• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1691-1707
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• 2022

Cheonji Lake, the caldera of Baekdu Mountain, located on the border of the Korean Peninsula and China, alternates between melting and freezing seasonally. There is a magma chamber beneath Cheonji, and variations in the magma chamber cause volcanic antecedents such as changes in the temperature and water pressure of hot spring water. Consequently, there is an abnormal region in Cheonji where ice melts quicker than in other areas, freezes late even during the freezing period, and has a high-temperature water surface. The abnormal area is a discharge region for hot spring water, and its ice gradient may be used to monitor volcanic activity. However, due to geographical, political and spatial issues, periodic observation of abnormal regions of Cheonji is limited. In this study, the degree of ice change in the optimal region was quantified using a Landsat -5/-7/-8 optical satellite image and a Modified U-Net regression model. From January 22, 1985 to December 8, 2020, the Visible and Near Infrared (VNIR) band of 83 Landsat images including anomalous regions was utilized. Using the relative spectral reflectance of water and ice in the VNIR band, unique data were generated for quantitative ice variability monitoring. To preserve as much information as possible from the visible and near-infrared bands, ice gradient was noticed by applying it to U-Net with two encoders, achieving good prediction accuracy with a Root Mean Square Error (RMSE) of 140 and a correlation value of 0.9968. Since the ice change value can be seen with high precision from Landsat images using Modified U-Net in the future may be utilized as one of the methods to monitor Baekdu Mountain's volcanic activity, and a more specific volcano monitoring system can be built.

• Korean Journal of Remote Sensing
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• v.36 no.3
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• pp.401-410
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• 2020

Recently, many studies have been conducted on the changing phenology on the Korean Peninsula due to global warming. However, because of the geographical characteristics, research on plant season in autumn, which is difficult to measure compared to spring season, is insufficient. In this study, all leaves that maple and fallen leaves were defined as 'Decay leaves' and decay leaf detection was performed based on the Landsat-8 satellite image. The first threshold value of decay leaves was calculated by using NDVI and the secondary threshold value of decay leaves was calculated using by NDWI and the difference of spectral characteristics with green leaves. POD, FAR values were used to verify accuracy of the dry leaf detection algorithm in this study, and the results showed high accuracy with POD of 98.619 and FAR of 1.203.

• Journal of Wetlands Research
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• v.8 no.3
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• pp.29-38
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• 2006

Digital Elevation Model (DEM) of intertidal flat can be widely used not only for scientific fields, coastal management, fisheries, ocean safety, military, but also for understanding natural and artificial topographic changes of the tidal flat. In this study, we generated DEM of the Ganghwado southern intertidal flat, the largest tidal flat in the west coast of the Korean Peninsula, using waterline method and interferometric synthetic aperture radar (InSAR). Constructed DEM which applied waterline method to the Landsat-5 TM and Landsat-7 ETM+ images closely expresses overall topographic relief of tidal flat. We found that the accuracy was determined by the number of waterlines which reflect various tidal conditions. The application of InSAR to the ERS-1/2 and ENVISAT images showed that only ERS-1/2 tandem pairs successfully generated DEM in the part of northern Yeongjongdo, but construction of DEM in the other areas was difficult due to the low coherence caused by a lot of surface remnant waters. In the near future, Kompsat-2 will provide satellite images having multi-spectral and high spatial resolution within a relatively short period at different sea levels. Application of waterline method to these images will help us construct a high precision tidal flat DEM. Also, we should develop DEM generation method using single-pass microwave satellite images.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.6
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• pp.445-452
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• 2019

In this study, parallel processing codes of k-means clustering algorithm were developed and implemented in a PC-cluster for unsupervised classification of large satellite images. We implemented intra-node code using multicores of CPU (Central Processing Unit) based on OpenMP (Open Multi-Processing), inter-nodes code using a PC-cluster based on message passing interface, and hybrid code using both. The PC-cluster consists of one master node and eight slave nodes, and each node is equipped with eight multicores. Two operating systems, Microsoft Windows and Canonical Ubuntu, were installed in the PC-cluster in turn and tested to compare parallel processing performance. Two multispectral satellite images were tested, which are a medium-capacity LANDSAT 8 OLI (Operational Land Imager) image and a high-capacity Sentinel 2A image. To evaluate the performance of parallel processing, speedup and efficiency were measured. Overall, the speedup was over N / 2 and the efficiency was over 0.5. From the comparison of the two operating systems, the Ubuntu system showed two to three times faster performance. To confirm that the results of the sequential and parallel processing coincide with the other, the center value of each band and the number of classified pixels were compared, and result images were examined by pixel to pixel comparison. It was found that care should be taken to avoid false sharing of OpenMP in intra-node implementation. To process large satellite images in a PC-cluster, code and hardware should be designed to reduce performance degradation caused by file I / O. Also, it was found that performance can differ depending on the operating system installed in a PC-cluster.

