds) Earth surf remote sens II. SPIE, Barcelona, Spain, pp 101–113Google Scholar
- Tramutoli V, Di Bello G, Pergola N, Piscitelli S (2001) Robust satellite techniques for remote sensing of seismically active areas. Ann Geophys 44(2):295–312Google Scholar