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This paper suggests a novel and reliable method to detect water body from Sentinel-1 SAR satellite data using deep learning technique. There have been a lot of studies to extract water body from SAR images with deep learning. Although they achieved good performance, most of them used training data without guaranteeing good quality. In this study, land cover map generated by an official government agency were used for labelling ground truth data. After identifying the acquisition date of aerial photo used for generating the land cover map, vector polygons for river or reservoir were extracted and used as label data. This new method reduced producing time and cost to generate reliable training data. After training our deep learning model, it showed 0.874 of f1score. We also tested our deep learning model to the heavy rain season in Korea (August 2020) and successfully detected river flooding.

Monitoring of tidal creeks is important for safety in tidal flats and for understanding coastal changes due to sedimentation and erosion. The tidal creek is a small stream developed on tidal flats and requires very precise Digital Elevation Model (DEM) to detect it. Interferometric SAR (InSAR) technique was usually applied for generating DEM over inland regions. In tidal flat regions, low backscattering due to flatness and remnant water of the tidal flat prevents from generating high precision DEM. In this study, optimum InSAR baseline condition was investigated to generate such a precise DEM in the tidal flat. The long-baseline TanDEM-X and airborne InSAR system were found to be useful, and the tidal creek information (width and depth) was successfully extracted from the DEM that was generated from optimal baseline InSAR systems.

Monitoring and detecting ships via machine learning based algorithm were regarded efficient in martial and economic manners. As an algorithm regarding automated training data retrieval from SAR image was proposed, the identification of unclassified ships without AIS information could be raised as another challenging issue of ship surveillance. This study presented the effective identification algorithm of discerning unclassified ships from AIS information and the results of conventional ship detection based on machine learning. The accurately detected ships were selected from the conventional ship detection results, followed by the preprocessing of AIS information corresponding to the SAR images containing the detection results. Superposition of AIS information on accurate detection results was conducted and concluded the ships without AIS information as unclassified ships. From 3 Sentinel-1 SAR images, it obtained the average rate of identification as 85.67%. Additional research implementing the identification algorithm accompanied by rapidly acquired satellite or airborne SAR images could be effective in rendering a ship surveillance system with rapid response.

Recruitment corruption makes people demand fair and objective hiring procedures. The development of IT technology has promoted the emergence of recruitment system based on AI which make interview conduct without human intervention. As companies can reduce costs and efforts through the AI recruitment system, more and more companies are using the system. As the result, the research for figuring out the user intention on the system is needed. We designed the research model to find factors affecting the intention to use of AI-based recruitment system utilizing constructs of TAM and TOE. Also the moderating effect by the number of employees in the corporation will be estimated.

Recently, interest in the spread of the culture of sharing has been increasing at a social level due to the deepening income polarization, poverty, and the rapid growth of civil society and the importance of public interest activities of private organizations. In 2016, the National Statistical Office conducted a survey on changes in donation attitudes and recognition of donations, items that took up a large part in the area for the spread of the overall donation culture were the convenience of donation methods and the enhancement of transparency of donation organizations. The existing donation system is a way for donors to donate directly to several donor organizations. However, this method has its disadvantage: it is difficult for donors to see how their donations are spent. To address the convenience of such donation methods, based on the platform that is the core of the fourth industrial era, it enables unrestricted interaction in the network environment such as mobile or PC, inducing open participation in talent donation to the general public. Blockchain is a data forgery/modulation prevention technology based on distributed computing technology. Because the block chain records continuously changing data on all participating nodes, it is impossible to arbitrarily manipulate the data by the operators of distributed nodes. Blockchain technology is in the spotlight because it can secure transparency in transactions. In this paper, to solve these problems, we try to introduce the block chain technology into the donation system.

Assessment of bridge deflection and serviceability is essential for structural condition and infrastructure maintenance. In this study, we aim to estimate the high-resolution displacements of bridges using X-band Cosmo-SkyMed and C-band Sentinel-1 A/B SAR data. We applied multi-temporal Interferometric analysis to Geobuksan bridge and Dolsan Bridge in the Yeosu region. In addition to the bridge displacements, the geolocation error of scatterers were corrected by estimating DEM error.

