• Korean Journal of Remote Sensing
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• v.26 no.5
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• pp.571-580
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• 2010

Coastal shoreline movement due to erosion and deposition is a major concern for coastal zone management. Shoreline is changed by nature factor or development of coastal. Change of shoreline is threatening marine environment and destroying. Therefore, we need monitoring of shoreline change with time series analysis for coastal zone management. In this study, we analyzed the shoreline change using airphotograph, LiDAR and satellite imagery from 1971 to 2009 in Uljin, Gyeongbuk, Korea. As a result, shoreline near of the nuclear power plant show linear pattern in 1971 and 1980, however the pattern of shoreline is changed after 2000. As a result of long-term monitoring, shoreline pattern near of the nuclear power plant is changed by erosion toward sea. The pattern of shoreline near of KORDI until 2003 is changed due to deposition toward sea, but the new pattern toward land is developed by erosion from 2003 to 2009. The shoreline is changed by many factors. However, we will guess that change of shoreline within study area is due to construction of nuclear power plant. In the future work, we need sedimentary and physical studies.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.871-884
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• 2021

The purpose of this study was to determine ways to increase efficiency in constructing and verifying artificial intelligence learning data on land cover using aerial and satellite images, and in applying the data to AI learning algorithms. To this end, multi-resolution datasets of 0.51 m and 10 m each for 8 categories of land cover were constructed using high-resolution aerial images and satellite images obtained from Sentinel-2 satellites. Furthermore, fine data (a total of 17,000 pieces) and coarse data (a total of 33,000 pieces) were simultaneously constructed to achieve the following two goals: precise detection of land cover changes and the establishment of large-scale learning datasets. To secure the accuracy of the learning data, the verification was performed in three steps, which included data refining, annotation, and sampling. The learning data that wasfinally verified was applied to the semantic segmentation algorithms U-Net and DeeplabV3+, and the results were analyzed. Based on the analysis, the average accuracy for land cover based on aerial imagery was 77.8% for U-Net and 76.3% for Deeplab V3+, while for land cover based on satellite imagery it was 91.4% for U-Net and 85.8% for Deeplab V3+. The artificial intelligence learning datasets on land cover constructed using high-resolution aerial and satellite images in this study can be used as reference data to help classify land cover and identify relevant changes. Therefore, it is expected that this study's findings can be used in the future in various fields of artificial intelligence studying land cover in constructing an artificial intelligence learning dataset on land cover of the whole of Korea.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.3
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• pp.137-147
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• 2012

Recently, floating green algae (FGA) in open oceans and coastal waters have been reported over wide area, yet accurate detection of these using traditional ground based measurement and chemical analysis in the laboratory has been difficult or even impossible due to the lack of spatial resolution, coverage, and revisit frequency. In contrast, spectral reflectance measurement makes it possible to quickly assess the chlorophyll content in green algae. Our objectives are to investigate the spectral reflectance of the FGA observed in the Yellow Sea and to develop a new index to detect FGA from satellite imagery, namely floating green algae index (FGAI), which uses relatively simple reflectance ratio technique. The Moderate Resolution Imaging Spectroradiometer (MODIS) and Geostationary Ocean Color Imager (GOCI) satellite images at 500m spatial resolution were utilized to produce FGAI which is defined as the ratio between reflectance at 860nm and 660nm bands. Both FGAI results yielded reasonable green algae detection at the regional scale distribution. Especially houly GOCI observations can present more detaield information of FGAI than low-orbit satellite.

• Korean Journal of Remote Sensing
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• v.37 no.6_3
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• pp.1923-1929
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• 2021

Earth observation satellites are being used in various field and are being developed in many countries due to their high utility and marketability. Korea is developing various Earth observation satellites according to National Space Development Plan. Among them, the Korea Multi-Purpose Satellite(KOMPSAT) series is the most representative low-orbit satellite. So far, a total of five KOMPSAT have been launched to meet the national image demand and have been used in various fields, including national institutions. This special issue introduces research related to data processing, analysis, and utilization using various image data from the KOMPSAT series. Meanwhile, for the uninterrupted utilization of the subsequent KOMPSAT image data, data processing and utilization research suitable for high-resolution images must be continued, and related research contents will be continuously shared through a special issue.

