• Ocean and Polar Research
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• v.32 no.1
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• pp.53-61
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• 2010

The distribution of coral reefs can be an indicator of environmental or anthropogenic impacts. Here, we present a habitat map of coral reefs developed using high-spatial satellite images. The study area was located on the north-eastern part of Weno island, in the Chuuk lagoon of Federated States of Micronesia. Two fieldwork expeditions were carried out between 2007 and 2008 to acquire optical and environmental data from 121 stations. We used an IKONOS image obtained in December 2000, and a Kompsat-2 image obtained in September 2008 for the purpose of coral reef mapping. We employed an adapted version of the object-based classification method for efficient classification of the high-spatial satellite images. The habitat map generated using Kompsat-2 was 72.22% accurate in terms of comparative analysis with in-situ measurements. The result of change detection analysis between 2000 and 2008 showed that coral reef distribution had decreased by 6.27% while seagrass meadows had increased by 8.0%.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.6
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• pp.81-92
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• 2019

The objective of this study is to evaluate hydrologic impacts of climate change according to downscaling methods using the Soil and Water Assessment Tool (SWAT) model at watershed scale. We used the APCC Integrated Modeling Solution (AIMS) for assessing various General Circulation Models (GCMs) and downscaling methods. AIMS provides three downscaling methods: 1) BCSA (Bias-Correction & Stochastic Analogue), 2) Simple Quantile Mapping (SQM), 3) SDQDM (Spatial Disaggregation and Quantile Delta Mapping). To assess future hydrologic responses of climate change, we adopted three GCMs: CESM1-BGC for flood, MIROC-ESM for drought, and HadGEM2-AO for Korea Meteorological Administration (KMA) national standard scenario. Combined nine climate change scenarios were assessed by Expert Team on Climate Change Detection and Indices (ETCCDI). SWAT model was established at the Mankyung watershed and the applicability assessment was completed by performing calibration and validation from 2008 to 2017. Historical reproducibility results from BCSA, SQM, SDQDM of three GCMs show different patterns on annual precipitation, maximum temperature, and four selected ETCCDI. BCSA and SQM showed high historical reproducibility compared with the observed data, however SDQDM was underestimated, possibly due to the uncertainty of future climate data. Future hydrologic responses presented greater variability in SQM and relatively less variability in BCSA and SDQDM. This study implies that reasonable selection of GCMs and downscaling methods considering research objective is important and necessary to minimize uncertainty of climate change scenarios.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.2
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• pp.79-86
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• 2010

Generally, image fusion is defined as generating re-organized image by merging two or more data using special algorithms. In remote sensing, image fusion technique is called as Pan-sharpening algorithm because it aims to improve the spatial resolution of original multispectral image by using panchromatic image of high-spatial resolution. The pan-sharpened image has been an important task due to various applications such as change detection, digital map creation and urban analysis. However, most approaches have tended to distort the spectral information of the original multispectral data or decrease the spatial quality compared with the panchromatic image. In order to solve these problems, a novel pan-sharpening algorithm is proposed by considering the spectral and spatial characteristics of multispectral image. The algorithm is applied to the KOMPSAT-2 and QuickBird satellite image and the results showed that our method can improve the spectral/spatial quality compared with the existing fusion algorithms.

• Journal of Fisheries and Marine Sciences Education
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• v.24 no.2
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• pp.333-345
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• 2012

NOAA/AVHRR, Topex/Poseidon, and Jason-1 data were used to analyze sea surface temperatures and thermal fronts in the North East Asia Seas. Temporal and spatial analyses were based on data from 1993 to 2008. The amplitude and phase for the annual mode on SL and SST were investigated with harmonic analysis. The geographical distribution of amplitudes for comparison of SL and SST are slightly reverse in southwest-northeast tilted direction. The time series analysis conducted on the entire researched area presented consistent pattern. Peak of Sea Level was presented 1~2 months after the peak of the surface sea temperature was shown. This explains that Sea Level change occurs after the generation of surface sea temperature change in sea. The Sobel edge detection method delineated four fronts. Thermal fronts generally occurred over steep bathymetric slopes. Annual amplitudes and phases were bounded within these frontal areas.

