• Korean Journal of Remote Sensing
• /
• v.25 no.3
• /
• pp.243-253
• /
• 2009

For the last 14 years, space-borne satellite SAR system such as RADARSAT-1, ERS-2, and ENVISAT ASAR have provided a continuous observation over the ocean. However, the data acquired from those systems were limited to C-band frequency until the advent of the first spacebome German X-band SAR system TerraSAR-X in 2007. Korea is also planning to launch the nation's first X-band SAR satellite (KOMPSAT-5) in 2010. It is timely and necessary to develop X-band models for estimating geophysical parameters from these X-band SAR systems. In this study, X-band wind retrieval model was investigated and developed based on numerical ocean scattering model (radar backscattering model and hydrodynamic interaction model). Although these models have not yet been tested and validated for broad ranges of wind conditions, the estimated wind speeds from TerraSAR-X data show generally good agreement with in-situ measurements.

• Korean Journal of Remote Sensing
• /
• v.38 no.5_3
• /
• pp.901-912
• /
• 2022

The frequency of disasters is increasing due to global climate change, and unusual heavy rains and rainy seasons are occurring in Korea. Periodic monitoring and rapid detection are important because these weather conditions can lead to drought and flooding, causing secondary damage. Although research using optical images is continuously being conducted to determine the waterbody, there is a limitation in that it is difficult to detect due to the influence of clouds in order to detect floods that accompany heavy rain. Therefore, there is a need for research using synthetic aperture radar (SAR) that can be observed regardless of day or night in all weather. In this study, using Sentinel-1 SAR images that can be collected in near-real time as open data, the UNet model among deep learning algorithms that have recently been used in various fields was applied. In previous studies, waterbody detection studies using SAR images and deep learning algorithms are being conducted, but only a small number of studies have been conducted in Korea. In this study, to determine the applicability of deep learning of SAR images, UNet and the existing algorithm thresholding method were compared, and five indices and Sentinel-2 normalized difference water index (NDWI) were evaluated. As a result of evaluating the accuracy with intersect of union (IoU), it was confirmed that UNet has high accuracy with 0.894 for UNet and 0.699 for threshold method. Through this study, the applicability of deep learning-based SAR images was confirmed, and if high-resolution SAR images and deep learning algorithms are applied, it is expected that periodic and accurate waterbody change detection will be possible in Korea.

• Korean Journal of Remote Sensing
• /
• v.23 no.4
• /
• pp.257-272
• /
• 2007

This paper analyzed relationships between various features from SAR data with multiple acquisition dates and mode (frequency, polarization and incidence angles), and land-cover classes. Two typical types of features were extracted by considering acquisition conditions of currently available SAR data. First, coherence, temporal variability and principal component transform-based features were extracted from multi-temporal and single mode SAR data. C-band ERS-1/2, ENVISAT ASAR and Radarsat-1, and L-band JERS-1 SAR data were used for those features and different characteristics of different SAR sensor data were discussed in terms of land-cover discrimination capability. Overall, tandem coherence showed the best discrimination capability among various features. Long-term coherence from C-band SAR data provided a useful information on the discrimination of urban areas from other classes. Paddy fields showed the highest temporal variability values in all SAR sensor data. Features from principal component transform contained particular information relevant to specific land-cover class. As features for multiple mode SAR data acquired at similar dates, polarization ratio and multi-channel variability were also considered. VH/VV polarization ratio was a useful feature for the discrimination of forest and dry fields in which the distributions of coherence and temporal variability were significantly overlapped. It would be expected that the case study results could be useful information on improvement of classification accuracy in land-cover classification with SAR data, provided that the main findings of this paper would be confirmed by extensive case studies based on multi-temporal SAR data with various modes and ground-based SAR experiments.

• Proceedings of the KSRS Conference
• /
• 2007.10a
• /
• pp.258-261
• /
• 2007

Although there have been lack of studies using X-band SAR data particularly for forestry application as compared to C-, and L-band SAR data, it has a potential to distinguish tree species because most signals are backscattered on the top of canopy. This study aimed to compare signal characteristics of multi-band SAR data including X-band for classifying tree species. The data used for the study are SIR-C/X-SAR data (X-, C-, L-band) obtained on Oct. 3, 1994 over the forest area near Seoul, S. Korea. Thirty ground sample plots were collected per each tree species. Initial comparison of backscattering coefficients among three SAR bands shows that X-band data showed better separation of tree species than C- and L-band SAR data irrespective of polarization. The weak penetrating in canopy layer might be possible source of information for X-band data to be useful for the classification of forest species and cover type mapping.

