Asep Saepuloh

Applying Bayesian Decision Classification to Pi-SAR Polarimetric Data for Detailed Extraction of the Geomorphologic and Structural Features of an Active Volcano

An understanding of the geomorphology and distribution of surface materials on an active volcano is crucial to characterize eruptions and mitigate volcanic hazards. For volcanoes, synthetic aperture radar (SAR) remote sensing is the only useful observation and monitoring technology that can be undertaken in any weather condition. This letter uses the data from one type of airborne SAR system termed polarimetric and interferometric airborne SAR and L-band microwaves to classify SAR imagery into geomorphologic units, based on a scattering mechanism, using the example of Mt. Sakurajima, a representative active volcano situated in southern Japan. This is accomplished by adopting a Bayesian decision classification (BDC) scheme applied to two polarimetric parameters, namely, entropy and the type of scattering mechanism, which are derived from Cloude-Pottier decomposition of full polarimetry. In spite of the thick vegetation cover, BDC can divide SAR imagery from Mt. Sakurajima into three geomorphologic units: volcanic cone, terrace, and foot. The suitability of the BDC classification of microwave sensor imagery-and its superiority over a traditional classification scheme, the K -means unsupervised classification-is confirmed by polarimetric signature analysis and ground-truth surveying that directly quantifies surface scattering.

Identifying Surface Materials on an Active Volcano by Deriving Dielectric Permittivity From Polarimetric SAR Data

Dielectric permittivity εr measured on the Earths surface is an effective property for characterizing surface materials in terms of rock type and water content, particularly in highly changeable environments such as active volcanoes. We propose a technique termed dielectric permittivity from polarimetric synthetic aperture radar (dPSAR) to quantify εr using a single scene of polarimetric SAR data, based on the small perturbation model of backscattering (SPMB). For an optimal solution, the Nelder-Mead simplex method was combined with SPMB. The application of dPSAR to a scene of ALOS PALSAR data from the vicinity of Mt. Merapi, Indonesia, correctly identified the relative value ranges of εr for pyroclastic flow and tephra deposits accompanying large eruptions that occurred on November 5, 2010; their means were 2.55 and 3.07, respectively. Pore water within porous ashes is a plausible factor for increases in the εr of the tephra.

Using PS-InSAR to detect surface deformation in geothermal areas of West Java in Indonesia

In this paper, the Persistent Scatterer InSAR (PS-InSAR) technique is applied in order to investigate the ground deformation in and around two geothermal areas in West Java, Indonesia. Two time-series of ALOS PALSAR and Sentinel-1A acquisitions, covering the period from 2007 to 2009 and 2015–2016, are analysed. The first case study examines the Wayang Windu geothermal zone where the PS-InSAR analysis provides an overview of the surface deformation around a geothermal reservoir. Uplift is observed around the injection wells in the area. The second example involves the use of the PS-InSAR technique over a more recent geothermal system in Patuha field. Again, a pattern of uplift was observed around the only available injection well in the area. Due to the dense vegetation coverage of the geothermal areas in West Java, the longer wavelength ALOS PALSAR data is provides better results by identifying a larger number of PS points. Additionally, experiments have been carried out to compare the resulting deformation with another example of the fluid migration process i.e. water extraction in Bandung basin. The potential of sentinel-1A and ALOS PALSR data are compared in all the experiments.

Identification of linear features at geothermal field based on Segment Tracing Algorithm (STA) of the ALOS PALSAR data

