• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.383-392
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• 1993

Identification of rice paddy fields and estimation of their areas from the images taken by LANDSAT-5/TM were attempted. The results were verified by aerial photographs and also by ground observations. Changes of the spectral characteristics of rice plants were measured with a portable spectroradiometer during the growth period. Analyzing these characteristics, an index was developed for evaluating the growth and the yield of rice . Applying the index to the data observed by LANDSAT-5.TM on Sep. 26, 1986, Oct .20, 1989 and Sep, 21, 1990, it was confirmed that the estimated derived from the index agreed with actual values. The results well demonstrated its feasibility for evaluating the yield of rice by a satellite like LANDSAT-5/TM.

• International journal of advanced smart convergence
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• v.10 no.1
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• pp.216-224
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• 2021

Aim of this research was to classify forest types at Wando in Jeonnam Province and develop warm temperate forest management system with application of Remote Sensing and GIS. Another emphasis was given to the analysis of satellite images to compare forest type changes over 10 year periods from 2009 to 2019. We have accomplished this study by using ArcGIS Pro and ENVI. For this research, Landsat satellite images were obtained by means of terrestrial, airborne and satellite imagery. Based on the field survey data, all land uses and forest types were divided into 5 forest classes; Evergreen broad-leaved forest, Evergreen Coniferous forest, Deciduous broad-leaved forest, Mixed fores, and others. Supervised classification was carried out with a random forest classifier based on manually collected training polygons in ROI. Accuracy assessment of the different forest types and land-cover classifications was calculated based on the reference polygons. Comparison of forest changes over 10 year periods resulted in different vegetation biomass volumes, producing the loss of deciduous forests in 2019 probably due to the expansion of residential areas and rapid deforestation.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.22-24
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• 2007

Waterline extraction is the one of widely used methods for studying changes in tidal flat environment and coastlines using multi-temporal optical images such as Landsat TM and Landsat ETM+. High dynamics of tidal currents and land reclamation which accelerate sedimentation and/or erosion cause waterline change in tidal flats. The amount of sediment deposited or eroded can be evaluated by precisely estimating waterline changes in tidal flats. The objective of this study is to detect the change of waterlines during 17 years and analyze the trends of erosion and sedimentation in the study areas. The Ganghwado tidal flat on the west coast of the Korean Peninsula was selected. The study area is famous for high dynamics of tidal currents and vast tidal flats. Land reclamation which has been carried out on a large scale is also considered as one of elements that have accelerated the environmental changes in this tidal flat. In this study, we acquired 26 waterlines from Landsat TM and Landsat ETM+ images. We extracted the waterline from each satellite image to generate a digital elevation map (DEM) which was used for reference and to compare with the other waterline which was extracted from DEM having a same tide. The result of comparison well depicted the areas of dominant sedimentation and erosion, and general trends of sedimentation and erosion according to sub-regions are also revealed during the investigation time. Results showed that erosion during a decade was dominant at the west of the Southern Ganghwado tidal flat, while sedimentation was dominant at the wide channel between the Southern Ganghwado tidal flat and the Yeongjongdo tidal flat. This area has been commonly affected by high currents and sedimentation energy. Although we were not able to verify the accuracy of the waterline changes, this result clearly showed the waterline change and therefore, the waterline extraction method used in this study has proven as an effective tool for long term tidal change estimation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.4D
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• pp.569-577
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• 2008

The purpose of this study is focused on the development of compound classification process by mixing multitemporal data and annexing a specific image enhancement technique with a specific image classification algorithm, to gain more accurate land information from satellite imagery. That is, this study suggests the classification process using canonical correlation classification technique after principal component analysis for the mixed multitemporal data. The result of this proposed classification process is compared with the canonical correlation classification result of one date images, multitemporal imagery and a mixed image after principal component analysis for one date images. The satellite images which are used are the Landsat 5 TM images acquired on July 26, 1994 and September 1, 1996. Ground truth data for accuracy assessment is obtained from topographic map and aerial photograph, and all of the study area is used for accuracy assessment. The proposed compound classification process showed superior efficiency to appling canonical correlation classification technique for only one date image in classification accuracy by 8.2%. Especially, it was valid in classifying mixed urban area correctly. Conclusively, to improve the classification accuracy when extracting land cover information using Landsat TM image, appling canonical correlation classification technique after principal component analysis for multitemporal imagery is very useful.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.4
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• pp.3-11
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• 2016

Sixty four percent of Korean territory consists of forest which is fragile for forest fire. However, it is difficult to detect the disaster-induced damages due to topographic complexity in mountainous areas and harsh weather conditions. For this reason, satellite imaging systems have been widely utilized to detect the damage caused by forest fire. In particular, ground vegetation condition can be estimated from multi-spectral satellite images and change detection technique has been used to detect forest fire damages. However, since Korea has clear four seasons, simple change detection technique has limitation. In this regard, this study applied the NDVI(normalized difference vegetation index) annual cycle modeling technique on time-series of Landsat images from 1991 to 2007 to analyze influence of forest fire of Yangyang-gun, Gangwon-do in 2005 on vegetation condition. The encouraging result was obtained when comparing the areas where forest fire occurs with non-damaged areas. The mean value of NDVI was decreased by 0.07 before and after the forest fire. On the other hand, annual variability of NDVI had been increasing and peak value of NDVI was stationary after the forest fire. It is interpreted that understory vegetation was seriously damaged from the forest fire occurred in 2005.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.221-226
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• 2004

For comparing more than two images, the precise geometric corrections should be preceded because it necessary to eliminate systematic errors due to basic sensor information difference and non-systematic errors due to topographical undulations. In this study, we did sensor modeling using satellite sensor information to make a basic map of change detection for artificial topography. We eliminated the systematic errors which can be occurred in photographing conditions using GCP and DEM data. The Kompsat EOC images relief could be reduced by precise rectification method. Classifying images which was used for change detections by city and forest zone, the accuracy of the matching results are increased by 10% and the positioning accuracies also increased.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1464-1466
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• 2003

classification of the satellite images provides information about land cover and/or land use. Quality of the classification result depends mainly on the spatial and spectral resolutions of the images. In this study, image fusion in terms of resolution merging, and band integration with multi-source of the satellite images; Landsat ETM+ and Ikonos were carried out to improve classification. Resolution merging and band integration could generate imagery of high resolution with more spectral bands. Precise image co-registration is required to remove geometric distortion between different sources of images. Combination of unsupervised and supervised classification of the fused imagery was implemented to improve classification. 3D display of the results was possible by combining DEM with the classification result so that interpretability could be improved.

• 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.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.842-845
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• 2004

The aim of this study is to compare the classification results for choosing the fuzzy membership function within fuzzy rules. There are various methods of extracting rules from training data in the process of fuzzy rules generation. Pattern distribution characteristics are considered to produce fuzzy rules. The accuracy of classification results are depended on not only considering the characteristics of fuzzy subspaces but also choosing the fuzzy membership functions. This paper shows how to produce various type of fuzzy rules from the partitioning the pattern spaces and results of land cover classification in satellite remote sensing images by adopting various fuzzy membership functions. The experiments of this study is applied to Landsat TM image and the results of classification are compared by fuzzy membership functions.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.148-151
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• 2004

In this study the micro landform of tide flat in west Seohan bay. North Korea was classified and the change of this environment was detected by using Landsat TM. FTM+, KOMPAST. For this. ISODATA method of the unsupervised methods was used to classify the micro landform while tasseled cap method was used to detect the change of environment in west Seohan bay, North Korea by passing years. This study shows the possibility that the topography analysis and change especially in unapproachable area could be detected and monitored by using satellite images.