• Journal of Korea Water Resources Association
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• v.53 no.12
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• pp.1159-1172
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• 2020

This study applied deep convolution neural network based on U-Net and SegNet using long period weather radar data to very short-term rainfall prediction. And the results were compared and evaluated with the translation model. For training and validation of deep neural network, Mt. Gwanak and Mt. Gwangdeoksan radar data were collected from 2010 to 2016 and converted to a gray-scale image file in an HDF5 format with a 1km spatial resolution. The deep neural network model was trained to predict precipitation after 10 minutes by using the four consecutive radar image data, and the recursive method of repeating forecasts was applied to carry out lead time 60 minutes with the pretrained deep neural network model. To evaluate the performance of deep neural network prediction model, 24 rain cases in 2017 were forecast for rainfall up to 60 minutes in advance. As a result of evaluating the predicted performance by calculating the mean absolute error (MAE) and critical success index (CSI) at the threshold of 0.1, 1, and 5 mm/hr, the deep neural network model showed better performance in the case of rainfall threshold of 0.1, 1 mm/hr in terms of MAE, and showed better performance than the translation model for lead time 50 minutes in terms of CSI. In particular, although the deep neural network prediction model performed generally better than the translation model for weak rainfall of 5 mm/hr or less, the deep neural network prediction model had limitations in predicting distinct precipitation characteristics of high intensity as a result of the evaluation of threshold of 5 mm/hr. The longer lead time, the spatial smoothness increase with lead time thereby reducing the accuracy of rainfall prediction The translation model turned out to be superior in predicting the exceedance of higher intensity thresholds (> 5 mm/hr) because it preserves distinct precipitation characteristics, but the rainfall position tends to shift incorrectly. This study are expected to be helpful for the improvement of radar rainfall prediction model using deep neural networks in the future. In addition, the massive weather radar data established in this study will be provided through open repositories for future use in subsequent studies.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.5
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• pp.343-353
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• 2018

Ocean tides in Antarctica are not well constrained mostly due to the lack of tidal observations. Especially, tides underneath and around ice shelves are uncertain. InSAR (Interferometric Synthetic Aperture Radar) data has been used to observe ice shelf movements primarily caused by ocean tides. Here, we demonstrate that it is possible to estimate tidal constituents underneath the Sulzberger ice shelf, West Antarctica, solely using ERS-1/2 tandem mission DInSAR (differential InSAR) observations. In addition, the tidal constituents can be estimated in a high-resolution (~200 m) grid which is beyond any tidal model resolution. We assume that InSAR observed ocean tidal heights can be derived after correcting the InSAR data for the effect of atmospheric loading using the inverse barometric effect, solid earth tides, and ocean tide loading. The ERS (European Remote Sensing) tandem orbit configuration of a 1-day separation between SAR data takes diminishes the sensitivity to major tidal constituents including $K_1$ and $S_2$. Here, the dominant tidal constituent $O_1$ is estimated using 8 differential interferograms underneath the Sulzberger ice shelf. The resulting tidal constituent is compared with a contemporary regional tide model (CATS2008a) and a global tide model (TPXO7.1). The InSAR estimated tidal amplitude agrees well with both models with RMS (root-mean-square) differences of < 2.2 cm and the phase estimate corroborating both tide models to within $8^{\circ}$. We conclude that fine spatial scale (~200 m) Antarctic ice shelf ocean tide determination is feasible for dominant constituents using C-band ERS-1/2 tandem mission InSAR.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.320-323
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• 2008

This study attempts to establish a system extracting and monitoring cultural grounds of seaweeds (lavers, brown seaweeds and seaweed fulvescens) and abalone on the basis of both KOMPSAT-2 and Terrasar-X data. The study areas are located in the northwest and southwest coast of South Korea, famous for coastal cultural grounds. The northwest site is in a high tidal range area (on the average, 6.1 min Asan Bay) and has laver cultural grounds for the most. An semi-automatic detection system of laver facilities is described and assessed for spacebome optic images. On the other hand, the southwest cost is most famous for seaweeds. Aquaculture facilities, which cover extensive portions of this area, can be subdivided into three major groups: brown seaweeds, capsosiphon fulvescens and abalone farms. The study is based on interpretation of optic and SAR satellite data and a detailed image analysis procedure is described here. On May 25 and June 2, 2008 the TerraSAR-X radar satellite took some images of the area. SAR data are unique for mapping those farms. In case of abalone farms, the backscatters from surrounding dykes allows for recognition and separation of abalone ponds from all other water-covered surfaces. But identification of seaweeds such as laver, brown seaweeds and seaweed fulvescens depends on the dampening effect due to the presence of the facilities and is a complex task because objects that resemble seaweeds frequently occur, particularly in low wind or tidal conditions. Lastly, fusion of SAR and optic spatial images is tested to enhance the detection of aquaculture facilities by using the panchromatic image with spatial resolution 1 meter and the corresponding multi-spectral, with spatial resolution 4 meters and 4 spectrum bands, from KOMPSAT-2. The mapping accuracy achieved for farms will be estimated and discussed after field verification of preliminary results.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.18 no.8
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• pp.984-996
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• 2007

