• Korean Journal of Remote Sensing
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• v.39 no.1
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• pp.65-76
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• 2023

The Gamma Portable Radar Interferometer (GPRI) is a ground-based real aperture radar (RAR) that can acquire images with high spatial and temporal resolution. The GPRI ground-based radar used in this study composes three antennas with a Ku-band frequency of 17.1-17.3 GHz (1.73-1.75 cm of wavelength). It can measure displacement over time with millimeter-scale precision. It is also possible to adjust the observation mode by arranging the transmitting and receiving antennas for various applications: i) obtaining differential interferograms through the application of interferometric techniques, ii) generation of digital elevation models and iii) acquisition of full polarimetric data. We introduced the hardware configuration of the GPRI ground-based radar, image acquisition, and characteristics of the collected radar images. The interferometric phase difference has been evaluated to apply the multi-temporal interferometric SAR application (MT-InSAR) using the first observation campaigns at Pusan National University in Geumjeong-gu, Busan.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.6
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• pp.547-555
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• 2015

The vegetation index is a crucial parameter in many biophysical studies of vegetation, and is also a valuable content in ecological processes researching. The OVIs (Optical Vegetation Index) that of using multispectral and hyperspectral data have been widely investigated in the literature, while the RVI (Radar Vegetation Index) that of considering volume scattering measurement has been paid relatively little attention. Also, there was only some efforts have been put to fuse the OVI with the RVI as an integrated vegetation index. To address this issue, this paper presents a novel FVI (Fusion Vegetation Index) that uses multispectral and full-PolSAR (Polarimetric Synthetic Aperture Radar) data. By fusing a NDVI (Normalized Difference Vegetation Index) of RapidEye and an RVI of C-band Radarsat-2, we demonstrated that the proposed FVI has higher separability in different vegetation types than only with OVI and RVI. Also, the experimental results show that the proposed index not only has information on the vegetation greenness of the NDVI, but also has information on the canopy structure of the RVI. Based on this preliminary result, since the vegetation monitoring is more detailed, it could be possible in various application fields; this synergistic FVI will be further developed in the future.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.283-285
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• 2005

To account for the importance of variable in multi-sensor data fusion, random forests are applied to supervised land-cover classification. The random forests approach is a non-parametric ensemble classifier based on CART-like trees. Its distinguished feature is that the importance of variable can be estimated by randomly permuting the variable of interest in all the out-of-bag samples for each classifier. Supervised classification with a multi-sensor remote sensing data set including optical and polarimetric SAR data was carried out to illustrate the applicability of random forests. From the experimental result, the random forests approach could extract important variables or bands for land-cover discrimination and showed good performance, as compared with other non-parametric data fusion algorithms.

• Korean Journal of Remote Sensing
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• v.22 no.3
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• pp.211-219
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• 2006

A random forests classifier is applied to multi-sensor data fusion for supervised land-cover classification in order to account for the importance of variable. The random forests approach is a non-parametric ensemble classifier based on CART-like trees. The distinguished feature is that the importance of variable can be estimated by randomly permuting the variable of interest in all the out-of-bag samples for each classifier. Two different multi-sensor data sets for supervised classification were used to illustrate the applicability of random forests: one with optical and polarimetric SAR data and the other with multi-temporal Radarsat-l and ENVISAT ASAR data sets. From the experimental results, the random forests approach could extract important variables or bands for land-cover discrimination and showed reasonably good performance in terms of classification accuracy.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.582-585
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• 2004

Oyster fanning structures in tidal flats are well detected by SAR system. Each frame of these artificial structures is composed of two vertical and one horizontal wooden pole. We investigate characteristics of polarimetric features in the target structures. In this paper, the results of AIRSAR L-band POLSAR data and experiments in laboratory are discussed. The ratio of single bounce to double bounce scattering depends of vertical pole height, direction of horizontal pole to radar look direction, and incidence angle as well as sea surface condition. We have conducted laboratory experiments. According to target scale, Ku-band and targets downsized by scale of 10 are used. The results of the experiments are summarized as: i) total power of the backscattering is more affected by vertical poles than a horizontal pole; ii) and backscattering from a horizontal pole is sensitive to the relative radar look direction to target array. We conclude that water level can be effectively measured by using interferometric phase and backscattering intensity if vertical poles in the water are observed by L-band HH- or VV-polarization. Measurement of tide height can be further improved if double bounced components are separated from fully polarized SAR data.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.262-265
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• 2007

Preliminary results are reported on ship detection using coherence images computed from cross-correlating images of multi-look-processed dual-polarization data (HH and HV) of ENVISAT ASAR. The traditional techniques of ship detection by radars such as CFAR (Constant False Alarm Rate) rely on the amplitude data, and therefore the detection tends to become difficult when the amplitudes of ships images are at similar level as the mean amplitude of surrounding sea clutter. The proposed method utilizes the property that the multi-look images of ships are correlated with each other. Because the inter-look images of sea surface are covered by uncorrelated speckle, cross-correlation of multi-look images yields the different degrees of coherence between the images and water. The polarimetric information of ships, land and intertidal zone are first compared based on the cross-correlation between HH and HV. In the next step, we examine the technique when the dual-polarization data are split into two multi-look Images.

