MONITORING BAWAKARAENG POST-LANDSLIDE USING ALOS PALSAR DINSAR AND GROUND MEASUREMENT

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1 MONITORING BAWAKARAENG POST-LANDSLIDE USING ALOS PALSAR DINSAR AND GROUND MEASUREMENT Ilham Alimuddin 1,2, Luhur Bayuaji 2, Josaphat Tetuko Sri Sumantyo 2 and Hiroaki Kuze 2 1,2 Department of Geology, Faculty of Engineering, Hasanuddin University, Indonesia Kampus UNHAS Tamalanrea, Makassar, 90245, ialimuddin@hotmail.com 2 Center for Environmental Remote Sensing (CEReS), Chiba University 1-33 Yayoi Cho, Inage Ku, Chiba Shi, Chiba, Japan Dr. Luhur Bayuaji: ludiro96@yahoo.com, Prof. Hiroaki Kuze: hkuze@faculty.chiba-u.jp Prof. Josaphat Tetuko Sri Sumantyo: jtetukoss@faculty.chiba-u.jp, ABSTRACT: Indonesia is undeniably true is one of the most disastrous country in the world when it comes to incidences of natural disaster. Besides its geologic setting of being squeezed by three major tectonic plates (Eurasian, Pacific and Indo-Pacific plates), its location in tropical region makes it also vulnerable in terms weather imposed disaster such as flood, landslides and typhoon. On the other hand, remote sensing technology has been developed intensively and extensively for the use of natural disaster mapping. On March 24, 2004, one of the major landslides occurred at the head of Jeneberang River in Bawakaraeng Mountain inactive volcano complex bringing huge amount of debris flowing to the lower stream of the river which endangered the Bili-Bili Dam in the district of Gowa, South Sulawesi. The Dam is very essential to the city of Makassar for the supply of drinking water and electrical power plant. This study aims to monitor the distribution and the surface displacement of the uncontrolled collapsed material of the previous landslide from the potential of material blockage to the Bili Bili Dam and possibility of future landslide by utilizing the Japanese Advanced Land Observation Satellite (ALOS) with Phased Array type L-band Synthetic Aperture Radar (PALSAR) images in the Differential Interferometric of Synthetic Aperture Radar (DInSAR) processing technique in three consecutive years of 2007, 2008 and With this technique the surface deformation of the landslide area can be measured and validated with ground measurement of Global Positioning System (GPS) and direct ground survey. Landsat images were also used to analyze the spatial extent of the area. The result shows the surface deformation occurred along the path of the collapse material where river discharge becomes an erosive agent that weakened the strength of the material cohesion which in turn creates further landslides. This phenomenon is dangerous to the people, crops and cattle surfacing this area. Therefore this area especially where cracks are found needed to be mapped and monitored and the result of the study must be distributed. In conclusion, this study is able to show that DInSAR technique with ALOS PALSAR image data can be used to monitor the post landslide area and to support the creation of landslide susceptibility map of the area. Small movement of cracks of 5-10 cms can be mapped in some parts of the surface displacement area. Using remote sensing technology this effort is effective and efficient to map such a large area. Keywords: Post-landslide, ALOS PALSAR, DInSAR, Bawakaraeng, ground measurement. 1. INTRODUCTION Natural disaster In Indonesia have occurred more often statistically compared to a decade ago (BNPB, 2012). Once within a month in 2011, in three different islands, Indonesia had been stricken by earthquake, tsunami, flash floods and volcanic eruptions with severe fatalities to the people and environment. It is obvious that Indonesia is prone to natural disaster due to its position of being squeezed geologically by three major world plates and this fact makes Indonesia one of the most dangerous countries regarding natural disasters. Mountainous areas are specifically vulnerable to sediment related disaster. High slopes with loose material support and high frequency of rainfall are areas fond of landslides incidence. As Indonesia lies on the tropical environment, many landslides incidences occurred in Indonesia due to this cause. Local governments and responsible bodies are not able to fully monitor the area because of the lack of spatial information supporting the decision making regarding the disaster area`s condition.

2 Figure 1. Study site specifically delineate the Jeneberang Watershed by the red outline with yellow line showing the material of the 2004 landslide incidence. Remote sensing data on the other hand is now promising along with the advancement of information technology but yet has not been effectively and efficiently utilized. The use of remote sensing data can contribute to mapping disaster attributes on a variety of scales ranging from community, regional and global scale (Westen, 2008). Various technique and models have also been developed to specifically map landslides. The use of remote sensing data, whether air-, satellite- or ground-based varies according to three main stages of a landslide related study, namely detection and identification; monitoring; and spatial analysis and hazard prediction. (Matternicht et al. 2005). One technique that is now becoming popular in mapping slight deformation changes on the earth surfaces is called Differential Synthetic Aperture Radar Interferometry (DInSAR). This technique is an established method for the detection and monitoring of earth surface processes. This approach has been most successful where the observed area fulfills specific requirements, such as sufficient backscattering, flat slope gradients or very slow changes of vegetation. The emerging Differential SAR Interferometry technique is able map slight surface deformation for a specific type of landslide. This technique can be utilized to create an inventory database. In this study we continue focusing on a large scale mass movement occurred on 26 March, 2004 in Jeneberang Watershed, Indonesia. A research on this landslide event has been conducted by Hasnawir (2006), and JICA Sabo Urgent Investigation Group led by Tsuchiya from Kochi University (2009). The landslides area has also been recently revisited for ground data collection in August 2009

