kyo Jung

HLA class II allele associations in Korean patients with pemphigus.

Background: Studies at the population level have demonstrated associations between pemphigus (pemphigus vulgaris, PV, and pemphigus foliaceus, PF) and particular HLA haplotypes, which suggests that there may be a genetic predisposition for the disease. Objective/Methods: The aim of the present study was to examine the distribution/frequency pattern of HLA class II alleles (DRB1, DQA1 and DQB1) from a group of 30 Korean patients with pemphigus (15 PV and 15 PF) by PCR amplification with sequence-specific primers. Results: In PV, the frequency of DRB1*01 allele was found to be significantly high (pc = 0.0014); in PF, DRB1*01, DQA1*0302 and DQB1*0603 alleles showed positive associations with statistical significances (pc = 0.0002, 0.0007 and 0.0067, respectively), when compared with those found in Korean controls. Conclusions: In this small-sample study, findings of allelic frequencies among Korean patients with pemphigus are somewhat different from those found in other populations.

Coherent Change Detection Using InSAR Temporal Decorrelation Model: A Case Study for Volcanic Ash Detection

Detection of changes caused by major events-such as earthquakes, volcanic eruptions, and floods-from interferometric synthetic aperture radar (SAR) data is challenging because of the coupled effects with temporal decorrelation caused by natural phenomena, including rain, snow, wind, and seasonal changes. The coupled effect of major events and natural phenomena sometimes leads to misinterpretation of interferometric coherence maps and often degrades the performance of change detection algorithms. To differentiate decorrelation sources caused by natural changes from those caused by an event of interest, we formulated a temporal decorrelation model that accounts for the random motion of canopy elements, temporally correlated dielectric changes, and temporally uncorrelated dielectric changes of canopy and ground. The model parameters are extracted from the interferometric pairs associated with natural changes in canopy and ground using the proposed temporal decorrelation model. In addition, the cumulative distribution functions of the temporally uncorrelated model parameters, which are associated with natural changes in canopy and ground, are estimated from interferometric pairs acquired before the event. Model parameters are also extracted from interferometric SAR data acquired across the event and compared with the cumulative probabilities of natural changes in order to calculate the probability of a major event. Subsequently, pixels with cumulative probabilities greater than 75% are marked as changed due to the event. A case study for detecting volcanic ash during the eruption of the Shinmoedake volcano in January 2011 was carried out using L-band Advanced Land Observation Satellite PALSAR data.

Development of a Cost-Effective Airborne Remote Sensing System for Coastal Monitoring

Coastal lands and nearshore marine areas are productive and rapidly changing places. However, these areas face many environmental challenges related to climate change and human-induced impacts. Space-borne remote sensing systems may be restricted in monitoring these areas because of their spatial and temporal resolutions. In situ measurements are also constrained from accessing the area and obtaining wide-coverage data. In these respects, airborne remote sensing sensors could be the most appropriate tools for monitoring these coastal areas. In this study, a cost-effective airborne remote sensing system with synthetic aperture radar and thermal infrared sensors was implemented to survey coastal areas. Calibration techniques and geophysical model algorithms were developed for the airborne system to observe the topography of intertidal flats, coastal sea surface current, sea surface temperature, and submarine groundwater discharge.

Temporal decorrelation model in repeat pass SAR interferometry for detection of volcanic ash

The coherence in SAR interferometry is used as a parameters for change detection. However, it is difficult to quantitatively analyze the coherence value because the decorrelation come from diverse reasons and the unwanted targets naturally changes. In order to isolate the changed region by an accumulation of the volcanic ash, we analyze the reasons of the decorrelation. We estimate the temporal decorrelation using time-series dataset and predict the temporal decorrelation for dataset involving dramatic changes. The estimated and the expected ratio is useful to identify the regions affected by volcanic ash. This method successfully isolate the regions with dramatic change due to volcanic ash from the naturally changing region, easily misinterpreted as a dramatic changed area.

Subsidence in the Kathmandu Basin, before and after the 2015 Mw 7.8 Gorkha Earthquake, Nepal Revealed from Small Baseline Subset-DInSAR Analysis

Land subsidence in densely urbanized areas is a global problem that is primarily caused by excessive groundwater withdrawal. The Kathmandu Basin is one such area where subsidence due to groundwater depletion has been a major problem in recent years. Moreover, on 25 April 2015, this basin experienced large crustal movements caused by the Gorkha earthquake (Mw 7.8). Consequently, the effects of earthquake-induced deformation could affect the temporal and spatial nature of anthropogenic subsidence in the basin. However, this effect has not yet been fully studied. In this paper, we applied the SBAS-DInSAR technique to estimate the spatiotemporal displacement of land subsidence in the Kathmandu Basin before and after the Gorkha earthquake, using 16 ALOS-1 Phased Array L-band Synthetic Aperture Radar (PALSAR) images during the pre-seismic period and 26 Sentinel-1 A/B SAR images during the pre- and post-seismic periods. The results showed that the mean subsidence rate in the central part of the basin was about −8.2 cm/year before the earthquake. The spatial extents of the subsiding areas were well-correlated with the spatial distributions of the compressible clay layers in the basin. We infer from time-series InSAR analysis that subsidence in the Kathmandu basin could be associated with fluvio-lacustrine (clay) deposits and local hydrogeological conditions. However, after the mainshock, the subsidence rate significantly increased to −15 and −12 cm/year during early post-seismic (108 days) and post-seismic (2015–2016) period, respectively. Based on a spatial analysis of the subsidence rate map, the entire basin uplifted during the co-seismic period has started to subside and become stable during the early-post-seismic period. This is because of the elastic rebound of co-seismic deformation. However, interestingly, the localized areas show increased subsidence rates during both the early-post- and post-seismic periods. Therefore, we believe that the large co-seismic deformation experienced in this basin might induce the local subsidence to increase in rate, caused by oscillations of the water table level in the clay layer.

