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Deep learning is a promising method for image classification, including satellite images acquired by various sensors. However, the synergistic use of geospatial data for water body extraction from Sentinel-1 data using deep learning and the applicability of existing deep learning models have not been thoroughly tested for operational flood monitoring. Here, we present a novel water body extraction model based on a deep neural network that exploits Sentinel-1 data and flood-related geospatial datasets. For the model, the U-Net was customised and optimised to utilise Sentinel-1 data and other flood-related geospatial data, including digital elevation model (DEM), Slope, Aspect, Profile Curvature (PC), Topographic Wetness Index (TWI), Terrain Ruggedness Index (TRI), and Buffer for the Southeast Asia region. Testing and validation of the water body extraction model was applied to three Sentinel-1 images for Vietnam, Myanmar, and Bangladesh. By segmenting 384 Sentinel-1 images, model performance and segmentation accuracy for all of the 128 cases that the combination of stacked layers had determined were evaluated following the types of combined input layers. Of the 128 cases, 31 cases showed improvement in Overall Accuracy (OA), and 19 cases showed improvement in both averaged intersection over union (IOU) and F1 score for the three Sentinel-1 images segmented for water body extraction. The averaged OA, IOU, and F1 scores of the ‘Sentinel-1 VV’ band are 95.77, 80.35, and 88.85, respectively, whereas those of ‘band combination VV, Slope, PC, and TRI’ are 96.73, 85.42, and 92.08, showing improvement by exploiting geospatial data. Such improvement was further verified with water body extraction results for the Chindwin river basin, and quantitative analysis of ‘band combination VV, Slope, PC, and TRI’ showed an improvement of the F1 score by 7.68 percent compared to the segmentation output of the ‘Sentinel-1 VV’ band. Through this research, it was demonstrated that the accuracy of deep learning-based water body extraction from Sentinel-1 images can be improved up to 7.68 percent by employing geospatial data. To the best of our knowledge, this is the first work of research that demonstrates the synergistic use of geospatial data in deep learning-based water body extraction over wide areas. It is anticipated that the results of this research could be a valuable reference when deep neural networks are applied for satellite image segmentation for operational flood monitoring and when geospatial layers are employed to improve the accuracy of deep learning-based image segmentation.

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.

A sea surface imaging technique for an emergency response using a ready-made frequency modulated continuous wave&ndash, synthetic aperture radar (FMCW SAR) system and its experimental results are described in this paper. The optimal range of radiowave incidence angle for sea surface imaging was analyzed by a theoretical scattering model and measurement data, and it was properly applied to the FMCW SAR system by readjusting the delayed-dechirp process. Raw data acquired through flight experiments were reconstructed to SAR image by the range-doppler algorithm. To verify the performance of the reconstructed sea surface image, dual-channel images collected by the configuration of the along-track interferometry were used, and then performance indicators such as signal attenuation, coherence, and phase difference were analyzed. Through this experimental study, it was confirmed that the ready-made FMCW SAR system without a function of the incident angle control can also conduct limited missions for maritime observation. It is possible to be an alternative resource for emergency response, in which the cases are requiring urgent maritime disaster detection and analysis.

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.

Irrigated rice fields in Asia have a distinct topography and scattering mechanisms. Because of these factors, many studies using radar backscattering information have been conducted to improve the mapping accuracy; however, relatively little attention has been paid to the topographic features (TF) provided by polarimetric synthetic aperture Radar (PolSAR) data. To address this issue, this letter presents a simple rice field mapping method in its late-vegetative stage using both the TF and scattering features (SF) of the PolSAR data. First, two TF, the polarization orientation angle and the dominant beta angle from the PolSAR data, were analyzed with respect to the slope from a digital elevation model. The results indicated that this feature pair had a moderately high correlation. As a result, flat areas were easily extracted using these two TF. Second, to use the SF of rice in the late-vegetative stage, the copolarized ratio and the copolarized phase difference were simply combined to map only paddy fields, of which scattering was dominated by the double-bounce scattering caused by the ground and canopy reflection. The results using C-band Radarsat-2 data were compared with a support vector machine classifier and demonstrated that the proposed mapping method provided an overall better performance. The proposed method might also be efficiently applied, with modification, for the aforementioned purpose in inaccessible areas.

