During the last century, Merapi eruptions characterized by effusive dome growth and collapsed producing “Merapi Type” pyroclastic flows. The eruption of Mt. Merapi in November 2010 was more explosive, a VEI 4 eruption, involving large size dome and fountain collapse pyroclastic flows as well as ash falls. To obtain the deformation precursor to the eruption, we applied a Differential Interferometric Synthetic Aperture Radar (D-InSAR) with short-continuous baseline method using ALOS PALSAR data. We collected 38 scenes single and dual polarization modes in total. Among them, there are only 25 scenes plausible for D-InSAR analysis due to low coherency and data quality. To reduce the atmospheric disturbance in the interferograms, we combined the Pair-wise Logic (PWL) with Referenced Linear Correlation (RLC) method. The Electronic Distance Measurement (EDM) and Seismicity statistics prior to the eruption were used to know the correction performance. This proposed method was proved effective to reduce the atmospheric phase twice from deformation phase.

Fig.1. Original interferogram containing deformation, atmospheric delay, and noise.

Fig.2. Interferogram after atmospheric phase delay removal.

Source:

Saepuloh A., Urai M., Evaluating the Deformation and Atmospheric Signals in the InSAR of ALOS PALSAR data at Mt. Merapi, Abstract of Workshop on Renovation of Observation of Natural Disaster 2012, DPRI-Kyoto University, Japan, pp. 3-7, September 2012.

Understanding precursory signal leading to a large and explosive eruption, such as Merapi eruption in 2010, is the key to a successful hazard assessment in the future. Towards resolution of this problem, time series of Differential Interferometric SAR (D-InSAR) of ALOS/PALSAR data together with thermal radiance at summit area were analyzed to characterize magmatic process. The D-InSAR could detect deformation changes in between two eruption episodes of Merapi in 2006 and 2010. The maximum uplifting rate ~0.7 mm/day is observed twice: two years and one month before eruption in October 26, 2011. The first uplift is related to magma ascent and the later is precursory to an imminent eruption. Thermal radiance of ASTER data not only served as indicator on the arrival of fresh magma near the surface, but also to confirm whether or not the deformation signal is related to the imminent eruption.

Fig. 1. Location of Mt. Merapi in Central Java, Indonesia.

Fig. 2. The interferograms of ALOS/PALSAR shows the uplifting and subsidence phenomena prior to the eruption.

Fig. 3. ASTER TIR images of Mt. Merapi from 2006 to 2010. The hot spots indicated the beginning and the ending of one periodical of eruption.

Fig. 4. The estimated-deformation rate at Mt. Merapi.

Source:

Saepuloh A., Urai M., Widiwijayanti C., Aisyah N., Observing 2006-2010 ground deformations of Merapi volcano (Indonesia) using ALOS/PALSAR and ASTER TIR data, Proceeding of the IEEE International Geoscience and Remote Sensing Symposium 2011 (IGARSS-2011), Vancouver, Canada, July 2011.

Surface volcanic rocks identification in active volcano is crucial not only to mitigate volcanic hazards, but also to characterize eruption, urban rehabilitation, and reconstruction especially after eruption. Remote sensing technology provides ground surface data relatively cheap and large coverage area. However, the application of remote sensing technology for identifying volcanic rocks distribution is still limited. The cloud is always the main problem of the optical sensor as well as the vegetation and geometric distortion for microwave sensor. Overcoming the problem, we tried to identify the volcanic rocks distribution using Polarimetric SAR data of The Phased Array type L-band Synthetic Aperture Radar (PALSAR) onboard The Advanced Land Observing Satellite (ALOS). The aim of this study is to evaluate the possibility using polarimetric SAR data for delineating volcanic rocks. The spatial comparison using optical sensor data was used to delineate the Geomorphologic and Structural Features (GSF) in the Polarimetric SAR data. Then, a seed fill method with pixel growth criterion was applied to identify volcanic rocks distribution based on the GSF automatically. The geological map was used to validate this approach. The Advanced Land Imager (ALI) instrument onboard EO-1 satellite and ASTER GDEM 30-m were used as benchmark to predict the effect of vegetation canopy and gradient slope of topography to the SAR backscattering data. Mt. Tangkuban Parahu located in a dense populated area in Bandung City, West Java, Indonesia was selected as study area. The small phreatic historical eruptions at this volcano have been recorded dominantly since the 19^th century. The distribution of volcanic rocks at Mt. Tangkuban Parahu followed mainly the GSF of the Polarimetric SAR data. Therefore, delineating the GSF of the Polarimetric SAR data is the key to interpret the volcanic rocks distribution. This approach is supposed to be applicable for other regions which have similar geological setting.

Figure 1. Onset of Mt. Tangkuban Parahu in West Java, Indonesia overlaid on the elevation map.

Figure 2. The illustration of backscatter signal in X-, C-, and L-bands respects to the clouds, vegetation canopy, and ground surface.

Figure 3. The color composite of backscattering intensity image for R=HH, G=HV, and B=VV (A), the local incidence angle in radian unit (B), the ASTER GDEM 30-m (C), and the NDVI originated from EO-1 ALI data (D) show the contribution of the surface condition to the polarimetric SAR data. The Red triangle is the summit of MTP.

Figure 4. The geological map of Mt. Tangkuban Parahu (A), the selected seed locations (B), the color composite of the P image for R=σ_HH, G=σ_HV, and B=σ_VV (C)_, and the seed fill map overlaid on the P image (D).

 Source:

Saepuloh A., Urai M., Bayuaji L., Sumintadireja P., Suparka E., Identifying volcanic rocks using geomorphologic and structural features of polarimetric SAR data, Proceeding of the 5th Indonesia Japan Joint Scientific Symposium (IJJSS-2012), October 2012.