Damage-Mapping Algorithm Based on Coherence Model Using Multitemporal Polarimetric–Interferometric SAR Data

This paper presents a new damage-mapping algorithm based on coherence images estimated from multitemporal polarimetric–interferometric synthetic aperture radar (SAR) data. The interferometric coherence has been restricted in the conventional damage-mapping approaches because the decorrelation sources are too complicated to interpret accurately and temporal decorrelation effects caused by slowly occurring natural changes and disaster events are often coupled together. To overcome these limitations, we formulate a coherence model that accounts for temporal decorrelation in two simplified layers, ground and volume layers, for long-temporal repeat-pass scenarios with zero spatial baseline. The model parameters include: 1) ground-to-volume ratio, a factor to determine the relative scattering contribution of ground and volume layers; 2) temporally correlated change, which captures the exponentially decaying behavior of coherence with time; and 3) temporally uncorrelated change, which is associated with random temporal changes. We estimate the model parameters in three steps: coherence optimization, interferometric pair-invariant parameter estimation, and interferometric pair-variant parameter estimation. To isolate the effects of disaster events from background natural changes, we calculate the probability density functions of historical change pixel by pixel and produce a probability map of damage. We tested the algorithm with uninhabited aerial vehicle data acquired from 2009 to 2015 for mapping the area damaged by the 2015 Lake Fire in California. Based on performance evaluation using receiver operating characteristic curves for optimized coherences and averaged probability maps, the proposed method reduced the false alarm from 0.25 to 0.07 when the probability of detection was 0.85 compared to coherence products alone.

Damage mapping based on coherence model using multi-temporal polarimetric-interferometric UAVSAR data

This study aims to evaluate the potential of coherent change detection using multi-temporal polarimetric interferometric SAR data. One of the limitations in damage area extraction is that the decorrelation caused by the disaster is commonly coupled with the natural changes. Also, the interpretation of the coherence is troublesome and requires the coherence model. The approach used in this study is based on the modified coherence model for a case of long-temporal and zero-spatial baseline. The inversion processes yield the temporal decorrelation contributions of ground and volume, respectively, having the physical meaning. We additionally applied simple statistical probability estimation method for the damage area to isolate the contributions of disaster from the natural changes. In this study, we used UAVSAR data acquired over Lake fire which occurred in June, 2015.

Intertidal flat topographies measured by long-baseline airborne sar and tandem-x

Intertidal flats which are located between land and ocean are productive and rapidly changing places. But these places are now facing many environmental challenges related to climate change and human-induced impacts. Topographic change related to sedimentation or erosion in intertidal flats is the most evident sign of the environmental changes. The intertidal flats usually have small topographic variations (less than 5m) and experience ebb and flood tides every day. Thus, the conventional SAR interferometric techniques (repeat-pass InSAR) cannot be applied for generating DEMs in these intertidal flats. In this study, we developed a long-baseline single-pass airborne interferometric SAR (InSAR) system that has small ambiguity height and collected airborne InSAR data in several intertidal flats, the west coast of Korean peninsula. The constructed topographies using the long-baseline airborne InSAR system were compared with TanDEM-X DEM obtained during long-baseline mission phase.

A long baseline airborne SAR interferometry for tidal flat mapping

Topographic change due to sedimentation and erosion of tidal flat is important for recognizing environmental changes and possible threatens. The tidal flat generally has small topographic variations and high moisture soil surfaces. The conventional SAR interferometric techniques cannot be used for generating DEMs in these tidal flats due to relatively short baseline. In this study, we developed a long-baseline airborne interferometric SAR (InSAR) system that has small ambiguity height and collected airborne InSAR data in the western coast of Korean peninsula. The constructed topographies using the long-baseline airborne InSAR were compared with GPS-RTK measurements.

Measurements of intertidal flat topography using a long-baseline airborne interferometric SAR

Intertidal flats are productive and rapidly changing places. However, these places are facing many environmental challenges related to climate change and human-induced impacts. Topographic change due to sedimentation or erosion in intertidal flats can be the key indicator for recognizing these environmental changes. The intertidal flats usually have small topographic variations (less than 5m) and high-moistured soil surfaces (greater than 50%). The conventional SAR interferometric techniques cannot be used for generating DEMs in these intertidal flats. In this study, we developed a long-baseline airborne interferometric SAR (InSAR) system that has small ambiguity height and collected airborne InSAR data in Jebu intertidal flat, west coast of Korean peninsula. The constructed topographies using the long-baseline airborne InSAR were compared with TanDEM-X DEM (acquired during long-baseline mission phase) and GPS-RTK measurements.