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.

Submarine groundwater discharge (SGD) is a widely recognized process that carries considerable amounts of groundwater and dissolved chemicals to the coastal ocean. Despite its importance, a lack of suitable tools to assess SGD's spatial and temporal variability has hampered a complete understanding of the process. Here we report, for the first time, use of an unmanned aerial vehicle (UAV or “drone”) to assess SGD variations. An octocopter UAV platform equipped with a thermal infrared (TIR) system was flown along a coastline on Jeju Island, Korea. The UAV clearly captured thermal signatures of SGD plumes and their dynamic temporal fluctuations modulated by tidal variations. Based on a plume area-SGD flux relation we developed by combining aerial and field data, we estimated that the SGD flux of the study site ranged from 33,000 to 54,000 m3 d−1. The drone approach enabled acquisition of time series plume imagery with easy control of spatial resolution, flexible field operations, and remote sensing of SGD at low cost compared to conventional aerial surveys. Combining the UAV-TIR images with on-site sampling enables one to determine fluxes of nutrients and other dissolved species. UAV-TIR mapping can thus serve as a powerful tool for study of SGD and other coastal processes.

Change detection using synthetic aperture radar (SAR) data is useful in emergency situations and unfavorable weather conditions. In this letter, change detection using multitemporal polarimetric Uninhabited Aerial Vehicle SAR data is investigated in an urban environment. The most robust polarimetric parameters are determined, and change detection techniques using a maximum likelihood ratio and a hyperbolic tangent model function are applied to the selected parameter. The model function was introduced to quantify the change characteristics and to rule out seasonal changes or those related to mobile features, and thus to only detect durable and permanent changes in urban environments. A comparison of results with historical Google Earth images showed a good level of agreement. Fitting of the hyperbolic tangent function to the multitemporal polarimetric parameters significantly reduces the false detection rate and indicates whether a building was constructed or destroyed, as well as when the detected changes occurred.

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.

Thwaites Ice Shelf in the Amundsen Sea is one of the biggest ice shelves in West Antarctica and is well known for significant mass changes. In the shear zone between Thwaites Glacier Tongue and its eastern ice shelf, shear stress forced by different flow rates of the ice shelves is causing the ice to break apart. A time series analysis of remote sensing data obtained by Landsat 7 Enhanced Thematic Mapper Plus (ETM+), TerraSAR-X, and airborne synthetic aperture radar (SAR) revealed that the shear zone has extended since 2006 and eventually disintegrated in 2008. We quantified the acceleration of Thwaites Ice Shelf with time by using the feature tracking method. The buttressing loss induced by the extension of the shear zone and progressive disintegration accelerated the flow of Thwaites Glacier Tongue, which in turn increased the shear stress on its eastern ice shelf. We determine causes of disintegration in the newly formed shear zone to be oceanic basal melting and structural weakening induced by Circump...

The Sea Surface Temperature (SST) is one of the most important oceanic environmental factors in determining the change of marine environments and ecological activities. Satellite thermal infrared images can be effective for understanding the global trend of sea surface temperature due to large scale. However, their low spatial resolution caused some limitations in some areas where complicated and refined coastal shapes due to many islands are present as in the Korean Peninsula. The coastal ocean is also very important because human activities interact with the environmental change of coastal area and most aqua farming is distributed in the coastal ocean. Thus, low-cost airborne thermal infrared remote sensing with high resolution capability is considered for verifying its possibility to extract SST and to monitor the changes of coastal environment. In this study, an airborne thermal infrared system was implemented using a low-cost and ground-based thermal infrared camera (FLIR), and more than 8 airborne acquisitions were carried out in the western coast of the Korean Peninsula during the periods between May 23, 2012 and December 7, 2013. The acquired thermal infrared images were radiometrically calibrated using an atmospheric radiative transfer model with a support from a temperature-humidity sensor, and geometrically calibrated using GPS and IMU sensors. In particular, the airborne sea surface temperature acquired in June 25, 2013 was compared and verified with satellite SST as well as ship-borne thermal infrared and in-situ SST data. As a result, the airborne thermal infrared sensor extracted SST with an accuracy of 1oC.

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.

