Mapping Alteration Zone using SAR and Hyperspectral data

Field mapping activity for an active volcano mainly in the Torrid Zone is usually hampered by several problems such as steep terrain and bad atmosphere conditions. In this paper we present a simple solution for such problem by analyzing Synthetic Aperture Radar (SAR) and optical sensor image data. By a combination of two types of satellite images, we detected the geothermal paths by identifying the alteration zone termed A-zone. The main purpose of this study is to discriminate alteration of the pyroclastic flow deposits and estimate their alteration degree by selecting Mt. Merapi in central Java, Indonesia, as a study site and targeting the eruptions during May-June 2006. To delineate the A-zone, we applied an image fusion technique using a ratio image of RADARSAT-1 SAR β0 data and an MNF transformation of Hyperion image data. The acquisition dates of these images were almost the same to reduce large different change in the image characteristics. In addition, a field survey was carried out to check the usefulness of the image fusion results. The A-zone is found to extend in the eastern flanks by 1.5 km2 which are covered mainly by the old pyroclastic flow deposits. This area can be interpreted as an ascent flow zone of hydrothermal fluids beneath the summit.

Figure 1: Mt. Merapi on a RGB color composition of a Hyperion image using three bands, 2.19 μm (R), 1.65 μm (G), and 1.07 μm (B). Red rectangular and red “+” stand for the main target area and rock sample locations, respectively.

Figure 2: Field photograph of altered rocks in the eastern part from the summit.

Figure 3: Eigenvalues of Minimum Noise Fraction (MNF) bands selected for image fusion.

Figure 4: Work flows of image fusion for RADARSAT-1 SAR and Hyperion image data.

Figure 5: Color composition of image fusion result by R: Hue (MNF band 1), G: Saturation (MNF band 2), and B: Intensity (RO equalized value). The A-zone is located in yellow-orange portions in the eastern part from the crater (red triangle).

Figure 6: Reflectance spectra of rock samples from visible to short-wave infrared regions.

Figure 7: Reflectance spectra of the AP compared with the reference spectra of clay minerals and silicates in the USGS spectral library.

Figure 8: Distribution of the A-zone overlaid with contour lines of lineament density from directional filtering of the SAR ß0 image on July 4, 2006. The black arrow and green polygon stand for the sample location of the AP and the alteration rocks inferred from SAM classification.


Saepuloh A., Koike K., Discriminating alteration of pyroclastic flow deposits in an active volcano by SAR image analysis for assessing the geothermal system, Proceeding of the World Geothermal Congress 2010 (WGC 2010), in PDF format No. 1336, pp. 1-5, Denpasar-Bali, Indonesia, April 2010.

Surface Detection using Pi-SAR Polarimetric Data

As a microwave remote sensing, an airborne high-resolution multiparameter synthetic aperture radar (Pi-SAR) has two types of frequencies, L-band and X-band.  In this paper, the authors used L-band frequencies of Pi-SAR data due to the wavelength which has possibility to penetrate vegetations. The aim of this study is to demonstrate the effectiveness of Pi-SAR data in analyzing volcanic surface condition. Some image processing methods were used to extract surface terrain features such as unsupervised classification and false color composition. The results were compared with an optical sensor image such as Landsat ETM+ for the same area. Mt. Sakurajima, a typical active volcano in southwest Japan, was chosen as a study site due to its high activity. The results showed that the Pi-SAR data could generate geomorphologic units such as volcanic cone, volcanic-terrace, and volcanic foot which were validated by the polarimetric signatures. On the other hand, lava flows structure appears clear and easy to be distinguished from the other products such as debris pumice or pyroclastic deposits. However, geomorphologic features and lava flows structure could not be detected by the optical remote sensing. Consequently, the Pi-SAR polarimetric data was proved had to have high capability to detect roughness of the volcanic terrain rather than optical remote sensing.

Fig. 1. Study area overlaid on a Landsat ETM+ image

Fig. 2. Color composite of L-band Pi-SAR magnitude data (R=HH; G=HV; B=VV)

Fig. 3. Image classification of Pi-SAR (left) clarifies typical feature for the flat area on the centre of the image, contrary with image classification of Landsat ETM+ image (right) which shows feature continues from the crater to the foot

(A) Volcanic Cone

(B) Volcanic Terrace

(C) Volcanic Foot

Fig. 4. Polarimetric signatures for each geomorphologic feature

Fig. 5. Lava edge detection by using synthetic color image of Pi-SAR data (R=HH; G=HV; B=VV)


Saepuloh A., Koike K., Omura M., Iguchi M., The application of Pi-SAR polarimetric data to detect surface condition of an active volcano, Proceeding of the 9th International Symposium on Mineral Exploration (ISME09), Bandung, Indonesia, pp. 236-240, September 2006.

Detecting and Modeling SAR data to Evaluate Geothermal System

Analyzing the volcanic product mainly for pyroclastic deposits soon after eruption time is difficult because the gases and ashes usually cover over half more the volcanic field. However the microwave remote sensed system can solve the difficulties. In this paper we demonstrate how the radar system using microwave wavelengths can detect the volcanic products soon after eruption. The main aim of this detection is to estimate the geothermal system, especially for fast assessment purpose.
The existence of pyroclastic deposits implies that explosive eruptions have occurred. Calculation of the volume of the deposits can be used to estimate the size of their parental magma chamber. Our approach for geothermal system in an active volcano is based on primarily understanding the volume and characteristic of pyroclastic rocks (tephra). The study site is located at Mt. Merapi, Indonesia which has been active during the last 5 years.