• Journal of Cadastre & Land InformatiX
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• v.46 no.2
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• pp.183-196
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• 2016

Ground control points are needed for precision geometric correction of satellite images, and the coordinates of a high-quality ground control point can be obtained from the GPS measurement. However, considering the GPS measurement requires an excessive amount o f t ime a nd e fforts, there is a need for coming up with an alternative solution to replace it. Therefore, we examined the possibility of replacing the existing GPS measurement with coordinates available at online maps to acquire the coordinates of ground control points. To this end, we examined error amounts between the coordinates of ground control points obtained through Daum Map API, and them compared the accuracies between three types of coordinate transformation equations which were used for geometric correction of satellite images. In addition, we used the coordinate transformation equation with the highest accuracy, the coordinates of ground control point obtained through the GPS measurement and those acquired through D aum M ap A PI, and conducted geometric correction on them to compare their accuracy and evaluate their effectiveness. According to the results, the 3rd order polynomial transformation equation showed the highest accuracy among three types of coordinates transformation equations. In the case of using mid-resolution satellite images such as those taken by Landsat-8, it seems that it is possible to use geometrically corrected images that have been obtained after acquiring the coordinates of ground control points through Daum Map API.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.52-52
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• 2023

저수지는 기존의 육상 수지에 직접적인 영향 뿐 만 아니라 수체가 육상에 머무르는 시간을 늘려 수온 및 수질에는 영향을 미친다. 이들이 환경 및 지역 기후 변화에 직접적인 영향을 미치는 주요인자로 기후 변화에 미치는 긍정적, 부정적 효과와 함께 중요성이 더 증대되고 있다. 위성 원격탐사는 북한 지역 등과 같은 현장 관측 자료의 수집이 어려운 지역을 포함한 전 지구 규모에서 저수량 변화를 추정하는데 유용한 자료를 제공한다. 우리는 광학 위성 (Landsat-8/9)과 능동형 마이크로파 위성 (Sentinel-1)를 활용해 한반도 지역에 분포하고 있는 저수지의 수체 면적을 산출하기 위해 2020년부터 2022년까지 자료를 수집했다. 저수지 표면적 산출은 전통적인 NDWI (Normalized Difference Water Index) 및 후방산란계수 (𝜎₀)에 multi-Otsu 방법을 적용하여 이진화 영상을 얻는 방식을 이용했다. 여전히 남아있는 과탐지 영역은 최대 표면적 영상과 상대 비교를 통해 제거했다. Landsat과 Sentinel-1 위성 원격 탐사 자료 기반 저수지 표면적은 높은 유사성이 있었고, 현장 및 위성 고도계 자료 기반 수면 고도 변화와 높은 관계성를 보여주었다. 실험을 통해 위성 원격탐사 자료를 활용한 한반도 지역 저수지의 저수량 변화을 추정했으며, 현장 관측자료와 비교했다. 이 추정 기술은 전 지구 저수지 및 호수로 확장할 수 있으며, 수문 모델의 검증자료 등으로 활용될 수 있다.

• Korean Journal of Remote Sensing
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• v.39 no.4
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• pp.409-423
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• 2023

North Korea is carrying out reclamation activities in tidal flat areas distributed throughout the west coast. Previousremote sensing research on North Korean tidal flats either failsto reflect recent trends or focuses on identifying and analyzing tidal flats. Thisstudy aimsto quantify the impact of recent reclamation activitiesin North Korea's coastal areas and contribute knowledge useful for determining the best remote sensing methods for coastal areas with limited accessibility, such as those in North Korea. Using Landsat-8 OLI images from 2014-2022, we analyzed land cover changesin an area on the west coast of Pyeonganbuk-do where reclamation activities are underway. Unsupervised classification using the normalized difference water index and the random forest classification technique were each used to divide the study area into classification groups, and changes in their areas over time were analyzed. The resultsshow a clear decrease in the water area and a tendency to increase cultivated area,supporting the evidence that North Korea'sreclamation isfor agricultural land expansion.Along coasts behind seawalls, the water area decreased by nearly half, and the cultivated area increased by over 2,300%, indicating significant changes and highlighting the anthropogenic nature of the cover changes due to reclamation. Both methods demonstrated high accuracy, making them suitable for detecting cover changes caused by reclamation. It is expected that further quality research will be conducted through the use of high-resolution satellite images and by combining data from multiple satellites in the future.