Definite surface topography of ice provides fundamental information for most glaciologists to study climate change. However, the topography at the marginal region of ice sheets exhibits noticeable dynamical changes from fast flow velocity and large thinning rates; thus, it is difficult to determine instantaneous topography. In this study, the surface topography of the marginal region of Thwaites Glacier in the Amundsen Sector of West Antarctica, where ice melting and thinning are prevailing, is extracted using TanDEM-X interferometry in combination with data from the near-coincident CryoSat-2 radar altimeter. The absolute height offset, which has been a persistent problem in applying the interferometry technique for generating DEMs, is determined by linear least-squares fitting between the uncorrected TanDEM-X heights and reliable reference heights from CryoSat-2. The reliable heights are rigorously selected at locations of high normalized cross-correlation and low RMS heights between segments of data points. The generated digital elevation model with the resolved absolute height offset is assessed with airborne laser altimeter data from the Operation IceBridge that were acquired five months after TanDEM-X and show high correlation with biases of 3.19 m and −4.31 m at the grounding zone and over the ice sheet surface, respectively. For practical application of the generated DEM, grounding line estimation assuming hydrostatic equilibrium was carried out, and the feasibility was seen through comparison with the previous grounding line. Finally, it is expected that the combination of interferometry and altimetery with similar datasets can be applied at regions even with a lack of ground control points.

One of the main limitations in measuring ground deformation using synthetic aperture radar interferometry (InSAR) is atmospheric phase delay effects. In volcanic regions, the atmospheric phase delay effects can cause serious problems in detecting volcanic unrest because atmospheric thickness is inversely related with the elevation of a volcanic mountain. It is commonly known that the atmospheric phase screen (APS) can be decomposed spatially into stratified and turbulent components. In this paper, the stratified and turbulent atmospheric conditions of a volcanic area were simulated using weather research and forecasting (WRF) model, and the simulated atmospheric conditions were compared with in situ radiosonde data. The comparison results proved that the stratified APS from the WRF model could reflect the reasonable patterns of seasonal changes and vertical profiles with dependable quality. We also found that the stratified APS was significantly correlated with time and sometimes severely contaminated the quality of volcanic deformation estimation. These results indicate that the temporal high-pass (HP) filtering, which has been usually applied in time series InSAR analysis for extracting and removing APS, cannot work properly in volcanic area. Thus, we propose a new method that employs the stratified APS obtained from the WRF model by correlating with topography and the (residual) turbulent APS that can be effectively eliminated by temporal HP filtering in persistent scatterer interferometry (PSI). We applied the proposed method (atmosphere-corrected PSI) to Advanced Land Observing Satellite Phased Array type L-band SAR data that cover Shinmoedake volcano, Japan, and found that the estimated surface deformation and APS agreed well with those measured from GPS and Moderate-Resolution Imaging Spectroradiometer data, respectively.

Oh, J.H.; Kim, D.-J., and Lee, H.S., 2019. Topographic information extraction of tidal flats using remote multi-sensory data. In: Lee, J.L.; Yoon, J.-S.; Cho, W.C.; Muin, M., and Lee, J. (eds.), The 3rd International Water Safety Symposium. Journal of Coastal Research, Special Issue, No. 91, pp. 371-375. Coconut Creek (Florida), ISSN 0749-0208.Sediment from rivers has created a vast tidal flat over the west coast of Korea. The topography of the area is critical to the fishing industry and pollution purification, and it is a dangerous area causing fatal accidents due to the depth and steep slope with the tidal flow. Topographic information of the area needs to be obtained and monitored periodically for rapid changes due to periodic tides; however terrestrial surveying of the area is limited by poor accessibility. For this reason, it would be better to use remote sensors, such as satellite or aerial sensors, which differ in terms of spectral bands, spatial resolution, and coverage. This study integrated data from the three platforms, processed the data through synthetic aperture radar (SAR) interferometry and stereo aerial photogrammetry to generate separate Digital Elevation Models (DEMs), and then fused these into a final product using three-dimensional (3D) point cloud matching. The product was used for automatic extraction of tidal flat channel information by analyzing tidal flat topography and deriving channel depth and width.

