• Journal of the Korean Geophysical Society
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• v.5 no.1
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• pp.29-39
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• 2002

Geophysical data sets from the Chojeong area in the Chungbok-Do are compositely studied in terms of multi-attribute interpretations for the subsurface mappings of shallow fracture zones, associated with groundwater reservoir. Utilizing a GIS software, the attribute data were implemented to a database; a lineament from the satellite image, electrical resistivities and its standard deviation, radioactivity, seismic velocity, and bedrock depth. In an attempt to interpret 1-D electrical sounding data in 3-D views, 1-D data are firstly performed horizontal and vertical inter- and extrapolation. Reconstruction of a resistivity volume is found to be an effective scheme for subsurface mapping of shallow fracture zones. Shallow fracture zones are located in the southeastern part of the study area, which are commonly correlated with the various exploration data.

• Journal of the Korean earth science society
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• v.30 no.2
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• pp.196-209
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• 2009

Occurrences of sandstorms in the deserts and loess of Mongolia and northern China and associated dustfall episodes in the Korean Peninsula were monitored during the period January through December, 2005. False colour images were made by directly receiving the NOAA Advanced Very High Resolution Radiometer (AVHRR) data, and the distribution and transport of sandstorms were analyzed. The ground concentrations for PM10, PM2.5 and visibility of the dustfall episodes (PM10 concentration over $190{\mu}g\;m^{-3}$) were analyzed at Cheongwon, located midway in South Korea, and in the leeward direction of the place of origin of the sandstorms. Variations in the concentrations of $O_3,\;NO_2$, CO and $SO_2$ were also compared with dust concentrations in the dustfall episodes. Fewer occurrences of strong sandstorms in the place of origin were observed in 2005, due largely to the accumulation of snow and mild fluctuations of high and low pressure systems in the place of origin, thereby accounting for a low frequency of dustfall episodes in Korea, compared with those during the period 1997-2005. A total of 7 dustfall episodes were monitored in Korea in 2005 that lasted 11 days. In summer, sandstorms occurred less frequently in the source region in 2005 due to high humidity and milder winds, thereby causing no dustfall episodes in Korea. In case the sandstorms occurring at the place of source head directly to Korea without passing through large cities and industrial areas of China, the PM2.5 concentrations were measured at 20% or lower than the PM10 concentrations. However, when the sandstorms headed to Korea via the industrial areas of eastern China, where they pick up anthropogenic air pollutants, the PM2.5 concentrations were at least 25% higher of the PM10 concentrations. On the other hand, over 5 cases were observed and analyzed in 2005 where the PM10 concentrations of sand dust originating from the deserts were measured at $190{\mu}g\;m^{-3}$ or lower, falling short of the level of a dustfall episode.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1407-1419
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• 2020

Long time-series gridded data is crucial for the analyses of Earth environmental changes. Climate reanalysis and satellite images are now used as global-scale periodical and quantitative information for the atmosphere and land surface. This paper examines the feasibility of DCT-PLS (penalized least square regression based on discrete cosine transform) for the spatial gap filling of gridded data through the experiments for multiple variables. Because gap-free data is required for an objective comparison of original with gap-filled data, we used LDAPS (Local Data Assimilation and Prediction System) daily data and MODIS (Moderate Resolution Imaging Spectroradiometer) monthly products. In the experiments for relative humidity, wind speed, LST (land surface temperature), and NDVI (normalized difference vegetation index), we made sure that randomly generated gaps were retrieved very similar to the original data. The correlation coefficients were over 0.95 for the four variables. Because the DCT-PLS method does not require ancillary data and can refer to both spatial and temporal information with a fast computation, it can be applied to operative systems for satellite data processing.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.497-510
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• 2022

Agricultural reservoirs are essential structures for water supplies during dry period in the Korean peninsula, where water resources are temporally unequally distributed. For efficient water management, systematic and effective monitoring of medium-small reservoirs is required. Synthetic Aperture Radar (SAR) provides a way for continuous monitoring of those, with its capability of all-weather observation. This study aims to evaluate the applicability of SAR in monitoring medium-small reservoirs using Sentinel-1 (10 m resolution) and Capella X-SAR (1 m resolution), at Chari (CR), Galjeon (GJ), Dwitgol (DG) reservoirs located in Ulsan, Korea. Water detected results applying Z fuzzy function-based threshold (Z-thresh) and Chan-vese (CV), an object detection-based segmentation algorithm, are quantitatively evaluated using UAV-detected water boundary (UWB). Accuracy metrics from Z-thresh were 0.87, 0.89, 0.77 (at CR, GJ, DG, respectively) using Sentinel-1 and 0.78, 0.72, 0.81 using Capella, and improvements were observed when CV was applied (Sentinel-1: 0.94, 0.89, 0.84, Capella: 0.92, 0.89, 0.93). Boundaries of the waterbody detected from Capella agreed relatively well with UWB; however, false- and un-detections occurred from speckle noises, due to its high resolution. When masked with optical sensor-based supplementary images, improvements up to 13% were observed. More effective water resource management is expected to be possible with continuous monitoring of available water quantity, when more accurate and precise SAR-based water detection technique is developed.