This paper presents techniques of 2-D scattering center extraction and 2-B ISAR(Inverse SAR) image formation for scattering wave which is scattered by a target. In general, 2-D IFFT is widely used to obtain 2-D scattering center and ISAR image of targets. But, this method has drawbacks, that is poor in a resolution aspect. To overcome these shortcomings with the FT(Fourier Transform)-based method, various techniques of high resolution signal processing were developed. In this paper, algorithms of 2-D scattering center extraction and ISAR image formation such as 2-D MEMP(Matrix Enhancement and Matrix Pencil), 2-D ESPRIT(Estimation of Signal Parameter via Rotational Invariance Techniques) are described. In order to show the performances of each algorithm, we use scattering wave of the ideal point scatterers and F-18 aircraft to estimate 2-D scattering center and abtain 2-D ISAR image.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2009.10a
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• pp.73-74
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• 2009

This study attempts to establish a system extracting and monitoring cultural grounds of seaweeds (lavers, brown seaweeds and seaweed fulvescens) and abalone on the basis of both KOMPSAT-2 and Terrasar-X data. The study areas are located in the northwest and southwest coast of South Korea, famous for coastal cultural grounds. The northwest site is in a high tidal range area (on the average, 6.1 m in Asan Bay) and has laver cultural grounds for the most. An semi-automatic detection system of laver facilities is described and assessed for spaceborne optic images. On the other hand, the southwest cost is most famous for seaweeds. Aquaculture facilities, which cover extensive portions of this area, can be subdivided into three major groups: brown seaweeds, capsosiphon fulvescens and abalone farms. The study is based on interpretation of optic and SAR satellite data and a detailed image analysis procedure is described here. On May 25 and June 2, 2008 the TerraSAR-X radar satellite took some images of the area. SAR data are unique for mapping those farms. In case of abalone farms, the backscatters from surrounding dykes allows for recognition and separation of abalone ponds from all other water-covered surfaces. But identification of seaweeds such as laver, brown seaweeds and seaweed fulvescens depends on the dampening effect due to the presence of the facilities and is a complex task because objects that resemble seaweeds frequently occur, particularly in low wind or tidal conditions. Lastly, fusion of SAR and optic spatial images is tested to enhance the detection of aquaculture facilities by using the panchromatic image with spatial resolution 1 meter and the corresponding multi-spectral, with spatial resolution 4 meters and 4 spectrum bands, from KOMPSAT-2. The mapping accuracy achieved for farms will be estimated and discussed after field verification of preliminary results.

• Korean Journal of Remote Sensing
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• v.24 no.4
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• pp.299-307
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• 2008

It is possible to extract qualified ground control points (GCPs) from SAR data itself without published maps. TerraSAR-X data that are one of highest spatial resolution among civilian SAR systems is now available. In this study, a sophisticated method for GCP extraction from TerraSAR-X data was tested and the quality of the extracted GCPs was evaluated. Mean values of the distance errors were 0.11m and -3.96 m with standard deviations of 6.52 m and 5.11 m in easting and northing, respectively. The result is one of the best among GCPs possibly extracted from any civilian remote sensing systems. The extracted GCPs were used for geo-rectification of IKONOS image. The method used in this study can be applied to KOMPSAT-5 for geo-rectification of high-resolution optic images acquired by KOMPSAT-2 or follow-up missions.

• Journal of Environmental Science International
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• v.18 no.8
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• pp.847-855
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• 2009

As a part of effort to establish an offshore wind resource assessment system of the Korean Peninsula, a numeric wind simulation using mesoscale climate model MM5 and a spatial distribution of offshore wind extracted from SAR remote-sensing satellite image is compared and analyzed. According to the analyzed results, the numeric wind simulation is found to have wind speed over predication tendency at the coastal sea area. Therefore, it is determined that a high-resolution wind simulation is required for complicated coastal landforms. The two methods are verified as useful ways to identify the spatial distribution of offshore wind by mutual complementation and if the meteor-statistical comparative analysis is performed in the future using adequate number of satellite images, it is expected to derive a general methodology enabling systematic validation and correction of the numeric wind simulation.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.3
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• pp.239-245
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• 2016

Deramping technique has been widely used to acquire high resolution SAR(Synthetic Aperture Radar) images for the advantage of the data size and the processing time. However, unwanted spurious signals caused by SAR hardware can be leaked in the process of converting into a digital signal through the ADC(Analog-Digital Converter) and added in a echo signal. These tones make image quality degrade significantly. In order to solve this problem, the unwanted tones need to be detected by analysing the characteristic of the noise tone and then effectively removed from raw data. In this paper, we propose a method for efficiently removing noise tone on the raw data based on the characteristic of spurious signals.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.1D
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• pp.89-94
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• 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
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• 1999.11a
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• pp.474-478
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• 1999

SAR interferometry (InSAR) using the space-borne Synthetic Aperture Radar (SAR) have recently become one of the most effective tools monitoring surface changes caused by landslides, earthquakes, subsidences or volcanic eruption. This study focuses on examining the feasibility of InSAR using the RADARSAT data. Although the RABARSAT SAR with its high resolution and variable incidence angle has several advantages for repeat-pass InSAR, it has two key limitations: first, the orbit is not precisely known; and second, RADARSAT's 24-day repeat pass interval is not very favourable for retaining useful coherence. In this study, two pairs of RADARSAT data in the Nahanni area, NWT, Canada have been tested. We will discuss about the special consideration required on the interferometric processing steps specifically for RADARSAT data including image co-registration, spectral filtering in both azimuth and range, estimation of the interferometric baseline, and correction of the interferogram with respect to the "flat earth" phase contribution. Preliminary results can be summarized as: i) the properly designed azimuth filter based upon the antenna characteristic improves coherence considerably if difference in Doppler centroid of the two images is relatively large; ii) the co-registration process combined by fringe spectrum and amplitude cross-correlation techniques results in optimal matching; iii) the baseline is not always possible to be estimated from the definitive orbit information.