SAR Techniques Research Articles

SBAS-DInSAR analysis of January 2020 eruption of La cumbre Volcano, Galapagos Archipelago

The Galapagos Archipelago in the Pacific Ocean, situated 1000 km from the Ecuadorian coast, has been considered one of the UNESCO World Heritage sites. Its geographical location, ongoing seismo_volcanic activities, and the island's extreme isolation have led to the development of a wide variety of unique plant and animal species, which inspired Charles Darwin's theory of evolution. La cumbre volcano is one of the most active volcanoes in the Galapagos archipelago and is situated closest to the mantle plume. Eruptions are frequent here, with a record of 30 eruptions since 1800. Recently La Cumbre volcano erupted on 2020 January 12, with 11 seismic tremors recorded on that day with a maximum magnitude of 4.7. The Small Baseline Subset (SBAS) is an advanced Differential Interferometric SAR technique used to generate the deformation time series from the sequence of SAR datasets with a reduced spatiotemporal decorrelation. It is one of the best approaches for monitoring and analyzing surface deformations from space with a millimeter level of accuracy. In this paper, we analyze the January 2020 eruption of the La cumbre volcano using the SBAS technique. 9 Sentinel-1C band SAR data granules from 2019 November 17 to 2020 February 21 were used to generate the deformation time series map for estimating the degree of deformation at the volcanic edifice. As per the analysis, it is evident that the recent eruption has caused a displacement of up to −38 cm at the South Eastern flank of the crater, which has increased initially and then decreased on approaching the steady-state of eruption.

Formulation of Radiometric Calibration for Azimuthal Multi-Angle Observation Space-Borne SAR

A novel space-borne SAR technique, azimuthal multi-angle observation (AMAO), has recently been proposed. It has highly flexible working modes and powerful capability of target information acquisition, but has challenges in achieving radiometric measurement accuracy. The larger the squint angle, the higher the resolution and the more variations involved. Radiometric calibration is a necessary approach to consistent and accurate SAR measurements, but has so far not been carefully considered for AMAO space-borne SAR. This paper addressed the new issues in radiometric calibration arising from the AMAO space-borne SAR system. The AMAO imaging modes are firstly been illustrated, based on which the influences of the AMAO on radiometric calibration are analyzed. To guarantee the accuracy of the radiometric calibration, an appropriate form of the SAR radar equation is derived for AMAO space-borne SAR. On these bases, the calibration models can be obtained by reformulating the novel AMAO SAR equation, and the corresponding normalization method is then proposed. The good experimental performance indicators verify the correctness of proposed models and the effectiveness of the correction method.

Toward a Comprehensive Dam Monitoring: On-Site and Remote-Retrieved Forcing Factors and Resulting Displacements (GNSS and PS–InSAR)

Many factors can influence the displacements of a dam, including water level variability and environmental temperatures, in addition to the dam composition. In this work, optical-based classification, thermal diachronic analysis, and a quasi-PS (Persistent Scatter) Interferometric SAR technique have been applied to determine both forcing factors and resulting displacements of the crest of the Castello dam (South Italy) over a one-year time period. The dataset includes Sentinel-1A images acquired in Interferometric Wide swath mode using the Terrain Observation with Progressive Scans SAR (TOPSAR); Landsat 8 Thermal Infrared Sensor (TIRS) thermal images, and Global Navigation Satellite System (GNSS) for interpreting the motion of the top of the dam retrieved via interferometry. Results suggest that it is possible to monitor both dam water level and temperature periodic forcing factors and resulting displacements via a synergistic use of different satellite images.

First mapping of China surface movement using supercomputing interferometric SAR technique

First mapping of China surface movement using supercomputing interferometric SAR technique

Assessment of groundwater depletion–induced land subsidence and characterisation of damaging cracks on houses: a case study in Mohali-Chandigarh area, India

