• Journal of Wetlands Research
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• v.23 no.2
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• pp.154-162
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• 2021

The naturally opened Han river estuary is a place where the flows of the Han river, Imjin river, Yaesung river meet with West Sea of Korea, so the hydrodynamic mechanism(Impact-Response) structure of Han river estuary is complex. Continuous observation and measurement due to the morphological characteristics at the estuary are required to maintain the estuary environment and river management facilities. However, the Sannam wetland(the study area) is in the military operation area. Therefore, Sannam wetland has the limited access under the control from military office. In 2020, there had a natural disaster due to flooding in August and COVID-19, and it made a survey hard. The noncontact survey technique, the analysis of LANDSAT images at Sannam wetland, was applied to analyze riverbed fluctuation and morphological transformation around Sannam wetland. LANDSAT images obtained from EarthExplorer, USGS and analyzed by QGIS. The analysis was performed based on the area and the distance near Sannam wetland. As a result, an erosion was happened on the downstream of the study area, and the upstream of the study area did not have any serious sediment transport. Considering the resolution of LANDSAT images, this noncontect survey technique is applicable to manage the study area. From the analysis of LANDSAT images, it is assumed that the tidal effect is greater than the inflow from the upstream. The pattern change of tidal response causes the damage of the river facilities near the Hangang river estuary.

• 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.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2004.11a
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• pp.89-89
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• 2004

• Proceedings of the KSEEG Conference
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• 2007.04a
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• pp.208-211
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• 2007

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1473-1473
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• 2003

• Korean Journal of Remote Sensing
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• v.33 no.3
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• pp.287-299
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• 2017

The Southern Volcanic Zone (SVZ) of Chile consists of many volcanoes, including the Mt.Villarrica and Mt.Llaima, and the two volcanoes are covered with snow at the top of Mountain. The purpose of this study is to analyze the relationship between the ice caps and the volcanic activity of the two volcanoes for 25 years by using the satellite image data are available in a time series. A total of 60 Landsat-5 TM and Landsat-7 ETM + data were used for the study from September 1986 to February 2011. Using NDSI (Normalized Difference Snow Index) algorithm and SRTM DEM, snow cover and snowline were extracted. Finally, the snow cover area, lower-snowline, and upper-snowline, which are quantitative indicators of snow cover change, were directly or indirectly affected by volcanic activity, were extracted from the satellite images. The results show that the volcanic activity of Villarrica volcano is more than 55% when the snow cover is less than 20 and the lower-snowline is 1,880 m in Llaima volcano. In addition, when the upper-snowline of the two volcanoes is below -170m, it can be confirmed that the volcano is differentiated with a probability of about 90%. Therefore, the changes in volcanic snowfall are closely correlated with volcanic activity, and it is possible to indirectly deduce volcanic activity by monitoring the snow.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.1
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• pp.129-139
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• 2019

Mapping urban areas using the earth observation satellites is useful for monitoring urban expansions and measuring urban developments. In this research, the different thresholds for detecting the urban areas separately from the remote-sensing index images (normalized-difference built-up index(NDBI) and urban index(UI) images) generated from the Landsat-8 image acquired in Daegu, South Korea were evaluated through the following steps: (1) the NDBI and UI images were separately generated from the given Landsat-8 image; (2) the different thresholds (-0.4, -0.2, and 0) for detecting the urban areas separately from the NDBI and UI images were evaluated; and (3) the accuracy of each detected urban area was assessed. The experiment results showed that the threshold -0.2 had the best performance for detecting the urban areas from the NDBI image, while the threshold -0.4 had the best performance for detecting the urban areas from the UI image. Some misclassification errors, however, occurred in the areas where the bare soil areas were classified into urban areas or where the high-rise apartments were classified into other areas. In the future research, a robust methodology for detecting urban areas, including the various types of urban features, with less misclassification errors will be proposed using the satellite images. In addition, research on analyzing the pattern of urban expansion will be carried out using the urban areas detected from the multi-temporal satellite images.

• Korean Journal of Agricultural Science
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• v.39 no.1
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• pp.87-95
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• 2012

Land surface temperature (LST) is an important factor in human health, thermal environment, heat balance, global change studies, and as control for climate change. The objective of this study was to assess the influence of Urban Heat Island (UHI) Effects on the LST and NDVI in Cheongju, Korea. The aim was to evaluate the effect of urban thermal environment for LST comparison of satellite-derived and in situ measured temperature. In this study, LANDSAT TM and KOMPSAT scene were used. The results indicated that the minimum LST is observed over dense forest as about $21{\sim}25^{\circ}C$ and maximum LST is observed over industrial area of about $28{\sim}32^{\circ}C$. The estimated LST showed that industrial area, bare soils and built-up areas exhibit higher surface temperatures, while forest, water bodies, agricultural croplands, and dense vegetations have lower surface temperatures during the summer daytime. Result corroborates the fact that LST over land use/land cover (LULC) types are greatly influenced by the amount of vegetation and water bodies present. The LST of industrial area and urban center is higher than that of suburban area, so it is clearly proved that there are obvious UHIE in Cheongju.

• Journal of Forest and Environmental Science
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• v.28 no.3
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• pp.144-151
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• 2012

Deforestation is a major and very critical problem faced by many tropical countries including Malaysia. Sabah is the second largest state in Malaysia and its deforestation rate has been accelerating. This study was conducted to monitor the deforestation in Sabah in the last two decades with Landsat images of 1990, 2000 and 2008. Supervised classification with maximum likelihood algorithm was conducted using the Landsat data for monitoring deforestation. In total, between 1990 and 2008, Sabah lost half of its intact forest, or more than 1.85 million ha in less than two decades. Overall, the deforestation rate for all forest types combined for the last two decades was 1.6% per year. Deforestation seemed to be accelerating because the deforestation rate between 1990 and 2000 was 0.9% per year and it had increased to 2.7% per year between 2000 and 2008. The deforestation trend seemed to follow a negative exponential from 1990 to 2008. In contrast, the agricultural areas increased rapidly with a total of increment more than 1 million ha. This confirmed that agriculture especially establishment of commercial plantation was the major factor of deforestation in Sabah for the last two decades.

• 한국방재학회:학술대회논문집
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• 2007.02a
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• pp.231-237
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• 2007

To monitor process of vegetation rehabilitation at the damaged area after large-fire is required a lot of manpowers and budgets. However the analysis of vegetation recovery using satellite imagery can be obtaining rapid and objective result remotely in the large damaged area. Space and airbone sensors have been used to map area burned, assess characteristics of active fires, and characterize post-fire ecological effects. Burn severity incorporates both short- and long-term post-fire effects on the local and regional environment. Burn severity is defined by the degree to which an ecosystem has changed owing to the fire. To classify fire damaged area and analyze burn severity of Samcheok fire area occurred in 2000, Cheongyang fire 2002, and Yangyang fire 2005 was utilized Landsat TM and ETM+ imagery. Therefore the objective of the present paper is to quantitatively classify fire damaged area and analyze burn severity using normalized burn index(NBR) of pre- and post-fire's Landsat satellite imagery.