Ship detection in coastal regions accompanied by machine learning could be effective in economic and martial issues. However, conventional researches on ship detection mainly focused on modifying the training model itself instead of obtaining qualified training data. In order to ameliorate the training data in the aspect of quality and quantity, this research aims to directly obtain training data from AIS information. From discrete AIS information, interpolation on SAR acquisition time was conducted, followed by adjusting the Doppler frequency shift caused by each vessel's velocity. Training data was constructed from the adjusted position using internal location of AIS sensor on each type of vessel. Extracted training data by the proposed algorithm from Sentinel-1 images was tested with CNN model. As the detection performance of the extracted training data exceeded that from visual interpretation, this study concluded that qualified training data could be extracted from the proposed algorithm.

Coastal sea level changes measured by tide gauges are affected by the severity of coastal land motion. Subsidence due to natural and anthropogenic activities in the coastal regions were directly exacerbates the tide gauge records. In this study, we aim to monitor the coastal land motion at the tide gauges in Korean peninsula using multi-temporal InSAR techniques. We present the methodology that simply employs the selection of sequential and small temporal interferograms in the StaMPS-SBAS technique for increased coherent PS pixels over coastal regions. C-band Sentinel-1 SAR data from ascending and descending mode were acquired over Pohang and Yeosu regions to map the coastal land motion. The preliminary results showed significant increased number of initial PS pixel density than conventional StaMPS-SBAS technique, chosen by Amplitude-Dispersion Index (ADI) and revealed the subsidence about 2 cm/year in Pohang tide gauge and small uplift of 1.46 mm/year near Yeosu tide gauge.

Tidal flats which are located between land and ocean are very vulnerable to the change of environment. These places are now facing many environmental challenges related to climate change and human-induced impacts. Topographic changes related to sedimentation or erosion in tidal flats are the most evident sign of the environmental changes. The tidal flats usually have small variations of topographies and experience ebb and flood tides every day. The conventional SAR interferometric techniques (such as repeat-pass InSAR) cannot be applied for generating digital elevation models (DEMs) in these tidal flats because of low coherence caused by ebb and flood tides. In this study, we developed a long-baseline single-pass airborne interferometric SAR (InSAR) system that has a small ambiguity height. We collected InSAR data in several tidal flats, the west coast of Korean peninsula, using our airborne InSAR system and TanDEM-X. The TanDEM-X is a space borne quasi-single pass interferometic SAR system. We also investigated the expected accuracy of DEM as function of baseline and coherence. In general, longer baseline is better for generating very sensitive and fine DEM that is absolutely needed for tidal flats, because longer baseline has smaller ambiguity height. But longer baseline can also cause low coherence due to baseline decorrelation. As the baseline increase, common spectral region is also decreased resulting in poorer coherence and poor vertical accuracy. Based on these investigations, we proposed optimal baselines for airborne InSAR system and space-borne SAR system. Finally, we compared the constructed topographies from our long-baseline airborne InSAR and TanDEM-X with GPS-RTK measurements.

Development of Big data, artificial intelligence and 5G networks, and advances have changed the marketing environment with the arrival of a hyper-connected society where everything is connected. And Kotler has described this change by naming it Market 4.0. In this environment, connectivity and communication between businesses and consumers have been emphasized, and constant communication is emphasized to match a brand identity and brand image in order to build a strong brand of business. Thus, from the point of view of communication, the brand identity prism model by Kapferer, which is an analytical framework of brand identity and brand image, has been framed. This paper used semantic network analysis to measure brand identity and brand image and analyzed difference in order to study semantic network analysis as strategic tool for building strong brand of enterprise. The brand identity was extracted from the web page managed by Samsung Electronics while the brand image was extracted through SNS and Samsung Members Page. The extracted data were interpreted by means of centrality after data preprocessing. This study found that Samsung Electronics’ brand identity and brand image matched that of “A global innovative technology company” And efficiency was demonstrated by comparing with prior studies studied around case analysis.