The present study identified groundwater depletion–induced land subsidence by spaceborne differential interferometric SAR (DInSAR) technique and assessed the damaging impacts of land subsidence by characterising the cracks on houses in Mohali-Chandigarh area of India. First, we identified groundwater depletion hot spots using pre-monsoon and post-monsoon groundwater-level (GWL) data of Central Ground Water Board (CGWB), India, for the period of 2005–2018. Both conventional and advanced DInSAR techniques were used to identify temporally consistent subsiding areas and measure precise rates of subsidence in and around groundwater depletion hot spots. We studied the damaging impacts of land surface deformation by characterising the damaging cracks on houses in affected areas. Groundwater depletion and resulting aquifer-system compaction increase effective stress on confining clay layer which leads to stress build-up at the soil-structure interface and causes damaging cracks on houses. A variety of damaging cracks on houses were observed at the affected areas such as Sohana, Landran, Kharar and Kurali localities. We attempted to characterise the damaging cracks on the basis of shape, size, orientation, surface morphology and texture of the cracks; sense of ground movement; and nature of stress build-up at the interface. We identified tensional cracks, compressional cracks and shear cracks with diverse orientations and separation widths. Finally, a comparative assessment of groundwater depletion, land subsidence and damaging impacts on houses has been made. Using DInSAR technique, we identified land subsidence in and around the groundwater depletion areas in Sohana and Landran (both in Mohali City area), Kharar and Kurali (in Mohali district outside Mohali City area) and Sectors 27–28 in Chandigarh with radar line-of-sight subsidence rates of ~6–7.5 cm/year, ~5.5–6.5 cm/year, and ~ 4 cm/year respectively. We observed that the houses in and around Landran appears to be worst affected followed by Kharar, Sohana and Kurali. From this study, it appears that the type of construction of the houses, e.g. prevalence of masonry and reinforced masonry structures, is primarily responsible for the worst damaging impacts of the houses in Landran and Kurali areas besides the magnitude of land subsidence.

Surface deformation and landslides caused by the 6th nuclear test of North Korea on September 3, 2017 detected by satellite SAR and InSAR techniques

The 6th nuclear test of North Korea on September 3, 2017 produced an mb 6.1 artificial earthquake and significant surface deformations detectable from satellite observations. Wang et al. (2018) have reported the surface displacement of the Mt. Mantap caused by the explosion by applying offset-tracking method to TerraSAR-X SAR images. Based on the assumption of elastic behaviour of the mountain body, they have modelled the rise and collapse of the mountain and suggested the location, depth and energy of the explosion. However, we suspect that the surface displacement might be caused by landslide in which case the elastic modelling would be misleading. In this paper, we use both SAR interferometry and offset-tracking method to quantify the elastic and random deformation caused by the explosion. The 3-D displacement vectors around the rim of the explosion, where the inter-ferometric coherence is maintained, were obtained by using three ALOS-2 interferograms acquired in different orbits. Only east-west component of the displacement vector was valid due to orbital characteristics, which indicates the explosive tendency of the bedrock of up to 25 cm in the rim of the mountain. Deformation on the ruptured zone, where the interferometric coherence is lost, was detected through visual inspection and offset tracking by using two pairs of high-resolution ALOS-2 and TerraSAR-X images. It showed up to 3.5 m displacement on the mountain slope towards the direction of gravity, which is similar to the results of Wang et al. (2018). However, we have visually identified many stable points and features that have not moved at all in the mountain flank surrounded by active surface deformation, which is believed to be stable bedrocks and outcrops. This implies that the displacements observed by the offset method in the mountain flank of the ruptured zone were mostly of landslides caused by the topsoil and boulder stones. It is suggested that elastic behaviour of the mountain body due to the 6th nuclear test of North Korea is unidentifiable and the subsequent modelling might be invalid in the mountain flank of the ruptured zone where surface motion from landslides is dominant.

Forest Aboveground Biomass Estimation Using Multi-Features Extracted by Fitting Vertical Backscattered Power Profile of Tomographic SAR

Forest aboveground biomass (AGB), which plays an important role in the study of global carbon cycle, is one of the most important indicators in forest resource monitoring. Thus, how to estimate and map regional forest AGB quickly and accurately attracts more interests of researchers. Tomographic SAR (TomoSAR) is an advanced SAR technique developed in recent years, which has a wide range application in forest AGB estimation. In this paper, we proposed a multi-feature-based modeling method to estimate forest AGB by fitting backscattered power of TomoSAR vertical profile. The procedure of the proposed method includes four parts: (1) Processing TomoSAR data to obtain the backscattered power of vertical profile. (2) Fitting the backscattered power of the vertical profile. (3) Analyzing the fitted backscattered power distribution characteristic of the vertical profile. (4) Extracting the TomoSAR vertical profile features according to the forest AGB measurement factors based on the dendrometry theory. In this paper, we proposed two new features like the forest average height weighted by backscattered power (BPFAH) and the total length of the backscattered power curve (LBPC) as supplement features to estimate forest AGB by TomoSAR technique. We also used the traditional TomoSAR features including backscattered power at specific height layer of vertical power profile (BPV) and forest average height (FAH) for AGB estimation. After the feature selection, the selected features and the ground field data of the forest AGB were used for regression and modeling. Then the forest AGB was estimated and the accuracy was validated. The results showed that the accuracy of proposed method is 90.73%, and RMSE is 42.45 t/ha. Finally, we discussed the performance of our proposed method compared with traditional methods.