• Korean Journal of Remote Sensing
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• v.29 no.5
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• pp.517-525
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• 2013

Time-series data of Normal Difference Vegetation Index (NDVI) obtained by the Moderate-resolution Imaging Spectroradiometer(MODIS) satellite imagery gives a waveform that reveals the characteristics of the phenology. The waveform can be decomposed into harmonics of various periods by the Fourier transformation. The resulting $n^{th}$ harmonics represent the amount of NDVI change in a period of a year divided by n. The values of each harmonics or their relative relation have been used to classify the vegetation species and to build a vegetation map. Here, we propose a method to estimate the annual amount of carbon absorbed on the forest from the $1^{st}$ harmonic NDVI value. The $1^{st}$ harmonic value represents the amount of growth of the leaves. By the allometric equation of trees, the growth of leaves can be considered to be proportional to the total amount of carbon absorption. We compared the $1^{st}$ harmonic NDVI values of the 6220 sample points with the reference data of the carbon absorption obtained by the field survey in the forest of South Korea. The $1^{st}$ harmonic values were roughly proportional to the amount of carbon absorption irrespective of the species and ages of the vegetation. The resulting proportionality constant between the carbon absorption and the $1^{st}$ harmonic value was 236 tCO2/5.29ha/year. The total amount of carbon dioxide absorption in the forest of South Korea over the last ten years has been estimated to be about 56 million ton, and this coincides with the previous reports obtained by other methods. Considering that the amount of the carbon absorption becomes a kind of currency like carbon credit, our method is very useful due to its generality.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1413-1425
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• 2023

The increasing frequency of wildfires due to climate change is causing extreme loss of life and property. They cause loss of vegetation and affect ecosystem changes depending on their intensity and occurrence. Ecosystem changes, in turn, affect wildfire occurrence, causing secondary damage. Thus, accurate estimation of the areas affected by wildfires is fundamental. Satellite remote sensing is used for forest fire detection because it can rapidly acquire topographic and meteorological information about the affected area after forest fires. In addition, deep learning algorithms such as convolutional neural networks (CNN) and transformer models show high performance for more accurate monitoring of fire-burnt regions. To date, the application of deep learning models has been limited, and there is a scarcity of reports providing quantitative performance evaluations for practical field utilization. Hence, this study emphasizes a comparative analysis, exploring performance enhancements achieved through both model selection and data design. This study examined deep learning models for detecting wildfire-damaged areas using Landsat 8 satellite images in California. Also, we conducted a comprehensive comparison and analysis of the detection performance of multiple models, such as U-Net and High-Resolution Network-Object Contextual Representation (HRNet-OCR). Wildfire-related spectral indices such as normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as input channels for the deep learning models to reflect the degree of vegetation cover and surface moisture content. As a result, the mean intersection over union (mIoU) was 0.831 for U-Net and 0.848 for HRNet-OCR, showing high segmentation performance. The inclusion of spectral indices alongside the base wavelength bands resulted in increased metric values for all combinations, affirming that the augmentation of input data with spectral indices contributes to the refinement of pixels. This study can be applied to other satellite images to build a recovery strategy for fire-burnt areas.

• Journal of the Korean association of regional geographers
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• v.9 no.2
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• pp.203-216
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• 2003

The process of constructing coastal digital elevation model(DEM), for the 3 dimensional analysis, is composed by abstracting land layers for land elevation and water depth, reprojecting UTM, relocating geographical grid, and interpolating works. The geomorphic set of shallow sea, including tidal current, tidal zone deposition, and water depth distribution, was analyzed by eye search of Landsat TM image, masking of land zone, band combination and regression analysis. Some horizontal differences, between combined DEM and surveyed data of shallow sea, was corrected for analysis. Analyzed geomorphic elements are stream channel, alluvial fan, coastal terrace, tidal current. and shallow sea bank. Results of analysis present that transported fluvial materials influence tidal sedimentation, especially from Gahwacheon river, for the role of artificial draining flooding waters from Jinyang Reservoir, almost in the summer season. In the coastal area with less tidal current, more fine materials are deposited. The influence of currental deposition are higher on small pockets with west coast of well developed terraces. The lower skirt of alluvial fans developed into the tidal zone of shallow sea. Small pocket type bays are closed by coastal current, and less influenced from tidal deposition. The bank of Jinju Bay are developed originally from submerging of remnant erosional mountain ranges, and play on the role of trapping fine materials.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.571-585
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• 2022