Indonesia has about 40% of geothermal energy resources in the world. An area with the potential geothermal energy in Indonesia is Wayang Windu located at West Java Province. The comprehensive understanding about the geothermal system in this area is indispensable for continuing the development. A geothermal system generally associated with joints or fractures and served as the paths for the geothermal fluid migrating to the surface. The fluid paths are identified by the existence of surface manifestations such as fumaroles, solfatara and the presence of alteration minerals. Therefore the analyses of the liner features to geological structures are crucial for identifying geothermal potential. Fractures or joints in the form of geological structures are associated with the linear features in the satellite images. The Segment Tracing Algorithm (STA) was used for the basis to determine the linear features. In this study, we used satellite images of ALOS PALSAR in Ascending and Descending orbit modes. The linear features obtained by satellite images could be validated by field observations. Based on the application of STA to the ALOS PALSAR data, the general direction of extracted linear features were detected in WNW-ESE, NNE-SSW and NNW-SSE. The directions are consistent with the general direction of faults system in the field. The linear features extracted from ALOS PALSAR data based on STA were very useful to identify the fractured zones at geothermal field.

Identification of Surface Manifestation at Geothermal Field Using SAR Dual Orbit Data

The Wayang -Windu Geothermal Field located in West Java, Indonesia is a geothermal field under tropical zone which is identified by high precipitation, dense vegetation, and extensive weathering/alteration. The clouds due to high precipitation and vegetation conditions on the tropical zone inhibit the identification of surface manifestation using optical remote sensing techniques. In this paper, we reduced these inhibiting factors using microwave remote sensing techniques termed as Synthetic Aperture Radar (SAR). The SAR dual orbits were used to observe the targets on the surface by minimizing the effects from the clouds and dense vegetation cover. This study is aimed to identify surface manifestation based on Geo morphologic and Structural Features (GSF) of the SAR in Ascending and Descending orbits. The Linear Features Density of SAR (lifedSAR) method was applied to quantify the linear features of the ground surface and served as basis of surface manifestation identification. Based on the lifedSAR and field observations, the surface manifestations could be detected succesfully at Wayang and Cibolang craters with density about 45%. The soil measurements were used validate the result and to interpret the correlation between LFD and surface manifestations.

Impact of oil and gas field in sugar cane condition using landsat 8 in Indramayu area and its surrounding, West Java province, Republic of Indonesia

This study tried to monitor sugar cane condition surrounding of oil and gas field area. The spectral approaches were conducted for mapping sugar cane stress. As an initial stage Landsat-8 was corrected radiometrically and geometrically. Radiometric correction is an important stages for spectral approaching. Then all pixel values were transformed to the surface reflectance. Several vegetation indices were calculated to monitor vegetation stress surrounding of oil and gas field. NDVI, EVI, DVI, GVI, GRVI, GDVI and GNDVI were applied for generating tentative sugar cane stress images. The results indicated that sugar cane surrounding of oil and gas field has been influenced by oil and gas field.

Identification of Altered Minerals Based on Synthetic Aperture Radar (SAR) For Mineral Exploration in a Tropical Area

Geological investigation by remote sensing using surface physical properties in tropical regions is challenging. To minimize the effects of atmosphere and vegetation in the obtained optical images, we used the synthetic aperture radar (SAR) images. The phased array L-band synthetic aperture radar (PALSAR) onboard the advanced land observing satellite (ALOS) was selected due to ability of the L-band to penetrate clouds and canopy vegetation. The polarimetric decomposition method based on Cloude–Pottier classification was used as the basis for backscattering analyses. The Ciseuti area in West Java, Indonesia was selected as the study site due to the existence of mining activities, including gold and galena mines. The identification is focused on the spatial distribution of prospected minerals regardless of cloud and vegetation canopy. The classified prospect zones could be extended using the Cloude– Pottier polarimetric decomposition into moderate random entropy and alpha double bounce scattering at argillic alterations, moderate random entropy and alpha surface scattering at intermediate argillic alterations, and highly moderate random entropy and alpha volume diffusion at advanced argillic alterations. The entropy and alpha extracted from ALOS PALSAR data based on Cloude–Pottier decomposition were very useful for identifying alteration zones.