The 2011 magnitude 9.0 Tohoku earthquake caused catastrophic damage to coastal areas in northeastern Japan. It is quite difficult to obtain an immediate assessment of large-scale natural disasters by ground survey. Microwave remote sensing by airborne or spaceborne sensors is a suitable tool for monitoring near-real-time damage over large areas. However, it is not always possible to acquire datasets with sufficient spatial and temporal resolutions for the precise detection of large areas of damage; therefore, this study focuses on the application of fully polarimetric scattering observations for deduction of information about damaged areas. Earthquake-induced changes in the radar backscattering mechanism are investigated by polarimetric scattering mechanism indicators. In addition, a change detection technique using the Expectation–Maximization (EM) based thresholding approach is applied to various polarimetric features. Furthermore, a new polarimetric information fusion method based on the contextual Markov Random Field (MRF) is proposed. The mapping accuracy for tsunami-swept urban areas can be improved by about 50% with significant reduction of false- and missed-alarm rates compared with the single-polarization SAR approach.

20세기 후반부터 유부도 주위에서 하구언 축조 등 비교적 큰 규모의 간척사업들이 진행되었다. 이러한 간척사업의 시작으로 인공구조물들이 연안에 축조됨에 따라 주변 해역의 해류, 조위 및 조류의 변화를 야기하여 퇴적 및 침식으로 인한 연안지형의 변화가 예상된다. 따라서 이 연구에서는 유부도 조간대를 포함하는 Landsat TM/ETM+자료를 1998년부터 2012년까지 획득한 후 waterline 기법을 적용하여 인공구조물 축조에 의한 지형변화를 탐지하였다. 그 결과 유부도의 동쪽, 북동쪽, 서쪽 조간대에서 주로 퇴적이 일어났으며 그 면적이 약 4.5 km2 이상 되었다. 한편, RADARSAT-2의 완전편파 SAR자료에 Freeman-Durden decomposition을 적용하여 퇴적이 뚜렷이 일어난 지역에 대한 산란특성을 분석하였다. 그 결과 동쪽 퇴적지역은 서쪽 및 북동쪽의 퇴적지역과는 다른 산란특징이 관찰되었으며, 이는 퇴적환경의 차이로 인해 다른 종류의 퇴적물이 퇴적되어 발생한 것으로 여겨진다.

Space-borne Synthetic Aperture Radar(SAR) has been one of the most effective tools for monitoring quantitative oceanographic physical parameters. The Doppler information recorded in single-channel SAR raw data can be useful in estimating moving velocity of water mass in ocean. The Doppler shift is caused by the relative motion between SAR sensor and the water mass of ocean surface. Thus, the moving velocity can be extracted by measuring the Doppler anomaly between extracted Doppler centroid and predicted Doppler centroid. The predicted Doppler centroid, defined as the Doppler centroid assuming that the target is not moving, is calculated based on the geometric parameters of a satellite, such as the satellite’s orbit, look angle, and attitude with regard to the rotating Earth. While the estimated Doppler shift, corresponding to the actual Doppler centroid in the situation of real SAR data acquisition, can be extracted directly from raw SAR signal data, which usually calculated by applying the Average Cross Correlation Coefficient(ACCC). The moving velocity was further refined to obtain ocean surface current by subtracting the phase velocity of Bragg-resonant capillary waves. These methods were applied to Envisat ASAR raw data acquired in the East Sea, and the extracted ocean surface currents were compared with the current measured by HF-radar.

Although space-borne satellites are useful in obtaining information all around the world, they cannot observe at a suitable time and place. In order to overcome these limitations, an airborne remote sensing system was developed in this study. It is composed of a SAR sensor and a thermal infrared sensor. Additionally GPS, IMU, and thermometer/hygrometer were attached to the plane for radiometric and geometric calibration. The brightness of SAR image varies depending on surface roughness, and capillary waves on the sea surface, which are easily generated by sea winds, induce the surface roughness. Thus, sea surface wind can be estimated using the relationship between quantified SAR backscattering coefficient and the sea surface wind. On the other hand, thermal infrared sensor is sensitive to measure object`s temperature. Sea surface temperature is obtained from the thermal infrared sensor after correcting the atmospheric effects which are located between sea surface and the sensor. Using these two remote sensing sensors mounted on airplane, four test flights were carried out along the west coast of Korea. The obtained SAR and thermal infrared images have shown that these images were useful enough to monitor coastal environment and estimate marine meteorology data.

