• The Journal of Engineering Geology
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• v.24 no.3
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• pp.411-421
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• 2014

The purpose of this study is to analyze the key factors that contribute to landslide causes through swelling clay minerals and terrain analysis in landslide sites taken place of in Yongin city, Gyeonggi-do, 2011. The study was conducted based on field survey by XRD (X-ray Diffraction), XRF (X-ray fluorescence), spectroscopic analysis on soil samples obtained from landslide sites and ASTER satellite image. Illite shows absorption features; $Fe^{2+}$ and $Fe^{3+}$ at 0.9 and $1.0{\mu}m$, broad water absorption features near 1.4 and $1.9{\mu}m$, and additional Al-hydroxyl features at 2.2, 2.3 and $2.4{\mu}m$, respectively. These absorption features are consistent with the bands 5, 6, and 7 of ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) satellite image. Illite image was extracted using band math of $SWIR_{Illite}$. From these results, we confirmed the applicability of ASTER satellite image using identification of swelling clay minerals to landslide study.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.4
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• pp.94-100
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• 2008

Recently, global warming for climate system is a crucial issue over the world and it brings about severe climate change, abnormal temperature, a downpour, a drought, and so on. Especially, a drought over the earth surface accelerates desertification which has been advanced over the several years mainly originated from a climatic change. The objective of this study is to detect variation of vegetation water condition around China and Mongolia desert by using satellite data having advantage in observing surface biological system. In this study, we use SPOT/VEGETATION satellite image to calculate NDWI (Normalized Difference Water Index) around study area desert for monitoring of status of vegetation characteristics. The vegetation water status index from remotely sensing data is related to desertification since dry vegetation is apt to desertify. We can infer vegetation water status using NDWI acquired by NIR (Near infrared) and SWIR (Short wave infrared) bands from SPOT/VGT. The consequence is that NDWI decreased around desert from 1999 to 2006. The areas that NDWI was decreased are located in the northeast of Mongolian Gobi desert and the southeast of China Taklamakan desert.

• Korean Journal of Remote Sensing
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• v.31 no.5
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• pp.371-384
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• 2015

Although GOCI has potential for land surface monitoring, there have been only a few cases for land applications. It might be due to the lack of reliable land products derived from GOCI data for end-users. To use for land applications, it is often essential to provide cloud-free composite over land surfaces. In this study, we proposed a cloud detection method that was very important to make cloud-free composite of GOCI reflectance and vegetation index. Since GOCI does not have SWIR and TIR spectral bands, which are very effective to separate clouds from other land cover types, we developed a multi-temporal approach to detect cloud. The proposed cloud detection method consists of three sequential steps of spectral tests. Firstly, band 1 reflectance threshold was applied to separate confident clear pixels. In second step, thick cloud was detected by the ratio (b1/b8) of band 1 and band 8 reflectance. In third step, average of b1/b8 ratio values during three consecutive days was used to detect thin cloud having mixed spectral characteristics of both cloud and land surfaces. The proposed method provides four classes of cloudiness (thick cloud, thin cloud, probably clear, confident clear). The cloud detection method was validated by the MODIS cloud mask products obtained during the same time as the GOCI data acquisition. The percentages of cloudy and cloud-free pixels between GOCI and MODIS are about the same with less than 10% RMSE. The spatial distributions of clouds detected from the GOCI images were also similar to the MODIS cloud mask products.

• Conservation Science in Museum
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• v.19
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• pp.19-40
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• 2018

Most stone monuments in Korea are made from the granitoids found extensively throughout the nation. To identify the provenance of the stone materials, this study carried out comprehensive analyses of the occurrence, physical properties, mineralogy, and chemical composition of Stupa for National Preceptor Wongong at Geodonsa Temple and Five-story Pagoda at Cheonsusa Temple, both located in the Gangwon region. Their features were compared with those of granite from Wonju City near the sites of the two monuments. Stupa for National Preceptor Wongong is composed purely of two-mica granite, whereas Five-story Pagoda was made from both two-mica and biotite granites. The occurrence and magnetic susceptibility of the two granite monuments generally coincide with those of granite from Wonju. When selecting materials for the restoration of stone monuments, it is deemed necessary to carry out a field survey on granite in areas adjacent to the locations of the stone monuments subject to restoration.