• Proceedings of the KSRS Conference
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• 2008.03a
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• pp.180-184
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• 2008

Preliminary results are reported on ship detection using coherence images computed from crosscorrelating images of multi-look-processed dual-polarization data (HH and HV) of ENVISAT ASAR. The traditional techniques of ship detection by radars such as CFAR (Constant False Alarm Rate) rely on the amplitude data, and therefore the detection tends to become difficult when the amplitudes of ships images are at similar level as the mean amplitude of surrounding sea clutter. The proposed method utilizes the property that the multi-look images of ships are correlated with each other. Because the inter-look images of sea surface are covered by uncorrelated speckle, crosscorrelation of multi-look images yields the different degrees of coherence between the images and water. The polarimetric information of ships, land and intertidal zone are first compared based on the cross-correlation between HH and HV. In the next step, we examine the technique when the dual-polarization data are split into two multi-look images.

• Korean Journal of Remote Sensing
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• v.25 no.4
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• pp.383-389
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• 2009

The main objective of the research is a feasibility study on the intertidal zone using a X-band radar satellite, TerraSAR-X. The TerraSAR-X data have been acquired in the west coast of Korea where large tidal flats, Ganghwa and Yeongjong tidal flats, are developed. Investigations include: 1) waterline and backscattering characteristics of the high resolution X-band images in tidal flats; 2) polarimetric signature of halophytes (or salt marsh plants), specifically Suaeda japonica; and 3) phase and coherence of interferometric pairs. Waterlines from TerraSAR-X data satisfy the requirement of horizontal accuracy of 60 m that corresponds to 20 cm in average height difference while current other spaceborne SAR systems could not meet the requirement. HH-polarization was the best for extraction of waterline, and its geometric position is reliable due to the short wavelength and accurate orbit control of the TerraSAR-X. A halophyte or salt marsh plant, Suaeda japonica, is an indicator of local sea level change. From X-band ground radar measurements, a dual polarization of VV/VH-pol. is anticipated to be the best for detection of the plant with about 9 dB difference at 35 degree incidence angle. However, TerraSAR-X HH/TV dual polarization was turned to be more effective for salt marsh monitoring. The HH-HV value was the maximum of about 7.9 dB at 31.6 degree incidence angle, which is fairly consistent with the results of X-band ground radar measurement. The boundary of salt marsh is effectively traceable specifically by TerraSAR-X cross-polarization data. While interferometric phase is not coherent within normal tidal flat, areas of salt marsh where the landization is preceded show coherent interferometric phases regardless of seasons or tide conditions. Although TerraSAR-X interferometry may not be effective to directly measure height or changes in tidal flat surface, TanDEM-X or other future X-band SAR tandem missions within one-day interval would be useful for mapping tidal flat topography.

• Ocean and Polar Research
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• v.33 no.1
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• pp.1-11
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• 2011

This study describes measurements of fast ice recorded on May 23, 2009, in Kongsfjorden (translated as 'Kongs Fjord'), an inlet on the west coast of Spitsbergen in the Svalbard Archipelago. Seasonal fast ice is an important feature for Svalbard fjords, both in relation to their physical environment and also the local ecosystem, since it grows seaward from the coast and remains in place throughout the winter. Ice thickness, snow, ice properties, and wind speed were measured, while SAR (Synthetic Aperture Radar) data was observed simultaneously observed two times from ALOS-PALSAR (L-band). Measured ice thickness was about 25-35 cm while the thickness of ice floe broken from fast ice was measured as 10-15 cm. Average salinity was 1.9-2.0 ppt during the melting period. Polarimetric data was used to extract H/A/alpha-angle parameters of fast ice, ice floe, snow and glacier, which was classified into 18 classes based on these parameters. It was established that the area of fast ice represents surface scattering which indicates low and medium entropy surface scatters such as Bragg and random surfaces, while fast ice covered with snow belongs to a zone of low entropy surface scattering similar to snow-covered land surfaces. The results of this study will contribute to various interpretations of interrelationships between H/A/alpha parameters and the wave scattering Phenomenon of sea ice.

• Journal of electromagnetic engineering and science
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• v.5 no.4
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• pp.183-188
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• 2005

A simple microwave backscattering model for vegetation canopies on earth surfaces is developed in this study. A natural earth surface is modeled as a two-layer structure comprising a vegetation layer and a ground layer. This scattering model includes various scattering mechanisms up to the first-order multiple scattering( double-bounce scattering). Radar backscatter from ground surface has been modeled by the polarimetric semi-empirical model (PSEM), while the backscatter from the vegetation layer modeled by the vector radiative transfer model. The vegetation layer is modeled by random distribution of mixed scattering particles, such as leaves, branches and trunks. The number of input parameters has been minimized to simplify the scattering model. The computation results are compared with the experimental measurements, which were obtained by ground-based scatterometers and NASA/JPL air-borne synthetic aperture radar(SAR) system. It was found that the scattering model agrees well with the experimental data, even though the model used only ten input parameters.