• Journal of Cadastre & Land InformatiX
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• v.53 no.1
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• pp.107-121
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• 2023

In order to acquire a wide range of land that changes in real time and quickly and accurately grasp it, we plan to utilize the recently released high-resolution S.Korea's satellite image data and artificial intelligence (AI). Compared to existing satellite images, the spectral and periodic resolutions of S.Korea's satellite are higher, making them a more suitable data source for periodically monitoring changes in land. Therefore, this study aims to acquire S.Korea's satellite, select 8 types of objects to detect land changes, construct data sets for them, and apply AI models to analyze them. In order to confirm the optimal model and variable conditions for detecting 8 types of objects of various types, several experiments are performed and AI-based image analysis is technically reviewed.

• Journal of the Korean Association of Geographic Information Studies
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• v.2 no.1
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• pp.73-83
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• 1999

The land use/cover information, which is periodically obtained from satellite imagery, can be effectively applied to change detection in rapidly changing urban areas. Also it can be used not only as base maps for spatial database in urban information system but as decision-making data for desired urban planning and development direction. In this study, we carried out both unsupervised and supervised classification on land use from Landsat TM and JERS-1 OPS data, which were collected respectively in 1991 and 1997, covering Kumi City and then detected land use changes.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.4
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• pp.224-232
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• 2006

This study investigates to detect Sea Surface Temperature (SST) and land cover change after tide embankment construction using Landsat Thematic Mapper (TM) Thermal Infrared (TIR) band data at Shihwa Lake and surrounding area. SST measurement is important for studies of both the structure of the ocean and as the thermal boundary between the ocean and the atmosphere. Since 1970s, the derivation of SST by satellite remote sensing (RS) has been applied to earth surface using Advanced Very High Resolution Radiometer (AVHRR) and Landsat TM. However, AVHRR has restriction in deriving SST in the area whose shoreline is complicated like western coast in South Korea because of coarse spatial resolution. The TIR band of TM images can be used to detect SST change whose shoreline is complicated and narrow like the study site. Thus, multi-temporal TM images were used for SST change detection in this study.

• Spatial Information Research
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• v.15 no.1
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• pp.25-33
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• 2007

The purpose of this study is to assess spatio-temporal variation of Imha Dam water quality according to suspended sediment algorithm using Landsat and SPOT 5 data. In order to learn synchronous suspended sediment concentrations(SSC) in Imha Dam waters, the satellite remote sensing data are analyzed. The key procedure of this research is that we should know the relationships between suspended sediment concentrations and satellite-detected reflectance. However, the SSC algorithm has the limitation that it must be compared calculated SSC with synchronous ground-truth data in the Dam water. Based upon the linear response from satellite-detected reflectance, SSC algorithm validated an efficient algorithm to estimate proportional factor and then derived an empirical equation far SSC estimations.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.509-511
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• 2004

This paper outlines the development of image processing system, which will allow the general users in Government and Public organizations easily to use and apply KOMPSAT EOC images in their own business. The system includes an import/export module of EOC image distributed in Hierarchical Data Format (HDF) file and various image processing analysis modules. Especially, the image mosaic and subset functions are designed to use EOC image as an image map, generating the Ortho-image module. To update the various spatial data with EOC image, some essential modules such as change detection by pattern recognition, overlay between images and vector data, and modification of vector data are implemented in the system. The system is developed based on the user request analysis of government agency, and suited for more efficient use of satellite image in public applications. Such system is expected to contribute to practical application of KOMPSAT-2 that will be launched in 2005. Further efforts will be made to accommodate the KOMPSAT -2 MSC data.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.493-502
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• 2021

Recently, because of changes in temperature and rising water temperatures due to increased pollution sources, many algae have been produced in the water system. Therefore, there has been a lot of research using satellite images for the generation and monitoring of green algae. However, in prior studies, it is difficult to consider the optical properties of the local water system by using only a single index, and by using medium and low-resolution satellite images to conduct large-scale algae detection, there is a problem of accuracy in narrow, broad rivers. Therefore, in this work, we utilize high-resolution images of Sentinel-2 satellites to perform green algae detection on a single index (NDVI, SEI, FGAI) and development index (NDVI & SEI, FGAI & SEI) that mixes single indices. In this study, POD, FAR, and PC values were utilized to evaluate the accuracy of green algae detection algorithms, and the FGAI & SEI index showed the highest accuracy with 98.29% overall accuracy PC.