Coastal Subsidence is a global phenomenon that caused by both natural and anthropogenic activities. The impact of coastal subsidence can affect the monitoring of sea level rise by in-situ tide gauges. The Korean peninsula is one of such areas that reported considerably rapid sea level rise than the global average in the recent years. The objective of this study is to estimate the earth’s surface movements along the coastal areas of Pohang, South Korea. To achieve that, we acquired C-band Sentinel-1 data during 2016 – 2017. Time-series InSAR technique is applied to measure displacements at high-resolution with reduced decorrelation noise from interferograms. The results showed about 1.83 cm/year subsidence in the Pohang coastal area, where significant sea level rise is observed in this region. The results will provide further insight into the localized subsidence rates in the study sites and its impact on the sea level monitoring.

In this study, we investigated signal processing algorithm to reconstruct SAR image obtained from Frequency Modulated Continuous Wave - Synthetic Aperture Radar (FMCW-SAR). The airborne SAR raw data is usually obtained with continuous motion and non-linear (fluctuating) flight path. In order to compensate these effects, Back-Projection Algorithm (BPA) which can compensate the continuous motion effect was developed in this study. The algorithm was evaluated by applying it to the simulated and real-airborne SAR data.

Monitoring land subsidence is important to prevent and manage disasters. The extent of land subsidence can be measured by various ways and one of them is PSI technique. Guatemala City has geologically weak structure and suffered from disasters such as sinkhole and landslide. The purpose of this study was to measure wide range of relative movement in Guatemala City and to analyze obtained values. C-band Sentinel-1 A/B data during November 2014 to March 2018 were used in this study. By gathering information from both ascending and descending paths, relative movements were decomposed from line of sight of each path to vertical and horizontal component. As a result 4 regions in Guatemala City showed significant subsidence patterns with average vertical movement going down with a scale of 14 mm/year.

Subsidence is a widespread phenomenon caused by both natural and anthropogenic activities, particularly in the coastal areas. Eventually, the impact of coastal subsidence can affect the monitoring of sea level rise by in-situ tidal gauge stations. The Korean peninsula is one of such areas that reported considerably rapid sea level rise than the global average in the recent years. Therefore, there is a need for assessing the land subsidence component of relative sea level rise for better future prediction models. Space borne Interferometric SAR technique provides millimeter level of accuracy in displacement measurements. The objective of this study is to estimate the earth’s surface movements along the coastal areas of Pohang, South Korea. To achieve that, we acquired C-band Sentinel-1 data during 2016 – 2017. Time-series Stanford Method of Persistent Scatter (StaMPS) InSAR analysis proved technique to measure displacements at highresolution with reduced decorrelation noise from interferograms. The results showed about 1.83 cm/year subsidence in the Pohang coastal area, whereas significant sea level rise is observed in this region. The results will provide further insight into the localized subsidence rates in the study sites and its impact on the sea level monitoring.

This study aims to monitor the long term behavior of the bridge using time series interferometric technique. The accurate interpretation of the interferometric phase in the case of bridge, relies on the understanding of contributions of components such as DEM error, thermal expansion, and linear displacement. To decompose each contribution, this study applied the PSI algorithm using multi-temporal Cosmo-Skymed SAR data for Kimdaejung bridge. This study was able to find the unique displacement pattern, which is called as a deflection. The deflection is commonly caused by the creep, shrinkage, and ageing. Due to the early stage after the completion of the construction, the physical change of the bridge characteristics leads to the deflection. Thus, this paper verifies the potential to monitoring the long term deflection and implies that the bridge need to be monitored continuously.

In recent years, subsidence due to excessive groundwater withdrawal is a major problem in the Kathmandu Basin. In addition, on 25 April 2015, the basin experienced large crustal displacements caused by Mw 7.8 Gorkha earthquake. Consequently, the effects of co-seismic deformation could affect the temporal and spatial nature of anthropogenic subsidence in the basin. In this study, we applied Small Baseline subset (SBAS)-DinSAR technique to estimate the spatio-temporal displacements in the basin, before and after the earthquake. 16 ALOS-1 L-band and 20 Sentinel-1 C-band SAR data are used for measuring pre- and post-seismic subsidence velocity, respectively. We found that the subsidence velocity in the central part of the basin is increased after the mainshock.

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 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.

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.

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.