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.

In this study, detection of icebergs that have various scattering characteristics aroundWilkinson glacier in West Antarctica is investigated using C-band fully-polarimetric RADARSAT-2SAR data. Various polarimetric analyses including Freeman-Durden decomposition, H/A/ @a decomposition, entropy (H) and anisotropy (A) method, and Wishart unsupervised classification, wereapplied for the RADARSAT-2 data used in this study. The polarimetric decomposition methods weresuccessfully classified most of the iceberg, yet some iceberg with similar intensity of volume andsurface scattering as sea ice were indistinguishable. Unsupervised classification with a combination ofthe polarimetric parameter, [1-H][1-A], gave a possibility to distinguish those unclassified iceberg.Key Words : Iceberg, West Antarctica, Polarimetry, RADARSAT-2, Classification i ¤ ™ A ² × ² i O c A$ – a8JMLJOTPO B Þ± o A“d Þ × i ¨ a ‘ AE `U8 I × B ‘8 Š c š ($ O X3"%"34"5 D io ž u a ? ³ ƒ eI 4"3 W 3I Þ E N a uS × Ý e8 E ³ Þ O i io ž u4"3 W Ax a uS × i ¨ a Ý e \oyW Ý u ‘ AE ` ?8 u ˆ a uS ×'SFFNBO %VSEFO EFDPNQPTJUJPO ) " @a EFDPNQPTJUJPO O ; ŠFOUSPQZ ) iBOJTPUSPQZ " Ý e \ — io ž u4"3W D ( 3$ c8JTIBSU – E ) ( e8 E ³N E4"3 W Ax Þ O i O ~ — 'SFFNBO %VSEFO ) " @a EFDPNQPTJUJPO8I a Ý e \7 D B ‘ \8\ ( Þ ON E c B — : $ a ´ v ‘ AE — Sx ‘ AE8 >N ŠS × B ‘7 ³ :N ‹ “ i E v ) i"D‘ a o uo Þ aK o u 3I a – E ) ( e7I Þ a B ‘ \8\ ³ Þ O i

Exposed oyster reefs in tidal flats have complex and rough surfaces because of their unique surface texture, which are quite distinct from the surrounding mud or sand flats. Here we investigate the microwave signatures, backscattered from naturally distributed oyster reefs in tidal flats, utilizing the polarimetric analysis techniques to fully polarimetric RADARSAT-2 (C-band) and ALOS PALSAR (L-band) data. The study areas include the tidal flats around Jebu Island and Hampyung Bay on the west coast of the Korean peninsula. We analyzed the microwave scattering mechanisms associated with oyster reefs and surrounding areas using the polarimetric target decomposition theorem and quantitatively measu ρ HHVV red target depolarization effects (the cross-polarized ratio (HV/VV), the co-polarized correlation coefficient ( ρ HHVV ), and the co-polarized phase difference between HH and VV). On the basis of a large increase in the cross-polarized backscattering (HV) in the C-band SAR data, one can observe strong volume (or multiple) scattering and depolarization effects over oyster reefs areas, whereas only surface scattering was dominant in most parts of the background tidal areas. In oyster reefs, the proportion of volume scattering and the cross-polarized ratio were greater than 0.7 and −8 dB, respectively. These scattering characteristics were also verified from in-situ measurements in the field using a ground-based polarimetric scatterometer system. However, almost no difference was observed between the scattering signatures of oyster reefs and background mudflat areas from L-band data, which have a considerably longer wavelength than C-band. The study clearly suggests that multi-frequency (C- and L-band) polarimetric SAR systems can be used to detect the naturally distributed oyster reefs in tidal flats.

In this paper, we have investigated the relationship between the depolarization effects and the wintertime sea ice thickness in the landfast ice region where smooth thick first-year ice (FYI) and deformed old ice coexisted by using C- and X-band spaceborne polarimetric synthetic aperture radar (SAR) data (RADARSAT-2 and TerraSAR-X). We have found a strong correlation between the in situ sea ice thickness and the SAR-derived depolarization factors (copolarized correlation and cross-polarized ratio). The observed relationships have demonstrated not only a categorical difference between FYI and multiyear ice (MYI) but also a one-to-one continuity in the scatter plots, rather than being clustered. It clearly shows that the observed correlations are not merely from the categorical difference in scattering mechanism between FYI and MYI and that there might exist a one-to-one relationship between thickness and depolarization factors at least in our deformed ice case. This suggests that depolarization factors could be effective SAR parameters in the estimation of wintertime sea ice thickness. Numerical model simulations explained some portions of the correlation by employing multiple scattering on the sea ice surface and volume scattering within the low-density subsurface layer.

