• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.3
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• pp.219-225
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• 2008

There are many problems in monitering environmental change around of nuclear power station, because interesting area is coastal and relatively large. The ground resolution of Landsat ETM+ imagery is high (30 m), but this imagery does not have enough informations for conducting atmospheric correction in evaluating sea surface temperatures. On the other hand, while it is possible to conduct atmospheric correction using MODIS imagery with it's two infrared bands, it's resolution is relatively low (1 km). Therefore, atmospheric corrected high resolution temperature information can be obtained from these two satellite images. In this study, digital numbers of Landsat ETM+ data in interesting area are georeferenced, converted to effective temperatures based on radiance value, and then the atmospheric correction is conducted using MODIS data. As a result, about $3.5^{\circ}C$ temperature differences were detected in comparing sea surface temperature of the surrounding area of Uljin nuclear power station with it of the same area located 5km far east.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.274-277
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• 2007

This study is to estimate the spatial distribution of soil loss using the land use data produced from QuickBird satellite imagery. For a small agricultural watershed (1.16 $km^2$) located in the upstream of Gyeongan-cheon watershed, a precise agricultural land use map were prepared using QuickBird satellite image of April 5 of 2003. RUSLE (Revised Universal Soil Loss Equation) was adopted for soil loss estimation. The data (DEM, soil and land use) for the RUSLE were prepared for 5 m and 30 m spatial resolution. The results were compared with each other and the result of 30 m Landsat land use data.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.2
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• pp.197-206
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• 2010

Recently, developed countries have continuously been trying to recognize many issues about heat island in urban area and to make up countermeasures for them. This research is designed to extract change of land cover in the area under condition of land development with satellite images and to analyze its effect on the heat change in there. Heat change upon change of land cover in daejeon was analyzed with the four Landsat satellite images taken in April 1985, August 1994, May 2001, and May 2009. In order to measure the temperature on the surface in the city, the land surface temperature was produced with Landsat TM Band 6. Heat change is to detected with it. As a result, The urban area has been increased up to 23.59 percent. On the other hand, the forest area has been decreased up to 27.91%. Due to the urbanization, the temperature on the surface in urban center was higher than surrounding area. In that case, the temperature of urban center area was higher 2.4 to $5.7^{\circ}C$ compared with the forest area.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.53 no.4
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• pp.388-393
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• 2008

Earth observation satellite imagery having medium-resolution can provide the useful information very rapidly and cheaply. The objective of this study was to assess the feasibility for monitoring rice growth and yield using medium resolution satellite imagery at Seosan AB reclaimed area, Chung-nam province. Using the LANDSAT imagery at booting stage ($29^{th}$ July 2004), $NDVI_R$ had the most significant linear relationships with rice yield of Seosan AB reclaimed area with the correlation coefficient (r) as 0.68. Therefore, this relationship was established as rice yield equation as function of $NDVI_R$, where excluding the 10 small area having low number of pixel, the determination coefficient ($R^2$) of the linear regression between NDVIred and milled rice yield was improved to 0.66. In addition, raster masking method, which was easier and faster even if a little unaccurate than preexisting method, was established for extracting information paddy field zone. Adaptability of rice yield equation function of $NDVI_R$ on year and region was investigated using rice yield and $NDVI_R$ values, which were extracted with raster masking method, from 7 counties or cities, Kyeong-ki province in 2005. Relationship between observed and calculated rice yield showed 1:1 line indicating that the adaptability was admitted.

• Korean Journal of Remote Sensing
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• v.33 no.4
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• pp.411-422
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• 2017

This research aims to analyze spectral reflectance of intertidal zone and its changes under various environmental conditions. We sampled sand of Mongsanpo tidal flat, Korea, and measured its spectral reflectance by using a spectroradiometer under various water contents, compositions and granularity. We also simulated the reflectance of Landsat 7 ETM+ and compared it with an actual satellite data. Five locations were selected for sampling from the coastline towards the ocean. Grain size diminished stepwise from the coastline to ocean direction, while spectral reflectance differed with wavelength. Water contents lowered the overall reflectance especially at the water absorption bands. Spectral reflectance data were then converted into the simulated one by using Landsat 7 ETM+ spectral reflectance function to be compared with the actual Landsat 7 ETM+ images. It showed the decrease of the spectral reflectance due to the increase of moisture contents from seashore towards the ocean. It is shown that Landsat 7 ETM+ imagery can be efficient to extract moisture contents in the tidal flat while compositional analysis needs satellite sensors with much higher spectral resolution.

