Monitoring the thermal anomalies around Milos Island with satellite thermal data

Although remote sensing is recognized as a powerful tool in the collection, analysis and modelling of environmental data, less attention has been given to the use of Thermal Infrared (TIR) remote sensing. Thermal property of a material is representative of upper several centimetres of the surface. As in thermal remote sensing we measure the emitted radiations, it proves to be complementary to other remote sensing data and even unique in helping to identify surface materials and features such as rock types, soil moisture, underwater springs, geothermal anomalies etc. During the last two decades a series of satellite and airborne sensors have been developed to collect TIR data from the earth surface, such as HCMM, Landsat TM/ETM+, AVHRR, MODIS, ASTER, and TIMS. In addition to Land Surface Temperature (LST) measurements, these TIR sensors may also be utilized to obtain emissivity data of different surfaces with varied resolutions and accuracies.
   The islands of Nisyros, Yali, Kos, Santorini, Milos, Poros, Aegina and the peninsula of Methana constitute the Hellenic Volcanic Island Arc. This arc seems to be geodynamically very active since it comprises the largest volumes of volcanic materials and is at present a region of high tectonic activity. This activity is very often expressed with earthquakes, gas explosions and hydrothermal eruptions, volcanic eruptions, landslides, etc.
   TIR data were used in order to detect undersea hydrothermal activities along the Hellenic Volcanic Island Arc. In this study there is a effort to monitor the thermal anomalies into the sea around Milos Island for the last 25 years using TIR data. More especially thermal data from the LANDSAT-TM the LANDSAT-ETM and ASTER sensors were used. The resolution of the thermal infrared bands ranges between 60 and 120 m. The sensitivity of these sensors is about 0.50C in the region of 10.4-12.5μm (thermal infrared zone) of the Electromagnetic Spectrum. Thus the sensors can contribute to the detection of thermal anomalies (water outflows into the sea environment), which are useful to hydrothermal studies.
   All the satellite data were orthorectified. Then using the appropriate algorithms the radiation was converted into Celsius Degrees in order to calculate the surface temperature of the area. Then in order to better distinguish thermal deviations the temperatures have been classified using the density slicing method. The results are presented in this study.