TanDEM-X (TerraSAR-X add-on for Digitial Elevation Measurement), a German SAR satellite, was launched in June 2010. Since 2012, TanDEM-X mission has provided the most detailed global DEM with unprecedented accuracy. Also, they carried out various experimental mode including long baseline XTI (cross track interferometry). Despite their progressive instrument calibration and high accurate orbit determination, the error of topographic height was still remained in the level of global DEM and was not entirely estimated. Particularly, the DEM accuracy in coastal area including tidal flats has never been reported. In this study, we evaluated the accuracy of TanDEM-X DEM in coastal area by comparing with RTK GPS measurements, and we investigated the optimal baseline condition to generate significant DEM in tidal flat.

Detection of changes induced by major events such as earthquakes, flooding and volcanic eruptions from interferometric SAR data is difficult due to the coupled effects with temporal decorrelation caused by natural phenomena such as rain, snow, wind and seasonal changes. In this study, we aim to separate the decorrelation caused by natural changes from the one caused by the major event by analyzing the coherence behavior using a temporal decorrelation model. We formulated the temporal decorrelation model that accounts for the random motion and dielectric changes. By applying the model into the multi-temporal coherence before the event, we extracted the temporal decorrelation components induced by natural phenomena. Based on the extracted parameters, their decorrelation probabilities related to natural changes were estimated in canopy and ground. The model parameters are also extracted from the interferometric SAR data acquired across the event. We compared probabilities between the natural phenomena and the certain event in order to assign the changed regions. Pixels with cumulative probabilities greater than 80% are selected 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 (ALOS) PALSAR data.

Grounding line estimation has substantial importance of determining vulnerability of ice mass in the Polar Regions. In this study, high resolution digital elevation model is utilized to estimate and update grounding line of Thwaites Glacier in West Antarctica in 2011. Estimation is done by comparing the calculated bottom topography of ice with the bathymetry model from Operation IceBridge. The bottom topography is computed by subtracting ice thickness which is also estimated from surface elevation assuming hydrostatic equilibrium. The updated grounding line infers its retreat of up to 5km inland when compared with the grounding line in 2009. The retreat is conspicuous over the bathymetric trough. Conceivable error sources are still present such as ice column density, bathymetry accuracy and firn height. Nonetheless, high resolution digital elevation model shows high practicability of estimating grounding line.

Paddy field extraction is a prerequisite to precision agriculture and to the monitoring of the rice condition. Many studies have been carried out for improving the mapping accuracy and retrieving the biophysical parameter, but most of these studies used the scattering characteristics of the rice crop, and little attention has been given to the topographic information provided by the single polarimetric synthetic aperture radar (PolSAR) data. To address this issue, this paper presents a paddy field extraction method using beta and polarization orientation angles (POAs). The beta angle is the tilt-angle measurement of target and the POA defines the angle between the normal ground surface and the incident plane. Thus, these two topographic parameters could be used to extract the paddy field. The experiment results using C-band Radarsat-2 data demonstrated that the proposed method is very simple and can be easily and efficiently used for the aforementioned purpose, but further studies are required for assessing its applicability.

This paper presents here aims at the retrieval of sea surface velocity during tropical clones using RADARSAT-1 ScanSAR Doppler centroid measurements. The sea surface velocity can be estimated by comparing Doppler shift anomalies between predicted and estimated Doppler centroids. The predicted Doppler centroid, defined as the Doppler centroid assuming that the target is not moving, is calculated based on the geometry model. While the estimated Doppler centroid, representing the moving target, can be extracted directly from SAR raw signal data by applying the Average Cross Correlation Coefficient (ACCC) method. In this study, we present characteristics of the sea surface response to tropical cyclones such as the size of hurricane eye or intensity and the spatial patterns of surface velocity from the center of hurricane. And we present the first attempt to derive sea surface velocity using RADARSAT-1 ScanSAR Doppler centroid measurements during two different hurricane (Typhoon Xangsane and Hurricane Lili) and three sequential cases of Hurricane Lili, especially when using inaccurate satellite's orbit and attitude information with wide coverage, such as RADARSAT-1 ScanSAR wide mode. Although the result was compared with one drifting buoy data in a single location during Typhoon Xangsane, it clearly shows that the sea surface velocity during tropical cyclones can represent the sea surface current.