Application of satellite SAR interferometry for the detection and monitoring of landslides along the Tijuana - Ensenada Scenic Highway, Baja California, Mexico

Geomorphological conditions along the Salsipuedes section of Tijuana-Ensenada Scenic Highway (TESH), on the northwestern coast of Baja California, promote the occurrence of slope instabilities which pose a severe threat to the daily basis highway operation. The monitoring systems used for risk management strategies can reduce the impact of landslides. Despite that, the landslides along the TESH have not been continuously monitored due to the high costs and tricky logistics of conventional monitoring techniques. Satellite SAR interferometry demonstrated to be a useful complementary tool for landslide monitoring. This study aims to investigate the potential of satellite interferometric SAR techniques, such as conventional DInSAR and Advanced DInSAR (IPTA approach), for landslide identification and characterization in the Salsipuedes region. For this purpose, ENVISAT ASAR descending and ascending images from the 2003–2010 period have been used. The obtained results showed that, despite the limitations of the techniques, they could be effectively used for the slope displacements detection and monitoring. Based on the results of the interferometric processing, six landslides that have been active during the study period were identified, their geometric parameters were obtained, and their displacement rates were quantified. The landslides were classified as very slow based on measured LOS displacement rates (up to 5.5 cm/yr).

Sinkholes threatening places of worship in the historic center of Naples

The historic center of Naples (southern Italy) is characterized by a variety of elements which, forming its cultural asset, have contributed to its recognition as a UNESCO World Heritage site. Among these, cathedrals, churches and chapels are particularly relevant due to their diffusion and differentiation in age. A singular feature of these places of worship is the presence of a frequently connected network of underground cavities. Such cavities, excavated for quarrying tuff blocks, are susceptible to sudden collapses generating sinkholes which in a number of cases have been responsible for the loss of human lives. On this basis and considering the importance of such elements as attractors of visitors, an analysis of susceptibility to sinkholes of cathedrals, churches and chapels has been here carried out. A sinkhole, cavities and places of worship inventory was prepared using available data and was used, in association to ongoing ground deformation data obtained by DInSAR. Results indicated that 40% of the inventoried sinkholes are a product of cavity collapses and in 45 cases cavities lie underneath places of worship. Geodetic data obtained by Differential Interferometric SAR technique indicate that approximately 1 km2 of the historic center of Naples is subject to ongoing subsiding deformation that in several cases is localized above cavities. The susceptibility map derived from available data indicate the presence of a zone where no cathedral, church and chapel can be subject to sinkholes (1) and 3 zones where they can be subject to sagging (2), potential future cavity collapses (3) and future cavity collapses anticipated by ongoing deformation (4); in detail, 34 places of worship are in zone 2, 57 in zone 3 and 9 in zone 4. Considering an increasing susceptibility level of the identified zones, the 9 places of worship located in zone 4 require a quick response in terms of characterization, stability analysis and real time monitoring have been identified.

Evaluation of land subsidence in Kashmar-Bardaskan plain, NE Iran

The development of agriculture and industry and the increase of population in countries with arid to semi-arid climates have led to more harvesting of groundwater resources and as a result land subsidence in different parts of the worlds. Decades of groundwater overexploitation in the Kashmar-Bardaskan plain in the north-east of Iran has resulted substantial land subsidence in this plain. The plain is considered as an arid to semi-arid zone and facing a negative water balance. The average annual precipitation in the plain is around 191 mm and the evaporation rate is 3956 mm. According to the unit hydrograph of the plain, the annual decline of water level is 1.12 m. In this study, the velocity of subsidence has been determined using Interferometric SAR technique (In-SAR) and radar images of Envisat ASAR and Sentinel-1 for a time period from 2003 to 2017. The results of an InSAR time series analysis indicated that an area of 1200 km2 with different speeds of 5 to 26 cm/year in the satellite line of sight (LOS) is subsiding. The results showed that in addition to the decline of groundwater level, subsurface conditions such as sediments types (fine-grained layers) and their thickness also affect the occurrence and amount of land subsidence.