The land cover map derived from spectral features of high resolution optical images has low spectral resolution and heterogeneity in the same land cover class. For this reason, despite the same land cover class, the land cover can be classified into various land cover classes especially in vegetation area. In order to overcome these problems, detailed vegetation classification is applied to optical satellite image and SAR(Synthetic Aperture Radar) integrated data in vegetation area which is the result of pre-classification from optical image. The pre-classification and vegetation classification were performed with MLC(Maximum Likelihood Classification) method. The hierarchical land cover classification was proposed from fusion of detailed vegetation classes and non-vegetation classes of pre-classification. We can verify the facts that the proposed method has higher accuracy than not only general SAR data and GLCM(Gray Level Co-occurrence Matrix) texture integrated methods but also hierarchical GLCM integrated method. Especially the proposed method has high accuracy with respect to both vegetation and non-vegetation classification.

In this study, a digital elevation model (DEM) in tidal flat of Suncheon Bay, one of the most ecological preserved area in the world, was generated from digital aerial stereo-images. The focal lengths for the aerial stereo-images were adjusted using ground control points (GCPs) in order to improve the accuracy of camera parameters. We proposed matching sizes suitable for generating DEM in tidal flat and a method for eliminating excessive position errors using intersection-distance() threshold value. The accuracies of the DEM generated from the proposed method as well as the commercial S/W were compared with the elevation profiles measured by Total Station in the filed. As the results, the DEM generated by the proposed method showed better result (maximum deviation is a -21 centimeters) with detailed topography than DEM by the commercial S/W in the region. These results suggest that the DEM of tidal flat, which hardly obtained with the traditional methods, can be generated from digital aerial images by applying the proposed method in this study. We believe that the generated DEM in tidal flat can be an essential data for monitoring the sediment erosion and deposit of the tidal flat.

This study proposes an inversion algorithm to extract the surface parameters, such as surface roughness and soil moisture contents, using multi-frequency SAR data. The study areas include the tidal flats of Jebu Island and the reclaimed lands of Hwaong district on the western coasts of the Korean peninsula. SAR data of three frequencies were accordingly calibrated to provide precise backscattering coefficients through absolute radiometric calibration. The root mean square (RMS) height and the correlation length, which can describe the surface roughness, were extracted from the backscattering coefficients using the inversion of the Integral Equation Method (IEM). The IEM model was appropriately modified to accommodate the environmental conditions of tidal flats. Volumetric soil moisture was also simultaneously extracted from the dielectric constant using the empirical model, which define the relations between volumetric soil moistures and dielectric constants. The results obtained from the proposed algorithm were verified with the in-situ measurements, and we confirmed that multi-frequency SAR observations combined with the surface scattering model for tidal flats can be used to quantitatively retrieve the geophysical surface parameters in tidal flats.

Most space-borne sensors cannot detect subsurface features. Groundwater is a typical subsurface feature, and its discharge to coastal ocean waters plays an important role in transporting terrestrial chemical constituents and providing habitats for various species of fauna and flora. This is the first paper to report observational evidence for submarine groundwater discharge (SGD) in tidal flats using space-borne synthetic aperture radar (SAR). Tidal flats are composed of high-moisture-saturated sediments and water puddles. These shallow water puddles were imaged effectively by using SAR systems. The presence of water puddles is usually indicated by low radar backscatter in SAR images due to specular reflections on the water surface. This effect was proved by comparing radar backscattering coefficients obtained from two space-borne SAR systems, TerraSAR-X and RADARSAT-2, with those obtained from two theoretical scattering models, IEM and Oh model. We observed relatively large, widely distributed water puddles in belt shape along the upper parts of the tidal flat, which were confirmed to be related to the discharge of groundwater. The results of this research suggest that SAR can be a powerful tool for observing and determining the areal distributions of possible groundwater discharge in large tidal flats, which is normally difficult to detect with traditional measurement tools or survey techniques for groundwater discharge. We firmly believe that this technique can reduce significantly the efforts of field work to confirm SGD in tidal flats.

