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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.

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.

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

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.

Precise image-to-image registration is required to process multi-sensor data together. The purpose of this paper is to develop an algorithm that register between high-resolution optical and SAR images using linear features. As a pre-processing step, initial alignment was fulfilled using manually selected tie points to remove any dislocations caused by scale difference, rotation, and translation of images. Canny edge operator was applied to both images to extract linear features. These features were used to design a cost function that finds matching points based on their similarity. Outliers having larger geometric differences than general matching points were eliminated. The remaining points were used to construct a new transformation model, which was combined the piecewise linear function with the global affine transformation, and applied to increase the accuracy of geometric correction.