
1-Introduction
Volcanoes are geologically unpredictable :
There is no rigorous methodology exists for predicting an impending eruption and the evolution of eruptive activity. Early detection of volcanic activity is mainly based on the observation of an anomalous increase in seismic activity and ground deformations. Substantial variations in these factors, which are a result of increased pressure of the magmatic system and magma motion, certainly constitute a basic tool for issuing a warning, but not all volcanoes behave as expected and existing data are too limited for reliable prediction on a global scale
Structure of volcanoes :
The main parts of a volcano are:
1.The crater, a depression at the top of the volcano from which volcanic material has been ejected.
2.The vent, the conduit between crater and the magma.
3.The cone, the area around the crater at the top of the volcano, made up of material ejected during an eruption. Many volcanoes have several craters, cones and vents.
Seismic Method :
Seismic monitoring is a powerful tool because it allows real-time data analysis. However, the seismic signals on volcanoes are complex and variable. So-called volcano-tectonic (VT) earthquakes are not directly linked to magma movement. Moreover, most data acquisition systems are tuned to the high-frequency band allowing detection of source parameters of the volcano-tectonic events
How can Remote Sensing Help ?
New developments in remote-sensing techniques have expanded the capability of scientists worldwide to monitor volcanoes using satellite. Two types of satellites are used for monitoring active volcanoes. One is known as "geostationary" while the other satellite is known as "low Earth orbit".
Satellites are used for six main objectives in regards to volcanic eruptions:
1) Rapid detection of an eruption plume
2) monitoring thermal energy emitted from the volcano
3) large area mapping of surface deformation of a volcano
4) measurement of volcano topography and topographic change
5) illustrating spatial distribution of ash, gases and aerosols produced by eruptions, and
6) referencing a data set for each volcano for quantifying of future changes.
Indications of volcanic eruptions :
•SO2 content
•Seismic activity
•Thermal
variation
•Ground leveling
Volcanoes
Volcanoes are often described as active, dormant or extinct. An active volcano is one that has erupted in some way relatively recently: say, within the last few hundred or few thousand years. A dormant volcano is one that hasn't erupted for some time, perhaps several hundred or thousand years, but is still considered likely of erupting sometime in the future. Extinct volcanoes are ones that are considered incapable of erupting. Some volcanoes labeled as extinct, however, such as mt. St. Helens, have erupted quite violently.
Volcanos are ..
•Predictable
•Unpredictable
•Continuous
Kluichevskoi volcano
kluichevskoi volcano, russia, was chosen in this study due to its activity state since 1999, which has produced multiple pyroclastic flows. Kluichevskoi volcano is also at higher latitudes, ensuring that many data acquisitions are possible as a result of the overlap of adjacent imaging swaths approaching the poles, and hence, an increase in the number of cloud-free data are available.
Methodology:
ASTER SATELLITE:
ASTER supplies high resolution visible and infrared imagery, plus thermal imagery and stereographic capabilities. The collection of ASTER available through GLCF is designed to complement overall project goals of distributing a global, multi-temporal, multi-spectral and multi-resolution range of imagery appropriate for land cover analysis
Satellite | Sensor | Band No. | Spectral Range | Scene Size | Pixel Res |
ASTER | VNIR | 1-3 | 0.52 - 0.86 µm | 120 X 150 km | 15 meter |
SWIR | 4-9 | 1.600 - 2.430 µm | 30 meter | ||
TIR | 10-14 | 8.125 - 11.65 µm | 90 meter |
Steps:
1-Radiometric calibration
radiometric calibration plans are described for the ASTER satellite images, which is a high spatial resolution imaging spectro-radiometer. ASTER comprises three subsystems which acquire images in three separate spectral regions: the visible and near infrared (VNIR), the shortwave infrared (SWIR), and the thermal infrared (TIR). The absolute radiometric accuracy is required to be better than 4% for VNIR and SWIR radiance measurements, and 1 K to 3 K, depending on the temperature region from 200 K to 370 K, for TIR temperature measurements.
2-Thermal atmospheric correction
The water vapor scaling (WVS) method involves an atmospheric correction algorithm for thermal infrared (TIR) multispectral data, designed mainly for the five TIR spectral bands of the advanced spaceborne thermal emission and reflection radiometer (ASTER) on the terra satellite. First, this method is improved for better applicability to ASTER/TIR imagery. The major improvement is the determination of a water vapor scaling factor on a band-by-band basis, which can reduce most of the errors induced by various factors such as algorithm assumptions.
3-The emissivity normalization
The accuracy of three techniques for recovering surface kinetic temperature from multispectral thermal infrared data acquired over land is evaluated. The three techniques are the reference channel method, the emissivity normalization method, and the alpha emissivity method. The methods used to recover the temperature of artificial radiance derived from a wide variety of materials.
4-ROI
regions of interest (ROIs) are selected samples of a raster that are identified for a particular purpose. ROIs could be used for processing in some ENVI tools, such as to extract statistics for classification. To create and manage ROIs, click the region of interest (ROI) tool button on the toolbar. When you define an ROI, you specify the pixels of an image that will be in or out of the ROI. For more information on the rules that determine when a pixel is included in an ROI, see the ROI pixel inclusion background topic.
5-Subset data from ROIs
often, image files contain areas much larger than a particular study area. In these cases, it is helpful to reduce the size of the image file by including only the area of interest. This not only eliminates the extraneous data in the file, but it speeds up processing due to the smaller amount of data to process. The study area has been subset from the original images. In this study, the study area has been extracted from the whole satellite image using a ROI rectangle.
Discussion
surface temperature
_Background temperature
_ Maximum temperature
_ Anomaly
Date | maximum Temp. | Background Temp. | Anomaly |
2009 04 07 | -2.6 | -17.12 | 14.52 |
2009 04 09 | -6.1 | -16.16 | 10.06 |
2009 04 25 | -9.3 | -17.19 | 7.89 |
2009 05 18 | 0.77 | -3.107 | 3.877 |
2009 05 25 | 5.7 | -2.2 | 7.91 |
2009 06 12 | 6.6 | 0.807 | 5.804 |
2009 06 19 | 8.3 | 2.206 | 6.106 |
2009 07 12 | 5.4 | -5.44 | 10.86 |
2009 07 14 | 8.6 | -0.6 | 9.2 |
2009 07 28 | 47.2 | 24.48 | 17.74 |
4-Conclusion
As a conclusion, it is clear that remote sensing techniques and analysis of thermal satellite images is considered as an effective method in volcanic eruption prediction pays off and so far it is the easiest, the most applicable and the least dangerous method aiming the same objective of other geophysical techniques in this field of study which is saving lives of as many as it could be.
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