RADARSAT-2 is a follow-up to RADARSAT-1 and is an all weather Earth observation satellite with fully polarimetric imaging capability. The synthetic aperture radars (SARs) onboard both RADARSATs are C-band imaging radars and they are well suited for Earth's ecosystem monitoring and maritime surveillance, because of the near polar orbit and their unique all weather imaging capability, independent of solar illumination. In this paper, RADARSAT-2 is first introduced and several applications of various modes of SAR data to coastal zone problems are discussed, including the coastal surface wind, waterline mapping, and polarimetric SAR data inversion for topographic and geological parameters of tidal flats. Coastal zones, the important interface between the land and the ocean, where a large proportion of the world's population inhabits, continuously change and evolve. The dynamic interaction of coastal winds, coupled with the coastal waves and currents, continuously erode rocks and land mass, and move and deposit various sediments on a continuous basis, along with the tides. Estimation of wind speeds and directions in coastal areas are empirically formulated and can further be improved with the available fully polarimetric data from RADARSAT-2. The water line mapping critically depends on the SAR frequency, or the wavelength of the SAR data used, and RADARSAT-2 SAR data using C-band should map waterlines more accurately than the longer wavelength L- or P-band SAR systems. The roughness parameters and partial information on the tidal flat compositions can be obtained from fully polarimetric SAR data. Some results obtained from NASA AIRSAR(2000) L-band data and RADARSAT-2(2008) C-band data do not fully agree with field measurements and further investigation is in progress. The inversion of polarimetric SAR data is a very complex problem and critically depends on the SAR signal frequency and model functions. RADARSAT-2 is an imaging radar, which is very flexible and powerful tool for potential coastal zone applications. Key RADARSAT-2 features and potential coastal zone application capabilities are also briefly reviewed.

Synthetic aperture radar (SAR) signals can propagate through hazardous weather and atmospheric conditions with heavy cloud cover, volcanic dust, snow, or rain. The all-weather capabilities of SARs have attracted significant interest in remote sensing communities, since serious environmental disasters such as oil spills have been highly ?elusive? to optical sensors, making visible spectrum data vulnerable to rapidly changing atmospheric conditions. In this paper, we discuss the technical functionalities of TerraSAR-X from the emergency response perspective, describing its technical abilities in terms of a damping ratio, radiometric accuracy, and noise level with reference to the actual Hebei Spirit oil-spill incident that occurred on the west coast of the Korean peninsula in December 2007. The damping ratios estimated from the TerraSAR-X data as a function of Bragg wavenumber for various wind speeds indicate that TerraSAR-X data can be effectively used to identify oil-spill areas with acceptable accuracy. We also received ERS-2, ENVISAT, RADARSAT-1, and ALOS PALSAR data for this oil-spill event, not simultaneously but with varying time delays. The processing results for the multitemporal data sets obtained from the X- and C-band SAR systems are useful since they can be used to determine the near-real-time migration of spilt oil. The results of the current study indicate that there are distinct advantages of using X-band TerraSAR-X data for oil-spill detection compared to the data obtained at other available frequencies.

The coastal zones of the Korean peninsula are well known for their large tide ranges and vast expanse of intertidal flats. In this paper, methods of extracting the roughness of the scattering surface of intertidal mudflats from polarimetric synthetic aperture radar (SAR) data have been investigated. The L-band NASA/Jet Propulsion Laboratories airborne SAR data, which were acquired in the intertidal zone during PACRIM-II Korea campaign, were used to estimate the roughness of intertidal mudflats. Surface roughness can be utilized as a useful parameter to monitor the fishery activities in intertidal flats as well as the changes in textural characteristics of surface sediments. In order to retrieve roughness parameters, such as the rms height and the correlation length, of intertidal mudflats, three types of roughness inversion algorithms, based on the Integral Equation Method (IEM), semiempirical, and extended-Bragg models, have been investigated and developed. The inversion algorithms based on the IEM and semiempirical models can be applied to the dual-polarized SAR, while the extended-Bragg model-based inversion approach is also applicable to the fully polarimetric SAR observations. Results indicate the fully polarimetric approach is more pertinent to monitor geophysical parameters from space than the dual polarimetric approach, even if it is possible to reduce the number of unknown surface variables in the specific case of inversion problems.