SAR change detection is useful when emergency situations occurred and weather conditions are unfavourable. In this study, a change detection using multi-temporal polarimetric UAVSAR data was investigated in urban environment. The most robust polarimetric parameter was evaluated, and change detction techniques using maximum likelihood ratio and hyperbolic tanget function were applied to the selected parameters. The comparison results with Google Earth's historical images showed a quite good agreement. A fitting of hyperbolic tangent function to the multi-temporal polarimetric parameters much reduced the false alarm rate, and it also provide whether the building was constructed or destructed and when the the changes occurred.

TanDEM mission enables the generation of high resolution digital elevation model over fast changing surfaces such as the Antarctic ice sheets. This study assesses the surface elevation over the marginal region of Thwaites Glacier in West Antarctica. The absolute height of SAR interferometry was derived by utilizing CryoSat-2 radar altimeter over the same region with minimizing temporal differences between the datasets. Then, the derived heights are compared with the airborne laser and radar altimetry data from the Operation IceBridge. The results show that surface and coherence are two main factors causing height offsets between the datasets, however, each effect must be separated for more accurate analysis.

Geophysical processes occur throughout the Earth system including all hydrosphere, atmosphere and Solid Earth. These geophysical processes are monitored using seismic (and acoustic) wave, measuring the changes in the magnetic and gravitational forces across the target areas, or measuring the changes in thermal properties across and surrounding the interested target areas. In this respect, application of synthetic aperture radar (SAR) is relatively limited compared to other geophysical survey methods, because SAR observation and related studies rely on the backscattered microwave signal received from the target surface areas through antennae. However, unlike optical remote sensing data, the additional phase information in addition to the amplitude values of processed SAR images allows us to develop interferometric techniques and also the polarimetric decomposition approaches, with which one can distinguish the scattering characteristics of the scattering target(s). Recent availability of fully polarimetric SAR imaging modes, at several frequencies (currently X-, C- and L-bands), has greatly extended the SAR application potential for various geophysics problems.

The coastal sea surface temperature (SST) is one of the important oceanic environmental factors in determining the change of marine environments and ecological activities. In order to extract coastal SST, we developed ship- and airborne thermal infrared remote sensing systems. The acquired thermal infrared images are radiometrically calibrated using an atmospheric radiative transfer model as well as a thermometer/hygrometer sensor and geometrically calibrated using a GPS/IMU sensor. In this study, the ship- and airborne SST data were compared and verified with spaceborne SST data and in-situ data. The comparison and validation results showed that the ship and air-borne thermal infrared remote sensing could be used in generating SST map, especially in mapping fine-scale coastal features.

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.

The surface heights of the marginal region of ice sheets are of interest among most glaciologist and remote sensing studies of glaciers. There have been a number of difficulties in estimating accuracy surface information in the marginal regions due to rough surfaces and high slope angles. In this study, the surface heights of the marginal region of Thwaites Glacier are calculated in high resolution using SAR interferometry of TanDEM-X. The calculated surface heights are compared after the absolute offset correction using CryoSat-2 radar altimeter. The results show that the general surface patterns are highly correlated, however, the RMS heights are larger than expected. The possible explanations can be related to the footprint size of CryoSat-2 and snow penetration depth due to different radar frequencies. Besides, absolute phase offset needs to be calculated accurately. In general, the possibility of utilizing TanDEM-X and CryoSat-2 data in the marginal regions is expected to be promising.

With advance of mobile sensor and wireless communication technologies, it becomes more feasible to monitor daily lives than ever. A smart phone, capable of sensing human motion as well as tracking current location, can record motion behavior as well as motion boundary for pattern study of social life. A passive or active Radio-frequency identification (RFID) based location tracing systems provide the resourceful information of the wildlife habitats. Accelerometers and gyroscopes can help to monitor daily activities of certain patient such as exercise patterns of the obesity. Regardless of how good the sensor is, missing or noisy data can be generated at any time with any reason-caused by the nature of monitoring sensor (on-body sensor) or communication failure. In data analysis, missing or noisy data generates many problems. In the last few decades, many approaches have been proposed. However, traditional approaches of handling missing data may require very complicated method and computational power to estimate the missing data. In this paper, we propose the Canonical Correlation based k weighted Angular Similarity (CkWAS) to map the missing data with reference pattern data set. Our experimental results show that the precision of finding similar motion patterns is 92% with 5% missing data and 64% with 95% missing data.

