• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.1
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• pp.98-106
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• 2003

Because satellite images have the advantage of high resolution, multi-spectral, revisit and wide swath characteristics, it is increased to utilize satellite image and get information little by little in nowadays. In order to utilize remote sensed images effectively, it is necessary to process satellite images through many processing steps. Among them, geometric correction is essential step for satellite image processing. In this study, we constructed geometric correction data using LANDSAT satellite images. First, we extracted GCPs from maps and constructed database over the Korean peninsular. Second, LANDSAT satellite images, 165 scenes were corrected geometrically using GCP database. Finally, we made 7 mosaic images by means of geometric correction images over Korean peninsular. We think that constructed geometric correction data will be used for many application fields as basic data.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.3
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• pp.63-71
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• 2013

This study calculated vegetation indexes such as SR, NDVI, SAVI, and LAI to figure out correlations regarding vegetation by using high resolution KOMPSAT-2 images and LANDSAT images based on the forest biomass distribution map that utilized field survey data, satellite images and LiDAR data and then analyzed correlations between their values and forest biomass. The analysis results reveal that the vegetation indexes of high resolution KOMPSAT-2 images had higher correlations than those of LANDSAT images and that NDVI recorded high correlations among the vegetation indexes. In addition, the study analyzed the characteristics of hyperspectral images by using the COMIS of STSAT-3 and Hyperion images of a similar sensor, EO-1, and further the usability of biomass estimation in hyperspectral images by comparing vegetation index, which had relatively high correlations with biomass, with the vegetation indexes of LANDSAT with the same GSD conditions.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.12 no.1
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• pp.159-166
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• 1992

Landsat data are valuable in itself, and if they are classified in quantitative information and transformed to practical users, they will be more useful. In this view, it is very important to extract hydrologic parameter from Landsat data and to develope the hydrologic model that can be transformed to hydrologist to use it. This study is primary step for accomplishment of such purpose. This paper include output of hydrologic model which define the relation between soil condition and discharge and process of analysis of optical image or digital image that is adapted for hydrologic model. Finally, this paper present that Landsat image is very useful, economic and produce sufficiently accurate information for hydrologic model in large area watershed.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2016.11a
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• pp.362-363
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• 2016

본 연구에서는 Landsat 위성영상이 가진 열적외 밴드를 이용하여 서울시의 '16년 지표면 온도 변화를 분석하였다. '16년 7월과 8월에 발생한 폭염에 의해 온열질환 환자 2,095명과 사망자 17명을 발생시켰다. 위성영상을 이용하여 동일시기의 한반도 전체 지역 파악에는 한계가 있지만 특정 지역의 변화 추이를 분석하는 것은 가능하다. 본 연구에서는 공간해상도 30m급인 Landsat 위성영상을 이용하여 서울시의 '16년 대비 '94년과 '14년의 지표면 온도 변화를 분석하였다. 분석 결과, '94년에 비해 $1.1^{\circ}C$가 낮고, '14년에 비해 $3.9^{\circ}C$ 높음으로 확인되었다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.2
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• pp.239-246
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• 2010

Satellite image has capability of getting a broad data rapidly. It is possible that acquisition of change information about topography, land, ecosystem and urbanization etc. from multi-temporal satellite Images. In this study, the time-series change of vegetation has detected using four period Landsat Imageries. Also, NDVI was used to recognize the vitality of vegetation. Time series change of vegetation about study area was able to detect effectively by the results of classification and NDVI. It is expected that this study should be utilized as the decision making related to the effective management and plan establishment.

• Journal of the Korean earth science society
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• v.25 no.8
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• pp.764-773
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• 2004

The soil in wildfire area Sacheon-myeon, Gangneung, Gangweon Province, Korea, were investigated to clarify pattern of the soils. The soils were classified into 5 types on the basis of vegetation, types of organic matter. thickness of soil horizons, and completeness of soil profile. Each type showed different erosion pattern and Landsat ETM image. Coverage of plant leaves, litter, root, ash and other organic matter was an important component that affected soil color and reflectance of Landsat image (digital number). Although the NDVI (Normalized Distribution Vegetation Index) method in the wildfire area did not show much difference in soil types, the applied supervised classification method showed characteristic pattern of Landsat ETM image of soil types. This study showed that the applied supervised Landsat TM image classification in wildfire area is an effective way to estimate the distribution of erosion pattern of soil in wildfire area.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.4 s.34
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• pp.59-65
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• 2005