As the threat of natural disasters such as droughts, floods, forest fires, and landslides increases due to climate change, social demand for high-resolution soil moisture retrieval, such as Synthetic Aperture Radar (SAR), is also increasing. However, the domestic environment has a high proportion of mountainous topography, making it challenging to retrieve soil moisture from SAR data. This study evaluated the usability of Sentinel-1 SAR, which is applied with the Artificial Neural Network (ANN) technique, to retrieve soil moisture. It was confirmed that the backscattering coefficient obtained from Sentinel-1 significantly correlated with soil moisture behavior, and the possibility of stand-alone use to correct vegetation effects without using auxiliary data observed from other satellites or observatories. However, there was a large difference in the characteristics of each site and topographic group. In particular, when the model learned on the mountain and at flat land cross-applied, the soil moisture could not be properly simulated. In addition, when the number of learning points was increased to solve this problem, the soil moisture retrieval model was smoothed. As a result, the overall correlation coefficient of all sites improved, but errors at individual sites gradually increased. Therefore, systematic research must be conducted in order to widely apply high-resolution SAR soil moisture data. It is expected that it can be effectively used in various fields if the scope of learning sites and application targets are specifically limited.

• Journal of Korea Water Resources Association
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• v.54 no.7
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• pp.535-544
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• 2021

Agricultural water occupies 48% of water demand, and management of agricultural reservoirs is essential for water resources management within agricultural basins. For more efficient use of agricultural water, monitoring the distribution of water resources in agricultural reservoirs and agricultural basins is required. Therefore, in this study, three threshold determination methods (i.e., fixed threshold, Otsu threshold, Kittler-Illingworth (KI) threshold) were compared to detect terrestrial water bodies using Sentinel-1 images for 3 years from 2018 to 2020. The purpose of this study was to evaluate methods for determining threshold values to more accurately estimate the reservoir area. In addition, by analyzing the relationship between the water surface and water storage at the Edong, Gosam, and Giheung reservoirs, water storage based on the SAR image was estimated and validated with observations. The thresholding method for detecting a waterbody was found to be the most accurate in the case of the KI threshold, and the water storage estimated by the KI threshold indicated a very high agreement (r = 0.9235, KGE' = 0.8691). Although the seasonal error characteristics were not observed, the problem of underestimation at high water levels may occur; the relationship between the water surface and the water storage could change rapidly. Therefore, it is necessary to understand the relationship between the water surface area and water storage through ground observation data for a more accurate estimation of water storage. If the use of SAR data through water resources satellites becomes possible in the future, based on the results of this study, it is judged that it will be beneficial for monitoring water storage and managing drought.

• Journal of the Korean earth science society
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• v.42 no.3
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• pp.264-277
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• 2021

This study analyzed the relationship between the total precipitable water vapor in the atmosphere and the moving speed of recent typhoons. This study used ground observation data of air temperature, precipitation, and wind speed from the Korea Meteorological Administration (KMA) as well as total rainfall data and Red-Green-Blue (RGB) composite images from the U.S. Meteorological and Satellite Research Institute and the KMA's Cheollian Satellite 2A (GEO-KOMPSAT-2A). Using the typhoon location and moving speed data provided by the KMA, we compared the moving speeds of typhoon Bavi, Maysak, and Haishen from 2020, typhoon Tapah from 2019, and typhoon Kong-rey from 2018 with the average typhoon speed by latitude. Tapah and Kong-rey moved at average speed with changing latitude, while Bavi and Maysak showed a significant decrease in moving speed between approximately 25°N and 30°N. This is because a water vapor band in the atmosphere in front of these two typhoons induced frontogenesis and prevented their movement. In other words, when the water vapor band generated by the low-level jet causes frontogenesis in front of the moving typhoon, the high pressure area located between the site of frontogenesis and the typhoon develops further, inducing as a blocking effect. Together with the tropical night phenomenon, this slows the typhoon. Bavi and Maysak were accompanied by copious atmospheric water vapor; consequently, a water vapor band along the low-level jet induced frontogenesis. Then, the downdraft of the high pressure between the frontogenesis and the typhoon caused the tropical night phenomenon. Finally, strong winds and heavy rains occurred in succession once the typhoon landed.