Characterizing Geothermal Surface Manifestation Based on Multivariate Geostatistics of Ground Measurements Data

Mt. Wayang Windu is one of geothermal field located in West Java, Indonesia. The characterization of steam spots at surface manifestation zones based on the soil physical measurements of the area is presented in this study. The multivariate geostatistical methods incorporating the soil physical parameter data were used to characterize the zonation of geothermal surface manifestations. The purpose of this study is to evaluate the performance of spatial estimation method of multivariate geostatistics using Ordinary Cokriging (COK) to characterize the physical properties of geothermal surface manifestations at Mt. Wayang Windu. The COK method was selected because this method is favorable when the secondary variables has more number than the primary variables. There are four soil physical parameters used as the basis of COK method, i.e. Electrical Conductivity, Susceptibility, pH, and Temperature. The parameters were measured directly at and around geothermal surface manifestations including hot springs, fumaroles, and craters. Each location of surface manifestations was measured about 30 points with 30 x 30 m grids. The measurement results were analyzed by descriptive statistics to identify at the nature of data. The correlation among variables was analyzed using linear regression. When the correlation coefficient among variables is higher, the estimation results is expected to have better Linear Coregionalization Model (LCM). LCM was used to analyze the spatial correlation of each variable based on their variogram and cross-variogram model. In oder to evaluate the performance of multivariate geostatistical using COK method, a Root Mean Square Error (RMSE) was performed. Estimation result using COK method is well applicable for characterizing the surface physics parameters of radar images data.

Performance analysis of mineral mapping method to delineate mineralization zones under tropical region

Geothermal explorations and productions are currently being intensively conducted at certain areas in Indonesia such as Wayang Windu Geothermal Field (WWGF) in West Java, Indonesia. The WWGF is located at wide area covering about 40 km2. An accurate method to map the distribution of heterogeneity minerals is necessary for wide areas such as WWGF. Mineral mapping is an important method in geothermal explorations to determine the distribution of minerals which indicate the surface manifestations of geothermal system. This study is aimed to determine the most precise and accurate methods for minerals mapping at geothermal field. Field measurements were performed to assess the accuracy of three proposed methods: 1) Minimum Noise Fraction (MNF), utilizing the linear transformation method to eliminate the correlation among the spectra bands and to reduce the noise in the data, 2) Pixel Purity Index (PPI), a designed method to find the most extreme spectrum pixels and their characteristics due to end-members mixing, 3) Spectral Angle Mapper (SAM), an image classification technique by measuring the spectral similarity between an unknown object with spectral reference in n- dimension. The output of those methods were mineral distribution occurrence. The performance of each mapping method was analyzed based on the ground truth data. Among the three proposed method, the SAM classification method is the most appropriate and accurate for mineral mapping related to spatial distribution of alteration minerals.

Observing lava dome roughness on synthetic aperture radar (SAR) data: Case study at Mt. Sinabung and Merapi — Indonesia

Detecting ground surface changes at active volcanoes is crucial for better hazard mitigation. Ground based measurements are commonly used to detect surface changes especially on the flanks near to the summit. However, the selection of observation points is limited by field conditions such as rough terrain and topographical barrier. The few number of observation points may lead to miss-interpretation when the displacements related to magma ascent occurred beneath unobserved flanks. This classical problem is common for dormant volcanoes. Overcoming the problem, we used the Synthetic Aperture Radar (SAR) data to observe surface roughness changes at the summit of active volcanoes. This paper discussed the potential capability of the SAR backscattering intensity to observe ground surface changes in view point of surface roughness around the summit. We presented two study cases at Mt. Sinabung in North Sumatra and Mt. Merapi in Central Java - Indonesia. Mt. Merapi was selected for comparison following published references. Mt. Sinabung is currently active since the first phreatic eruption has been occurred in August 2010. Time series of lava dome roughness on SAR (drSAR) method were used to detect ground surface changes prior to the eruption. Based on this method, the ground surface at the summit of Mt. Sinabung changed from 5121 to 6584 m2. The temporal pattern slightly agreed to the ground surface changes at summit of Mt. Merapi prior to the 2010 eruptions. Observing ground surface changes related to surface roughness at the summit might be used as new tools for observing volcanic activity.