Monitoring ground deformation of cultural heritage sites using SAR and geodetic techniques: the case study of Choirokoitia, Cyprus

Nowadays, assessing geo-hazards in cultural heritage sites in most cases takes place after the hazard has occurred. Monitoring structural and ground deformation resulting from geo-hazards facilitates the early recognition of potential risks and encourages effective conservation planning. This paper presents an integrated ground deformation monitoring approach based on the combined use of satellite SAR data, campaign-based GPS/GNSS observations, and aerial images from UAVs within the Choirokoitia UNESCO World Heritage Site in Cyprus. The Neolithic settlement of Choirokoitia is one of the most important prehistoric sites in the Eastern Mediterranean. The site is located on a steep hill, which makes it vulnerable to rock falls and landslides. As part of the PROTHEGO project, a series of field measurements were collected at the Choirokoitia site and compared against satellite SAR data to verify kinematic behavior of the broader area and to assist in monitoring potential geo-hazards over time. The results obtained indicate displacement rates of the order of 0.03 m/year. These results indicate that ground deformation should be monitored in the area surrounding the Choirokoitia using long-term, low-impact monitoring systems such as SAR images and UAV-based and geodetic techniques. The combination of such monitoring technologies can be compared to monitor and assess potential geo-hazards on archeological sites with increased accuracy.

Assessment of the Sentinel-1 based ground motion data feasibility for large scale landslide monitoring

In this paper, a systematic procedure to assess the feasibility of Advanced Differential Interferometric SAR (A-DInSAR) technique for landslide monitoring using SAR images acquired by Sentinel-1 sensors is presented. The methodology is named “Assessment of the advanced differentiaL interferometric synthetic aperture radar technique Feasibility for large scale lAndslide monitoring – ALFA” and it is structured in two main phases, which includes pre-processing and post-processing elaborations. The methodology was developed and tested in the Alpine sector of the Piedmont region in Italy, which represents a landslide prone area. In particular, ALFA represents a methodology based on previous algorithms available in the literature to assess the a-prior feasibility assessment and post-processing analysis of A-DInSAR data for landslide, which introduces three novel aspects such as (1) a systematic scheme suitable within regional practices; (2) the use of Sentinel-1 data and the development of (3) an index to take into account of the kind of distribution of the measuring points along the landslide. The approach was applied over an area extended about 5300 km2 affected by 5703 landslides mapped in the database of the Piedmont Region (Landslides information system in Piedmont—SIFRAP). Sentinel-1 images covering the period 2014–2018 were analysed. The results show the potential of the Sentinel-1 data for large-scale landslide monitoring. The developed methodology presents reliable tools that could be useful as feasibility for the use of Sentinel-1 data for landslide monitoring at regional and national scale.

History of the William G. Syrotuck Symposium on Search Theory and Practice

The Syrotuck Symposium began in 1996 to: “Foster the intellectual and scientific development of SAR methods and techniques, to promote new ideas, and to encourage development of new techniques and the practical use of technology.”

High Rates of Inflation During a Noneruptive Episode of Seismic Unrest at Semisopochnoi Volcano, Alaska in 2014–2015

AbstractMagma intrusion rate is a key parameter in eruption triggering but is poorly quantified in existing geodetic studies. Here we examine two episodes of rapid inflation in this context. Two noneruptive microseismic swarms were recorded at Semisopochnoi Volcano, Alaska in 2014–2015. We use differential SAR techniques and TerraSAR‐X images to document surface deformation from 2011 to 2015, which comprises island‐wide radial inflation totaling ~25 cm (+/−1 cm) line of sight displacement in 2014–2015. Multiple source geometries are tested in an inversion of the deformation data, and InSAR data are best fit by a spheroid trending to the northeast and plunging to the southeast, with a major axis of ~4 km and minor axes of ~1 km, directly under the central caldera of Semisopochnoi. In 2014, a modeled influx of 0.043 km3 of magma caused line of sight displacement of ~17 cm. This magma was stored at a depth of ~8 km, until 2015 when 0.029 km3 was added. Along with the definition of inflation source parameters, the recorded seismic events are relocated using differential travel times. These relocated events outline a linear aseismic area within a larger zone of shallow (<10 km) seismicity. This aseismic region aligns with the centroid of the deformation model. Based on these geodetic and seismic models, the plumbing system at Semisopochnoi is interpreted as a spheroidal magma storage zone at a depth of ˜8 km below a linear feature of partial melt. The observed deformation and seismicity appear to result from rapid injection into this main storage region.