A new method for estimating the atmospheric transmittance and wind speed over the ocean from WindSat data is derived using a simplified model for the ocean surface reflectivity. The simplified reflectivity model is used to calculate both the surface emissivity and the reflection of downwelling atmospheric radiation. The wind-speed dependence of the surface reflectivity is parameterized using simple rational functions with coefficients determined from the WindSat data. Because the vertically polarized brightness temperature depends primarily on the atmospheric state, it is used to obtain an initial estimate of the atmospheric transmittance at each spatial location. These estimates are then combined with the horizontally polarized brightness temperature to estimate the wind speed at each location. The first wind-speed estimate is used to refine the estimate of the transmittance, and the process is repeated until the estimates converge, resulting in a simultaneous solution for the atmospheric transmittance and the wind speed. The results are illustrated for two WindSat data sets collected on September 12 and 14, 2003. We have also investigated two methods of estimating wind direction using WindSat measurements of the third and fourth Stokes parameters. The first method involves an algebraic solution for the wind direction from simultaneous measurements of the third and fourth Stokes parameters. The second method involves measurements of the third Stokes parameter from two look directions (fore and aft scan angles), made possible by the conical scanning geometry of WindSat. A comparison and evaluation of these methods is made using the same data sets.

Waterline detection in the intertidal areas was investigated through synthetic aperture radar (SAR) images and field measurements. Two valuable facts were found in this letter: 1) A discrepancy of waterlines between L- and P-band airborne SAR images was discovered and investigated through precise global positioning system measurements and the theory of the SAR imaging mechanism. In the intertidal areas having low slopes, the Bragg waves resonant with the radar signal can reside in different depths depending on the radar frequency, with the result that the boundary between water and land can be mapped differently in the respective SAR images. 2) Intertidal areas covered with a water film present low radar backscatter in SAR images, which can cause mislocation of waterlines

Space-borne and ariborne SAR (Synthetic Aperture Radar) systems and SAR application technology have recently advanced greatly and interferometric SAR (InSAR) techniques can now be more effectively applied and used in many geological and engineering problems. There are several SAR data acquisition geometries for interferometric applications and PS (Permanent Scatter) InSAR (SAR interferometry) technique can accurately measure very small deformations on the Earth's surface with greatly increased precision. In this paper, the PSInSAR technique is tested and utilized to monitor and measure the land surface subsidence of areas near Incheon Port, and selected locations in Busan, Korea. All available JERS-1 (Japanese Earth Resource Satellite-1) L-band SAR data were acquired, processed and used to estimate the ground subsidence and subsidence rates, which range up to 30 mm/year.

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.

Synthetic aperture radars (SAR) have higher spatial resolution than scatterometers and we can obtain more detailed wind vector information from space-borne SAR data. This type of high spatial resolution wind information can be very useful particularly in coastal regions, where the scatterometer wind information can be altered by the coastal effects because the larger footprint spatial averaging of backscattered energy is unavoidable. This paper tested RADARSAT data with CMOD_4 and CMOD_IFR2 algorithms for extracting wind information over selected coastal test areas around the Korean peninsula. Because the CMOD algorithms were originally developed for the C-band, VV-Polarized scatterometer data, we applied currently available polarization ratio models (e.g., Kirchhoff, Elfouhaily, and Thompson models) for RADARSAT data processing. Three test areas, the West Sea and East Sea on both sides of the Korea peninsula and the open sea off Jeju Island, were tested with the RADARSAT Fine, Standard, and ScanSAR beam mode data. The correlation of the wind vector results with the buoy and meteorological station data agrees well with each other but with some variations. The RMS error for the SAR-derived wind direction is somewhat great, and the wind speed RMS error using CMOD_4 algorithm is about 1.7 m/s (Kirchhoff), 1.84 m/s (Elfouhaily), and 2.4 m/s (Thompson polarization ratio model), respectively.

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.

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.