• Korean Journal of Remote Sensing
• /
• v.14 no.1
• /
• pp.69-82
• /
• 1998

SAR imagery can overcome the limitations of electro-optical sensor imagery and provide us Information which plays a supplementary role. But it is necessary to remove a variety of geometric errors in SAR imagery. An accurate geometric correction of SAR imagery is not easy task to achieve, though some techniques and theories are introduced. We also have difficulties such as transformation problem between 'International' ellipsoid in Radarsat system and 'Bessel' ellipsoid. Two widely used correction method, one is made by simulated image, and the other by collinearity equation, usually use DEM. In this study, the merits and demerits of geocoding methods respectively and the effective method for Korean terrain were found.

• Korean Journal of Remote Sensing
• /
• v.27 no.5
• /
• pp.555-563
• /
• 2011

Nowadays, demands with respect to applications based on geo-based information on mobile device such as smartphone and those based on open platform or open source have been increasing. This trend can be regarded as significant opportunities to widen application fields and to expand industry business cases using satellite imagery. However, it needs a different approach from conventional remote sensing researches. This work focuses on SAR among many kinds of geo-based data resources. First, an application for Interferometric SAR processing based on open source was implemented. And using this, InSAR data was processed and stored into database. When smartphone users at any places request InSAR results, they can receive InSAR information and concerned metadata on their device. An smartphone application for this task was designed and implemented in this study. This provides a practical way for SAR service for smartphone, and can apply to build mobile service system of complex and compound types of remote sensing resources and their derived contents.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.32 no.1D
• /
• pp.89-94
• /
• 2012

The RFM (Rational Function Model), as an alternative to physical sensor models has been widely used for photogrammetric processing of high resolution optical satellite imagery. However, the application of RF modeling to the SAR (Synthetic Aperture Radar) is very limited. In this paper, stereo radargrammetric processing of TerraSAR-X stereo pairs with RFM is implemented and analyzed. The investigation has shown that the accuracy of TerraSAR-X DSM is similar to that of the commercial S/W product. Finally, it is demonstrated that RFM is effective and feasible in the application to the radargrammetric SAR image processing.

• Proceedings of the KSRS Conference
• /
• 2008.10a
• /
• pp.422-425
• /
• 2008

TerraSAR-X is new radar satellite operated at X-band, multi polarization, and multi beam mode. Compared with C-band or L-band SAR, the X-band system inherently suffers from more temporal decorrelation, but is more sensitive to surface deformation monitoring due to short wavelength (3.1 cm) and high spatial resolution (1m-3m). It is generally expected that sensitivity to estimate surface movement using TerraSAR-X will be increased by the factor of 10, compared to current C-band system with low spatial resolution such as ERS-2, Envisat. Many urban areas are experiencing land subsidence due to water, oil and natural gas withdrawal, underground excavation, sediment compaction, and so on. Monitoring of surface deformation is valuable for effectively limiting damage areas. In addition high accuracy and spatially dense subsidence map can be achieved by X-band InSAR observation, promoting identification and separation of various subsidence processes and leading to enhanced understanding via mechanical modeling. In this study we will introduce some initial InSAR results using new TerraSAR-X SAR data for surface deformation monitoring.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.12
• /
• pp.46-54
• /
• 2015

SAR is a Radar to obtain the video information using a radio wave. Platform emit the radio wave, depending backscattered waves returned from the target object the signal to the distance, to create a topographical map is recorded in two-dimensional image. In this paper, through a simulation to apply a variety of window in the SAR image processing for SAR image recovery is to study the application effect of the window, as a result, at the side of the signal of the SNR, Flattop window to improve the best performance it was confirmed to show.

• Journal of electromagnetic engineering and science
• /
• v.6 no.1
• /
• pp.47-52
• /
• 2006

The objective of this study is to evaluate the effects of size and permittivity on the specific absorption rate(SAR) values of rat brains during microwave exposure at mobile phone frequency bands. A finite difference time domain (FDTD) technique with perfect matching layer(PML) absorbing boundaries is used for this evaluation process. A color coded digital image of the Sprague Dawley(SD) rat based on magnetic resonance imaging(MRI) is used in FDTD calculation with appropriate permittivity values corresponding to different tissues for 3, 4, 7, and 10 week old rats. This study is comprised of three major parts. First, the rat model structure is scaled uniformly, i.e., the rat size is increased without change in permittivity. The simulated SAR values are compared with other experimental and numerical results. Second, the effect of permittivity on SAR values is examined by simulating the microwave exposure on rat brains with various permittivity values for a fixed rat size. Finally, the SAR distributions in depth, and the brain-averaged SAR and brain 1 voxel peak SAR values are computed during the microwave exposure on a rat model structure when both size and permittivity have varied corresponding to different ages ranging from 3 to 10 weeks. At 900 MHz, the simulation results show that the brain-averaged SAR values decreased by about 54 % for size variation from the 3 week to the 10 week-old rat model, while the SAR values decreased only by about 16 % for permittivity variation. It is found that the brain averaged SAR values decreased by about 63 % when the variations in size and permittivity are taken together. At 1,800 MHz, the brain-averaged SAR value is decreased by 200 % for size variation, 9.7 % for permittivity variation, and 207 % for both size and permittivity variations.