• Korean Journal of Remote Sensing
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• v.14 no.4
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• pp.376-391
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• 1998

Images from satellites will have 1 to 3 meter ground resolution and will be very useful for analyzing current status of earth surface. An image processing system named GeoWatch with more intelligent image processing algorithms has been designed and implemented to support the detailed analysis of the land surface using high-resolution satellite imagery. The GeoWatch is a valuable tool for satellite image processing such as digitizing, geometric correction using ground control points, interactive enhancement, various transforms, arithmetic operations, calculating vegetation indices. It can be used for investigating various facts such as the change detection, land cover classification, capacity estimation of the industrial complex, urban information extraction, etc. using more intelligent analysis method with a variety of visual techniques. The strong points of this system are flexible algorithm-save-method for efficient handling of large size images (e.g. full scenes), automatic menu generation and powerful visual programming environment. Most of the existing image processing systems use general graphic user interfaces. In this paper we adopted visual program language for remotely sensed image processing for its powerful programmability and ease of use. This system is an integrated raster/vector analysis system and equipped with many useful functions such as vector overlay, flight simulation, 3D display, and object modeling techniques, etc. In addition to the modules for image and digital signal processing, the system provides many other utilities such as a toolbox and an interactive image editor. This paper also presents several cases of image analysis methods with AI (Artificial Intelligent) technique and design concept for visual programming environment.

• Korean Journal of Remote Sensing
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• v.39 no.5_2
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• pp.743-754
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• 2023

The global occurrence of myriad natural disasters and incidents, catalyzed by climate change and extreme meteorological conditions, has engendered substantial human and material losses. International organizations such as the International Charter have established an enduring collaborative framework for real-time coordination to provide high-resolution satellite imagery and geospatial information. These resources are instrumental in the management of large-scale disaster scenarios and the expeditious execution of recovery operations. At the national level, the operational deployment of advanced National Earth Observation Satellites, controlled by National Geographic Information Institute, has not only catalyzed the advancement of geospatial data but has also contributed to the provisioning of damage analysis data for significant domestic and international disaster events. This special edition of the National Disaster Management Research Institute delineates the contemporary landscape of major disaster incidents in the year 2023 and elucidates the strategic blueprint of the government's national disaster safety system reform. Additionally, it encapsulates the most recent research accomplishments in the domains of artificial satellite systems, information and communication technology, and spatial information utilization, which are paramount in the institution's disaster situation management and analysis efforts. Furthermore, the publication encompasses the most recent research findings relevant to data collection, processing, and analysis pertaining to disaster cause and damage extent. These findings are especially pertinent to the institute's on-site investigation initiatives and are informed by cutting-edge technologies, including drone-based mapping and LiDAR observation, as evidenced by a case study involving the 2023 landslide damage resulting from concentrated heavy rainfall.

• Korean Journal of Geomatics
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• v.3 no.2
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• pp.81-86
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• 2004

In recent years, the importance of geospatial data have been emphasized not only for the national GIS programs and but also in the value added commercial and industry markets. There is no doubt that GIS, GPS, aerial and satellite imagery data were provided powerful tools to support national information infrastructure for geospatial database. While great emphasis has been laid on the geospatial data, there has been little analysis or evaluation of how to maximize the benefits of using these information sources. Also, with the proliferation of geographic data and information sources such as satellite imagery, digital aerial photograph, digital topographic and vector data, there is a great need to inform professionals from all disciplines as to the benefits of these information sources and how to best put them to use within any given application. From the first publication of KSGPC(Korean Society of Geodesy, Photogrammetry and Cartography) papers in 1981, our objective was, and is, to help develop the wider spectrum of GIS in the academy and industry by exposing new users to the benefits of GIS, remote sensing, mapping, GPS and photogrammetry. In this presentation, we will introduce KSGPC works and will evaluate GIS-related governmental policies and programs in Korea for the past and the future to present different status between Korea and Russia. It is now important to investigate lessons learnt from two countries' experiences and developed an empirical framework to combine outcome from GIS-related researches in Korea and Russia. This may enable GIS professionals to gain a wider range of experiences in the international context, and consequently, help them to develop new markets for GIS. Therefore, we arranged the possible action items and interesting points to corporate and to promote the academic growth in the practice of GIS.