• Journal of Korea Water Resources Association
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• v.38 no.5 s.154
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• pp.391-399
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• 2005

The purpose of this study is to evaluate hydrological impact by the land cover change of typhoon damage. For the typhoon RUSA (rainfall 1,402 mm) occurred in 2002 (August $31\;{\sim}$ September 1), satellite images of Landsat 7 ETM+ of September 29, 2000 and Landsat 5 TM of September 11, 2002 were selected, and each land cover was classified for Namdae-cheon watershed $192.7km^2$ located in the middle-eastern part of Korea Peninsula. SCS unit hydrograph for watershed runoff and Muskingum for streamflow routing of WMS HEC-1 was adopted. 30m resolution DEM & hydrological soil group using 1:50,000 soil map were prepared. The model was calibrated using three available data of storm events of 1985 to 1988 based on 1985 land cover condition. To predict the streamflow change by damaged land cover condition, rainfall of 50 years to 500 years frequency were generated using 2nd quantile of Huff method. The damaged land cover condition treated as bare soil surface increased streamflow of $50.1\;m^3/sec$ for 50 years rainfall frequency and $67.6\;m^3/sec$ for 500 years rainfall frequency based on AMC-I condition. There may be some speedy treatment by the government for the next coming typhoon damage.

• Korean Journal of Remote Sensing
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• v.36 no.5_4
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• pp.1179-1194
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• 2020

This study investigates the feasibility of three algorithms, K-Nearest Neighbors (K-NN), Random Forest (RF) and Neural Network (NN), for estimating the air temperature of an unobserved area where the weather station is not installed. The satellite image were obtained from Landsat-8 and MODIS Aqua/Terra acquired in 2019, and the meteorological ground weather data were from AWS/ASOS data of Korea Meteorological Administration and Korea Forest Service. In addition, in order to improve the estimation accuracy, a digital surface model, solar radiation, aspect and slope were used. The accuracy assessment of machine learning methods was performed by calculating the statistics of R² (determination coefficient) and Root Mean Square Error (RMSE) through 10-fold cross-validation and the estimated values were compared for each target area. As a result, the neural network algorithm showed the most stable result among the three algorithms with R² = 0.805 and RMSE = 0.508. The neural network algorithm was applied to each data set on Landsat imagery scene. It was possible to generate an mean air temperature map from June to September 2019 and confirmed that detailed air temperature information could be estimated. The result is expected to be utilized for national disaster safety management such as heat wave response policies and heat island mitigation research.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.4
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• pp.52-68
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• 2014

In this study, we investigated the seasonal variation of SST(Sea Surface Temperature) and thermal effluents estimated by using Landsat-7 ETM+ around the Kori Nuclear Power Plant for 10 years(2000~2010). Also, we analyzed the direction and range of thermal effluents dispersion by the tidal current and tide. The results are as follows, First, we figured out the algorithm to estimate SST through the linear regression analysis of Landsat DN(Digital Number) and NOAA SST. And then, the SST was verified by compared with the in situ measurement and NOAA SST. The determination coefficient is 0.97 and root mean square error is $1.05{\sim}1.24^{\circ}C$. Second, the SST distribution of Landsat-7 estimated by linear regression equation showed $12{\sim}13^{\circ}C$ in winter, $13{\sim}19^{\circ}C$ in spring, and $24{\sim}29^{\circ}C$ and $16{\sim}24^{\circ}C$ in summer and fall. The difference of between SST and thermal effluents temperature is $6{\sim}8^{\circ}C$ except for the summer season. The difference of SST is up to $2^{\circ}C$ in August. There is hardly any dispersion of thermal effluents in August. When it comes to the spread range of thermal effluents, the rise range of more than $1^{\circ}C$ in the sea surface temperature showed up to 7.56km from east to west and 8.43km from north to south. The maximum spread area was $11.65km^2$. It is expected that the findings of this study will be used as the foundational data for marine environment monitoring on the area around the nuclear power plant.