Time series analysis of infrared satellite data for detecting thermal anomalies: a hybrid approach

Abstract

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.

A MODIS-Based Robust Satellite Technique (RST) for Timely Detection of Oil Spilled Areas

“…In detail, about 250 MODIS-Aqua data (level 0), downloaded from NASA ocean color web site [48], were converted to calibrated radiances using SeaDAS V7.3. It is worth nothing that the number of the investigated images (i.e., 250) is higher than the one found as minimum value (i.e., 80) to be representative of the investigated long-term time-series signal by an independent study applied on RST approach [49]. Then R rc data were derived for MODIS bands 1-2 and mapped to a WGS84 Lat/Long projection, producing a subset sized 800 × 800 and centred at 34 • N 32.5 • E (e.g., Figure 3) for each pass.…”

“…The results presented in this work seem to indicate that RST can be confidently used for first detecting for certain the presence of a spill, and then mapping its structure. It should be stressed here that a fundamental requirement of a RST near-real-time implementation is the availability of adequate reference fields for a specific area of interest that, as previously mentioned, relies on the availability of a historical dataset of satellite images larger, at least, than 80 records collected for the same month over different years [49,52].…”

On the Potential of Robust Satellite Techniques Approach for SPM Monitoring in Coastal Waters: Implementation and Application over the Basilicata Ionian Coastal Waters Using MODIS‐Aqua

“…Figure 5c shows that for many pixels in the area more than 100 records (survived to the above mentioned discarding procedure) were used for computing µ SPM (x, y) and σ SPM (x, y), with a median value of~92 useful record per pixel over the whole area. Such a number has been found to be, by an independent study applied on RST approach [44], high enough to be representative of the investigated long-term time-series signal. The identification of cloudy pixels has been performed using data acquired in the SWIR bands [45].…”

Remote Sensing of Volcanic Hazards and Their Precursors

“…The importance of being able to detect thermal anomalies from satellites has been highlighted in a number of papers, e.g., [72], [73], [67], [70] and operational tools now exist to provide early warnings of possible volcanic activity, e.g., MODVOLC [74], the Robust Satellite Technique [75] and a hybrid approach [76]. The principle of the detection is based, in its most fundamental level, on instances of high radiance detected at ∼3.7 µm compared with surrounding pixels and against "normal" or climatological radiance behaviour.…”