• 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.35 no.6_2
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• pp.1133-1148
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• 2019

Tree growth and vitality in forest shows seasonal changes. So, in order to detect forest damage accurately, we have to use satellite images before and after damages taken at the same season. However, temporal resolution of high or medium resolution images is very low,so it is not easy to acquire satellite images of the same seasons. Therefore, in this study, we estimated spectral information of the same DOY using time-series Landsat images and used the estimates as reference values to assess forest damages. The study site is Hwasun, Jeollanam-do, where forest damage occurred due to hail and drought in 2017. Time-series vegetation index (NDVI, EVI, NDMI) maps were produced using all Landsat 8 images taken in the past 3 years. Daily normal vegetation index maps were produced through cloud removal and data interpolation processes. We analyzed the difference of daily normal vegetation index value before damage event and vegetation index value after event at the same DOY, and applied the criteria of forest damage. Finally, forest damage map based on daily normal vegetation index was produced. Forest damage map based on Landsat images could detect better subtle changes of vegetation vitality than the existing map based on UAV images. In the extreme damage areas, forest damage map based on NDMI using the SWIR band showed similar results to the existing forest damage map. The daily normal vegetation index map can used to detect forest damage more rapidly and accurately.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.253-265
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• 2020

As the risk of landslide is recently increasing due to the typhoons and localized heavy rains, effective techniques for the landslide damage detection are required to support the establishment of the recovery planning. This study describes the analysis of landslide-damaged areas using ISODATA(Iterative Self-Organizing Data Analysis Technique Algorithm) with Sentinel-2 image, regarding the case of Gokseong in August 7, 2020. A total of 4.75 ha of landslide-damaged areas was detected from the Sentinel-2 image using spectral characteristics of red, NIR(Near Infrared), and SWIR(Shortwave Infrared) bands. We made sure that the satellite remote sensing is an effective method to detect the landslide-damaged areas and support the establishment of the recovery planning, followed by the field surveys that require a lot of manpower and time. Also, this study can be used as a reference for the landslide management for the CAS500-1/2(Compact Advanced Satellite) scheduled to launch in 2021 and the Korean Medium Satellite for Agriculture and Forestry scheduled to launch in 2024.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.695-706
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• 2022

Medium and high-resolution optical satellites have proven their effectiveness in detecting wildfire areas. However, smoke plumes generated by wildfire scatter visible light incidents on the surface, thereby interrupting accurate monitoring of the area where wildfire occurs. Therefore, a technology to extract smoke in advance is required. Deep learning technology is expected to improve the accuracy of smoke extraction, but the lack of training datasets limits the application. However, for clouds, which have a similar property of scattering visible light, a large amount of training datasets has been accumulated. The purpose of this study is to develop a smoke extraction technique using deep learning, and the limits due to the lack of datasets were overcome by using a cloud dataset on transfer learning. To check the effectiveness of transfer learning, a small-scale smoke extraction training set was made, and the smoke extraction performance was compared before and after applying transfer learning using a public cloud dataset. As a result, not only the performance in the visible light wavelength band was enhanced but also in the near infrared (NIR) and short-wave infrared (SWIR). Through the results of this study, it is expected that the lack of datasets, which is a critical limit for using deep learning on smoke extraction, can be solved, and therefore, through the advancement of smoke extraction technology, it will be possible to present an advantage in monitoring wildfires.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.422-425
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• 2005

Spectral characteristics depending on soil constituents and their proportion in a soil were firstly studied for monitoring of soil contamination using hyperspectral remote sensing. The reflectance spectra of heavy metals in soils were investigated in the VIS-NIR-SWIR regions (400-2500 nm) to observe spectral variation as a function of constituents and concentrations. Commercial kaolinite soils mixed with lead, copper, arsenic, and cadmium were used as synthetic soil samples for spectral measurement. In case of copper, relatively spectrally active regions was observed with some band shift whereas other heavy metals had only simple spectral variations expected to be related to the sorption phase and the amount of metal onto kaolinite. The reflectance spectrum of each metal on kaolinite could be identified in VIS-NIR region.

• Aerospace Engineering and Technology
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• v.11 no.2
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• pp.12-18
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• 2012

In this paper, impacts on the COMS MI images during the COMS eclipse period were analyzed and the method to eliminate the contaminated area was investigated. Main effect on the meteorological images during the eclipse is a stripping effect due to a strong stray light. The quantitative analyses were conducted during the COMS In-Orbit-Test period and the impacts of the stray light on the four infrared channels of the COMS MI according to the distance with respect to the Sun were examined. Based on the typical case of the stray light influence on the infrared channel of the MI, the intensity of contamination due to the stray light was investigated for each channel using the computed COMS eclipse information. The effectiveness of removal of a contaminated area by replacing the SWIR with the combined WINDOW channels was promising.