• Korean Journal of Remote Sensing
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• v.18 no.3
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• pp.141-146
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• 2002

Chlorophyll-a concentration maps of Yongdam reservoir in September and October, 2001 were produced using Landsat ETM imagery and the in-situ water quality measurement data. In-situ water samples were collected on 16th September and 18th October during the satellite overpass. The correlations between the DN values of the imagery and the values of chlorophyll-a concentration were analyzed. The visible bands(band 1, 2, 3) and the near infrared band(band 4) data of September image showed the correlation coefficient values higher than 0.9. The October image showed correlation coefficient values of about 0.7 due to the low variations of chlorophyll-a concentration. Regression models between the DN values of the Landsat ETM image and the chlorophyll-a concentration have been developed for each image. The developed regression models were then applied to each image, and finally the chlorophyll-a distribution maps of Yongdam reservoir were produced. The produced maps showed the spatial distribution of the chlorophyll-a in Yongdam reservoir in a synoptic way so that the tropic state could be easily monitored and analysed in the spatial domain.

• 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.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1231-1244
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• 2022

The frequency of exposure of field crops to stress situations is increasing due to abnormal weather conditions. In South Korea, large-scale diseases in representative paddy rice cultivation area were happened. There are limits to field investigation on the crop damage due to large-scale. Satellite-based remote sensing techniques are useful for monitoring crops in cities and counties, but the sensitivity of vegetation index measured from satellite under abnormal growth of crop should be evaluated. The goal is to evaluate satellite-based normalized difference vegetation index (NDVI) retrieved from different spatial scales using drone imagery. In this study, Sentinel-2 and Landsat-8 satellites were used and they have spatial resolution of 10 and 30 m. Drone-based NDVI, which was resampled to the scale of satellite data, had correlation of 0.867-0.940 with Sentinel-2 NDVI and of 0.813-0.934 with Landsat-8 NDVI. When the effects of bias were minimized, Sentinel-2 NDVI had a normalized root mean square error of 0.2 to 2.8% less than that of the drone NDVI compared to Landsat-8 NDVI. In addition, Sentinel-2 NDVI had the constant error values regardless of diseases damage. On the other hand, Landsat-8 NDVI had different error values depending on degree of diseases. Considering the large error at the boundary of agricultural field, high spatial resolution data is more effective in monitoring crops.

• Korean Journal of Remote Sensing
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• v.20 no.4
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• pp.253-259
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• 2004

The purpose of this study is to present a standardized scheme for providing agriculture-related information at various spatial resolutions of satellite images including Landsat + ETM, KOMPSAT-1 EOC, ASTER VNIR, and IKONOS panchromatic and multi-spectral images. The satellite images were interpreted especially for identifying agricultural areas, crop types, agricultural facilities and structures. The results were compared with the land cover/land use classification system suggested by National Geographic Information based on aerial photograph and Ministry of Environment based on satellite remote sensing data. As a result, high-resolution agricultural land cover map from IKONOS imageries was made out. The classification result by IKONOS image will be provided to KOMPSAT-2 project for agricultural application.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.1
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• pp.21-28
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• 2010

Forest fire is one of the main factor disturbing the environment of forest, and it influences greatly the structure and function on forest. The process of vegetation recovery could be decided according to the extent of the damage. It is required a lot of man powers and budgets to understand born severity and process of vegetation rehabilitation at the damaged area after large-fire. However, the analysis of born severity in the forest area using satellite imagery can acquire rapidly information and more objective results remotely in the large-fire area. In this study, the space sensors have been used to map area burned, assess characteristics of active fires. For classifying fire damaged area and analyzing severity of Cheongyang-Yesan fire in 2002, in this paper we use pre- and post-fire imagery from the Landsat TM and ETM+ to compute the evaluate large-scale patterns of burn severity, use the digital stock map to calculate the damaged condition about the forest fires damaged regions and use the NDVI to monitoring the situation of the revegetation.