3 and last field observation conducted in 2013 recently. Cracks existing along the steep slope of the landslide crown have been measured since 2006 and continuously monitored for the conuter measures of further incidents. 2. STUDY SITE AND DATA USED This specific study area covers the whole Jeneberang watershed in South Sulawesi Province, Indonesia, but focus on the local area where the previous landslide 2004 occurred. (Figure 1). The climate of Sulawesi Island is tropical. The northeast monsoon gives rise to the rainy season between November and May (with the maximum rainfall being in December and January), and the southwest monsoon causes the dry season between June and October. The monthly rainfall is more than 700 mm per month from December to February, and reaches 900 mm in January. The average annual rainfall is 4,424 mm. Under these conditions, the outlet valley from the caldera can maintain its dominant downcutting position by capturing the runoff from the primary depression to enlarge its drainage basin (Tsuchiya et al, 2009). The March 2004 landslide impacted significant damage with special concern on Bili-Bili Dam located downstream, which supplies water to the city of Makassar (capital city, population of 1.2 million). Approximately m 3 volume of earth material consisting of volcanic fragmental rocks and debris (Bawakaraeng Formation) slid to the upper part of River Jeneberang, covering one village, one primary school with 32 casualties (Tsuchiya et al. 2009). Some of the mechanical factors that enhanced this landslide are the tremendous height of the side wall of the caldera, fragility of the bedrock of the side wall, and susceptibility to erosion of the accumulated sediment inside the caldera (Hasnawir et al, 2006). This landslide is categorized as rock avalanche and the movement type is rotational and triggered by heavy rainfall. It has been nearly 10 years since the big horrifying landslide occurred. There also have been major physical changes especially to the condition of the landslide material. In order to visually identify the latest condition of the affected area of the landslides, we used the latest Landsat 8 satellite images acquired on 27 April Synthetic Aperture Radar (SAR) images of ALOS PALSAR acquired in three consecutive years of , , and were used in this study. All the SAR images are on the descending mode. Figure 2 shows the new Landsat 8 image with false composite band of 753 overlaid with the newest topography measured using detail digital field measurement of GPS theodolite. Figure 2. Landsat 8 Image with FCC of 753 overlaid with the field measurement contour

4 A B Figure 3. A. Digital Elevation Model (DEM) image generated form DInSAR processing pair of image. B. DInSAR processed image showing the affected area of previous landslide Black line indicate the watershed boundary. Red line focus of the landslide study. 3. METHODOLOGY Synthetic Aperture Radar Interferometry (InSAR) is an established method for the detection and monitoring of earth surface processes. Generally two SAR data acquisitions, called scenes or images, of the same area are required to generate interference fringes resulting from phase differences that can be interpreted as heights or displacements. The typical SAR geometry of master and slave scene with a short baseline for the detection of earth surface changes (Riedel and Walther, 2008; Colesanti and Wasowski, 2006). In SAR interferometry (InSAR), the phase data of SAR images are analyzed to derive the local topography (original InSAR) or detect and quantify the ground displacement that has occurred in the slant-range direction between the two acquisitions data called Differential-InSAR, (Agustan et.al, 2010). The result of this process is generally called DInSAR, which estimates the ground displacement in the slant-range direction Figure 3.. DInSAR processing has been applied to 3 different level 0 data of ALOS PALSAR from different acquisition years of with the JAXA/SIGMA SAR processing software (Shimada, 1999). Each pair of data went through the same procedure from image coregistrations, interferogram generation until phase unwrapping. Before phase unwrapping the DInSAR image was filtered using Goldstein and Werner filter with preconditioned conjugate gradient (PCG) (Singhroy and Molch, 2004). At the end all images were geocoded using cubic convolution with UTM transformation by resampling the DInSAR data to 12.5 resolution (Figure 4). We processed 3 scenes of path 84 row 309 where all scenes are on the descending mode with single HH polarization. Change detection analysis and thematic classification have been implemented to both the visible and SAR images over the study area to generate landslide susceptibility map. We conducted field survey to this area to check how the material has changed significantly in 2 different year, in 2009 and the latest in 2013 by visiting the affected area. We consulted the affected area with Japanese consultant working in this area in building 6 Sabo Dams in effort to reduce the invasion of erosion of the run off material. We managed to compare the ground measurement taken in detail measurement of the latest condition of the material. The field survey that was conducted in August 2009 was conducted by taking GPS measurements and sample material and the second visit was to obtain the crack locations and dimensions. The discussions with the staffs of The Jeneberang River Sediment Control Project under the coordination of public works office in South Sulawesi gave us significant overview of the post landslide monitoring. The project started monitoring the cracks along the weak zone of the upper head of the landslide since 2006 and continued until The crack location was measured regularly on monthly basis by staffs assigned to do the task. The measurement was done by measuring the distance of the crack. The pictures in Figure 5 shows how the crack are