It is very important to detect land cover/land use change from the past and to use it for future urban plan. This paper investigated the application of Landsat satellite imagery for detecting urban growth and assessing its impact on surface temperature in the region. Land cover/land use change detection was carried out by using 30m resolution Landsat satellite images and hierarchial approach was introduced to detect more detail change on the changing area through high resolution aerial photos. Also, surface temperature according to land cover/land use was calculated from Landsat TM thermal infrared data and compared with real temperature to analyze the relationship between urban expansion and surface temperature. As a result, the urban expansion has raised surface radiant temperature in the urbanized area. The method using remote sensing data based on GIS was found to be effective in monitoring and analysing urban growth and in evaluating urbanization impact on surface temperature.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2016.11a
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• pp.384-385
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• 2016

본 연구에서는 최근 어류 폐사, 상수원 오염 등의 피해를 발생시키고 있는 녹조를 대상으로 위성영상을 이용한 발생 유무와 분포를 분석하고자 하였다. 녹조는 엽록소를 가지고 광합성을 하므로 식생과 매우 유사한 분광특성을 가진다. 이는 위성영상에서 제공하는 근적외 정보로부터 정규식생지수를 산출하고 그 변화를 분석함으로써 녹조 발생 유무를 식별해낼 수 있음을 의미한다. 연구 대상지역인 대청호는 올해 첫 조류경보가 발령된 수역으로 8월~10월 사이 상류지역을 중심으로 녹조가 발생하였다. 본 연구에서는 Landsat-8 위성영상을 이용하여 대청호에서 발생한 녹조분포를 분석하고, 그 중 높은 농도의 녹조가 발생한 추소리를 직접 방문하여 Unmanned Aerial Vehicle(UAV) 자료를 취득하였다. UAV 촬영 영상을 통해 추소리 수역에 녹조가 다량 발생한 것을 확인할 수 있었다. 향후에는 고해상도 위성영상인 플래닛스코프 위성영상을 추가적으로 활용함으로써 녹조 모니터링의 정확성과 적시성을 확보할 예정이다.

• Spatial Information Research
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• v.10 no.2
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• pp.331-343
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• 2002

Recently, as various fields of applications using space-borne imagery have been emphasized, interests on integrated analysis or fusion using multi-sources are also increasing. In this study, to investigate applicability of multiple imageries for further regional-scaled application, DN value analysis and multi-resolution classification by using KOMPSAT EOC imagery and Landsat 7 ETM+image data in the Namyangju-city area were performed, and then this classified results were compared to land-use thematic data at the same area. In case of classified results by using muff-resolution image data, it is shown that linear-type features can be easily extracted. furthermore, it is expected that multi-resolution classified image can be effectively utilized to urban environment analysis, according to results of similar pattern by comparative study based on multi-buffered zone analysis or so-called distance analysis along main road features in the study area.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.1
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• pp.1-11
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• 2021

Detection of surface water features including river, wetland, reservoir from the satellite imagery can be utilized for sustainable management and survey of water resources. This research compared the water indices derived from the multispectral bands and the machine learning technique for detecting the surface water features from he Landsat-8 satellite image acquired in Daegu through the following steps. First, the NDWI(Normalized Difference Water Index) image and the MNDWI(Modified Normalized Difference Water Index) image were separately generated using the multispectral bands of the given Landsat-8 satellite image, and the two binary images were generated from these NDWI and MNDWI images, respectively. Then SVM(Support Vector Machine), the widely used machine learning techniques, were employed to generate the land cover image and the binary image was also generated from the generated land cover image. Finally the error matrices were used for measuring the accuracy of the three binary images for detecting the surface water features. The statistical results showed that the binary image generated from the MNDWI image(84%) had the relatively low accuracy than the binary image generated from the NDWI image(94%) and generated by SVM(96%). And some misclassification errors occurred in all three binary images where the land features were misclassified as the surface water features because of the shadow effects.