• Proceedings of the Korea Contents Association Conference
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• 2008.05a
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• pp.897-901
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• 2008

The objective of this study is to conduct land cover classification respectively using Landsat TM data collected on Oct., 1985 and KOMPSAT-1 EOC data collected on Jan., 2000 covering Gumi city, Gyeongbuk Province and to detect urban change by comparing between both land cover maps. Multispectral images of Landsat TM have spatial resolution of 30m are well known as useful data for extracting information related to landcover, vegetation classification, urban growth analysis and so forth. In contrast, as KOMPSAT-1 EOC collects panchromatic images with relatively high spatial resolution of 6.6m. We try to analyze how accurate landcover classification result is able to be derived from the panchromatic images. As the results of the study, the KOMPSAT EOC data with high resolution greater than 4 times showed higher classification degree than Landsat TM data. It was ascertained that the built-up region was extended by three to four times in the last 15 years between 1985 and 2000. In the contrast, it was shown that the forest region was decreased by 15% to 27% and the grass region including agricultural region was decreased by 28% to 45%.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.02a
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• pp.16-21
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• 2004

In recent years, the importance of geospatial data have been emphasized not only for the national GIS programs and but also in the value added commercial and industry markets. There is no doubt that GIS, GPS, aerial and satellite imagery data were provided powerful tools to support national information infrastructure for geospatial database. While great emphasis has been laid on the geospatial data, there has been little analysis or evaluation of how to maximize the benefits of using these information sources. Also, with the proliferation of geographic data and information sources such as satellite imagery, digital aerial photography, digital topographic and vector data, there is a great need to inform professionals from all disciplines as to the benefits of these information sources and how to best put them to use within any given application. From the first publication of KSGPC(Korean Society of Geodesy, Photogrammetry and Cartography) papers in 1981, our objective was, and is, to help develop the wider spectrum of GIS in the academy and industry by exposing new users to the benefits of GIS, remote sensing, mapping, GPS and photogrammetry. In this presentation, we will introduce KSGPC works and will evaluate GIS-related governmental policies and programs in Korea for the past and the future to present different status between Korea and Russia. It is now important to investigate lessons learnt from two countries' experiences and developed an empirical framework to combine outcomes from GIS-related researches in Korea and Russia. This may enable GIS professionals to gain a wider range of experiences in the international context, and consequently, help them to develop new markets for GIS. Therefore, we arranged the possible action items and interesting points to corporate and to promote the academic growth in the practice of GIS.

• Korean Journal of Remote Sensing
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• v.4 no.1
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• pp.31-40
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• 1988

Low-cost microcomputer systems can be assembled which possess computing power, color display, memory, and storage capacity approximately equal to graphic workstactions. A low-cost, flexible, and user-friendly IBM/PC/XT/AT based image processing system has been developed and named as KMIPS(KAIST (Korea Advanced Institute of Science & Technology) Map and Image Processing Station). It can be easily utilized by the resource managers who are not computer specialists. This system can: * directly access Landsat MSS and TM, SPOT, NOAA AVHRR, MOS-1 satellite imagery and other imagery from different sources via magnetic tape drive connected with IBM/PC; * extract image up to 1024 line by 1024 column and display it up to 480 line by 672 column with 512 colors simultaneously available; * digitize photographs using a frame grabber subsystem(512 by 512 picture elements); * perform a variety of image analyses, GIS and terrain analyses, and display functions; and * generate map and hard copies to the various scales. All raster data input to the microcomputer system is geographically referenced to the topographic map series in any rater cell size selected by the user. This map oriented, georeferenced approach of this system enables user to create a very accurately registered(.+-.1 picture element), multivariable, multitemporal data sets which can be subsequently subsequently subjected to various analyses and display functions.