AN APPLICATION OF SEGNET FOR DETECTING LANDSLIDE AREAS BY USING FULLY POLARIMETRIC SAR DATA

The study location of landslide is in Hokkaido, Japan which occurred due to the Iburi Earthquake 2018. In this study the landslide has been estimated by the fully Polarimetric SAR (Pol-SAR) technique based on ALOS-2 PALSAR-2 data using the Yamaguchi’s decomposition. The Yamaguchi's decomposition is proposed by Yoshio Yamaguchi et.al. The data has been analyzed using the deep learning process with SegNet architecture with color composite. In this research, the performance of SegNet is fast and efficient in memory usage. However, the result is not good, based on the Intersection over Union (IoU) evaluation obtained the lowest value is 0.0515 and the highest value is 0.1483. That is because of difficulty to make training datasets and of a small number of datasets. The greater difference between accuracy and loss graph along with higher epochs represents overfitting. The overfitting can be caused by the limited amount of training data and failure of the network to generalize the feature set over the training images.

Estimation of Co-Seismic Land Deformation Due to Mw 7.3 2017 Earthquake in Iran (12 Nov 2017) using Sentinel-1 DInSAR

A strong shaking with Mw 7.3 occurred on 12th November 2017 around the Sarpol-e Zahab town in the border area between Iran and Iraq. It has a number of foreshocks and aftershocks increasing the total deformation, cumulatively. In this study, we have investigated how earth surface deformed after such a strong earthquake and its scatters. Because, the deformation inspection are indispensable for the safety of citizens and infrastructures. The best way for monitoring of surface deformation in such a big event is the SAR technique. This system can work effectively during night and day under different weather conditions. The Interferometric SAR (InSAR) allows accurate measurements of surface deformation in mm resolution. There are several methods for the application of SAR techniques and one of them is Differential InSAR (DInSAR) indicating an uplift and subsidence around epicentral area precisely. We preferred to use it for sensitive vertical displacement in the target area. The seismological data from the observatory centers indicate that the recent earthquake sourced from the NW-SE trending, northeast dipping High Zagros Reverse Fault Zone. According to the results, epicentral area has been exposed a vertical displacement with 90 cm uplift and -41 cm subsidence in the northeastern and southwestern block of the fault, respectively.

Development of a hybrid classification technique based on deep learning applied to MSG / SEVIRI multispectral data

The approach developed in this paper for the classification of precipitation intensities is based on deep learning of neural network. Multispectral data from the MSG satellite (Meteosat Second Generation) providing information about the cloud's physical and optical characteristics are exploited and used as inputs to a deep neural network model. The model is a combination of CNN (Convolutional Neural Network) and DMLP (Deep Multi-Layer Peceptron) which is learned and validated by comparison with the corresponding Radar data during the rainy seasons 2006/2007 and 2010/2011 respectively. The CNN extracts spatial characteristics from MSG multi-spectral images. Then, the set of spatial and multi-spectral information are used as inputs for the DMLP. The results show an improvement compared to the three other classifiers (Random Forest, Support Vector Machine and Artificial Neural Network). The CNN-DMLP method was also compared to the technique combining the three classifiers (SAR). The results indicate a percentage correct (PC) of 97% and a probability of detection (POD) of 90% for CNN-DMLP method compared to 94% and 87% for of the SAR technique, respectively. In terms of bias, the CNN-DMLP method gives 1.08 compared 1.10 for SAR technique.