Tidal flat plays an import role in purifying pollutants discharged from land and in providing marine products such as oyster and many kinds of shellfishes. Oyster in tidal flat usually has rough structures, causing a strong depolarization in microwave backscattering. The signatures can be detected using multi-frequency polarimetric synthetic aperture radar (SAR) data. Strong volume and depolarization effects were observed in the oyster reefs of C-band SAR data, while only surface scattering was dominant in the L-band SAR data. We also investigated why the oyster reefs distributed in those areas and how they generated naturally. We focused on groundwater discharge to relate the distribution of oyster in tidal flat, and found obvious signatures of groundwater discharge along the marginal part of the tidal flat from SAR data.

Sea surface current plays an important role in understanding physical oceanography and can provide critical information for preventing natural disasters such as oil spill and ship distress. In this study, two techniques using space-borne Synthetic Aperture Radar (SAR) systems were processed to evaluate their feasibility to extract sea surface current velocities. The first technique employs the Doppler shift algorithm from a single SAR system which is generated when moving targets are imaged in East Sea of Korean Peninsula. The second technique utilizes Along-Track Interferometry (ATI) from dual SAR system to estimate sea surface current velocity in Strait of Korea. Envisat ASAR and TanDEM-X (TerraSAR-X add-on for Digital Elevation Measurement) data were used in each technique, respectively.

One of difficulties in measuring the ground deformation using SAR interferometry is the atmospheric phase screen (APS). Severe stratified APS could occur in mountain region. Thus APS could compromise the accuracy of the ground deformation estimated by SAR interferometry in stratovolcano. Since the stratified APS is correlated with the elevation, both ground deformation and APS error are indistinguishable. In order to improve the accuracy of the ground deformation and estimate the accurate APS involved in SAR interferogram, the effective algorithm is necessary which reflect the properties of APS in space and time. In this research we proposed a time-series approach combined with the weather prediction model. The main concept about APS is that the severe stratified APS usually occur in mountain region correlating with elevation and has the seasonality, while the turbulent APS has a random process in time and space. On basis of these temporal and spatial properties, we applied the troposphere-corrected time-series interferometry and successfully extracted both APS and estimated the better ground deformation results than a conventional time-series analysis.

Various polarimetric analyses were carried out in order to verify the break-up of the Thwaites Ice Tongue. The hypothesis was that the observed crack on the ice tongue must be filled with sea ice if completely broken. Although the recently published paper asserted that the ice tongue had been completely broken, we found that it is too early to come into the conclusion. The depolarization ratio is mainly used to compare and distinguish between certain features of the ice surface and entropy, as well as mean alpha angle, is also computed as complementary information.

The atmospheric phase delay when microwave propagates in troposphere can be severe and be misinterpreted as a surface deformation in differential SAR interferometry (DInSAR). The atmospheric phase delay errors are main difficulties in measuring the deformation caused by volcanic activities. In order to minimize the effects of atmospheric water vapor we calculated mesoscale atmospheric phase delay effects in DInSAR from the various atmospheric data such as WRF model, MODIS products, and radiosonde data. In addition, time-series analysis with atmospheric correction technique was carried out. We successfully minimize the atmospheric phase delay effects, misinterpreted as deformation, and measured the ground motion on the Shinmoedake volcano.

This paper investigates a quantization and clustering issue on human motion performance constrained by disabilities. In a longitudinal study of medical therapy on motion disorder, stages of patient disability condition change over time. We investigate four different stages of one arm constrained walking motions by restricting 0%, 10%, 16% and 22% of arm swing angles. For analysis we use One-way ANOVA and K-mean clustering to indentify the most significant features and to partition four different motion constrained groups. Our experimental result shows that all four arm constraints during walking motion are clustered with an average accuracy of 91.7% on two different feature conditions: a mixture of singular value decomposition (SVD) and power spectral density (PSD); and SVD only on selected gait cycles. The proposed method can be integrated with a ubiquitous system (using wearable sensors) for a remote distance patient monitoring system analysis.