5 still occurring and endanger the local people and cattle pass around this material. This is also happening to the new cracks that are now being recorded. Sometimes the displacement was nowhere to be found because they already collapsed. The displacement is important to be measured as it is the indication of the movement. These cracks become dangerous if they are not given indications because these materials can suddenly slide or drop. Figure 4. DInSAR Flow chart (Bayuaji, 2007). Ideally, the SAR images acquired should be the same time as the measurement years and by overlying with the DInSAR processed images we expect to improve the exact location and rate of changes in that area. Overlying this two data will give improvement on the landslide potential locations. A B Figure 5. A. Latest condition showing the material condition B. Future crack is still occurring.

6 4. RESULTS AND DISCUSSIONS Based on the DInSAR image processing,, the DInSAR images pair of 2007/2008 shows a linear movement of 5-10 cms along the line of the cracks area, suggesting the occurrence of cracks/gaps related to subsidence before the landslide event and this will continue to move which is why they must be monitored. Ground validation using high resolution differential GPS from the field also supports this interpretation of the DInSAR image. From project report of Jeneberang Sabo Dam, we managed to obtain the GPS location of the cracks that occurred before and after the landslides. Overlaying this points allow us to confirm the throne and the head of the landslides (Figure 2). The image analysis shows us there is a slight deformation along the slope of the potential landslide. 5. CONCLUSIONS We have proved that DInSAR processing image has given variety of results on surface displacement mapping. This study has shown that ALOS PAL SAR image pairs of the designated areas give good coherence image which therefore will give better result on the DInSAR images. Integrating new Landsat 8 image confirm and can complement the change detection analysis and Differential Interferometric SAR (DInSAR) is proven to be one of the effective methods in mapping surface displacement especially for landslides and post landslides for the purpose of monitoring. Integration of remote sensing and GIS can provide information on prior and post-landslide situations. From the DInSAR image processing it is observed that there has been a slight deformation measured until 15 cms along the line of sight (LOS) and this confirms that the cracks had been widening and will continuously moving. Post landslide material must be warned to people working in this area to prevent further casualties due to sudden fall, drop or sliding material. Further works must be carried out to validate the accuracy of the DInSAR image as it is still an estimation result. Validation with ground checked must also be carried out. Applying DInSAR method with ALOS PALSAR images has confirmed a better result considering ALOS PALSAR has better accuracy for the device specifications compared to JERS-1. The next step is to input DInSAR image to the GIS map to create landslides susceptibility map hence creating landslides inventory. ACKNOWLEDGEMENT The writers would like to thank you Japan Aerospace Agency (JAXA) through Dr. Shimada for the cooperation of using SIGMASAR software. REFERENCES [1] Asian Disaster Reduction Center; 2008; Landslide Hazard Mitigation in Indonesia, downloaded onnovember k2009.pdf [2] Alimuddin, I., Bayuaji, L.,, Haeruddin C. Maddi, Sri Sumantyo, J.T., and Kuze, H, Developing tropical landslide susceptibility map using DInSAR technique of JERS-1 SAR data,2011, International Journal of Remote Sensing and Earth Sciences Vol. 8: [3] Alimuddin. I, Bayuaji. L, Sri Sumantyo J. T., and Kuze. H, 2011, Surface deformation monitoring of Miyakejima volcano using DInSAR technique of ALOS PALSAR images, Proceeding of The 2011 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2011) : , [4] Baja.S, Ramli, M. and Lias, S.A., 2009, Spatial-based assessment of land use, soil erosion, and water protection in the Jeneberang valley, Indonesia, Biologia (64/3): [5] Bayuaji, L., Sri Sumantyo, J.T. and Kuze, H., 2010, ALOS PALSAR D-InSAR for land subsidence mapping in Jakarta, Indonesia, Can. J. Remote Sensing, 36(1) : 1 8. [6] Chen, Y., 2000, Monitoring Earth Surface Deformations with InSAR Technology: Principle and Some critical Issues, Journal of Geospatial Engineering, 2 (1) : 3-21.

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