VARIASI TEKNIK SYNTHETIC APERTURE RADAR (SAR) UNTUK REKONSTRUKSI GEOLOGI KABUPATEN PIDIE JAYA PROVINSI ACEH

Geology information has an important role in development planning in Indonesia especially in physical development so that it needs to be well laid out in order to give the complete information. The objectives of the study are: First, integrating result of the SAR technique processing to image fusion technique to identify geological structure, landform and litology in Pidie Jaya region, Aceh province and Second, testing ability of SAR technique and image fusion technique in geology reconstruction in Pidie Jaya region. This study was done in most parts of Pidie Jaya and Pidie region using the main data that were Sentine-1A with VH polarization and Landsat 8 OLI with 567 composite. The methods used are digital image processing and field observation. Digital image processing uses some techniques including: SAR technique (calibration, multilook, deburst, median speckle filtering, geometric correction), InSAR tecnique to create DEM, HSV image fusion and directional spatial filter techniques (3x3 and 5x5 windows) to identify landform, geological structure and litology through visual interpretation. Field observation was done through strike and dip measuring with purposive sampling method. Results of HSV fusion technique visual interpretation can identify structural landform, volcanic landorm, fluvial landform, drainage patterns and litology. Results of directional filter visual interpretation can identify lineament, fault and fold. Geological structure in study region has dominant direction South West – North East or 42.4 o – 223.63 o . The study region is dominated by structural landform with an area of 555.39 km 2 or 59.56 % of study area total with accuration 86.04 %. Litology which dominates in study area is sandstone with an area of 571.78 km 2 or 61.31 % of study area total with accuration 82.93 %.

Implementation and configuration of GB-SAR for landslide monitoring: case study in Minami-Aso, Kumamoto

ABSTRACTIn this paper, the applicability of ground-based synthetic aperture radar (GB-SAR) as an early warning system for landslide monitoring is discussed. The effectiveness of the differential interferometric SAR (DInSAR) technique used in GB-SAR depends strongly on the geography of the monitored location. Therefore, an assessment of the system compatibility to select the most appropriate remote monitoring method is essential prior to any hardware implementation. In the preliminary part of this study, a 3D model was created using a LiDAR survey, and proposed locations for GB-SAR installation were examined. A 3D simulation was carried out to estimate the illumination from each of the proposed GB-SAR locations. The proposed model increased the efficiency of the GB-SAR positioning by minimising installation cost and time. Hardware configuration parameters, such as platform height, maximum range, and the direction and view angle of the radar line of sight were estimated by considering the optimum reflected power and ground illumination. Unlike on flat terrain, deployment of GB-SAR in a mountainous area is challenging because of surface anomalies and continuous changes in meteorological parameters, such as atmospheric temperature, pressure and relative humidity. In this study, the experimental site was located 3 km from the Aso volcano, and the weather conditions in the Aso caldera became a critical factor in accurately estimating the interferometric phase. The presence of atmospheric artefacts also compromises the applicability of the classical DInSAR technique. Here, we minimised the atmospheric phase screen by estimating the optimum data acquisition interval from GB-SAR monitoring under extreme weather conditions. The developed methodologies were then used to design a new landslide early warning system that measures real-time displacement over an area of 1 km2 within 10 s of scanning. This fully automatic monitoring system updates every 15 min and presents displacement information in a 3D interface. The system we have developed has been deployed for continuous monitoring of the mountainous environment of a road reconstruction site in Minami-Aso, Kumamoto, Japan where a large-scale landslide was triggered following the Kumamoto earthquake in 2016.

Detection of Peat Fire Risk Area Based on Impedance Model and DInSAR Approaches Using ALOS-2 PALSAR-2 Data

Forest fire in Indonesia occurs mostly in peatland area. Dry peatland areas with groundwater table (GWT) more than 40 cm from the soil surface have become degradation areas with high potentials to fire. This paper presents a new novel to detect a peat fire risk area by incorporating two methods: the impedance model and the differential interferometric SAR (DInSAR) technique which is based on the knowledge of annual subsidence rate associated with the GWT. The previous impedance model is modified in this paper by integrating the surface roughness information in the model as a part of novelty. The proposed method was then validated with ground truth data of GWT. By using an impedance model, this paper successfully detected peat fire risk area based on the backscattering coefficient simulation of dry peatland. Based on the simulation model, the average, minimum, and maximum of backscattering coefficient of dry peat are -13.97, -11.5, and -17.29 dB, respectively. The correlation coefficient between the simulated backscattering coefficient and backscattering from ALOS-2/PALSAR-2 data is 0.8 with root mean square error of 1.4. By using the DInSAR method, detection of dry peatland area was successful. The significant relationships confirmed between GWT measurement and model are 0.71 for Pair A and 0.85 for Pair B. Both methods showed that peat fire risk areas were identified successfully. The dielectric constant of the peat soil also revealed that the soil condition of the area of interest is very dry indicating the potential to peat fire risk. Employing two models, respectively, were recommended to get precision of detection analysis.