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Analysis of the Surface Urban Heat Island Changes according to Urbanization in Sejong City Using Landsat Imagery (Landsat영상을 이용한 토지피복 변화에 따른 행정중심복합도시의 표면 열섬현상 변화분석)

  • Lee, Kyungil;Lim, Chul-Hee
    • Korean Journal of Remote Sensing
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    • v.38 no.3
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    • pp.225-236
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    • 2022
  • Urbanization due to population growth and regional development can cause various environmental problems, such as the urban heat island phenomenon. A planned city is considered an appropriate study site to analyze changes in urban climate caused by rapid urbanization in a short-term period. In this study, changes in land cover and surface heat island phenomenon were analyzed according to the development plan in Sejong City from 2013 to 2020 using Landsat-8 Operational Land Imager/Thermal Infrared Sensor (OLI/TIRS) satellite imagery. The surface temperature was calculated in consideration of the thermal infrared band value provided by the satellite image and the emissivity, and based on this the surface heat island effect intensity and Urban Thermal Field Variance Index (UTFVI) change analysis were performed. The level-2 land cover map provided by the Ministry of Environment was used to confirm the change in land cover as the development progressed and the difference in the surface heat island intensity by each land cover. As a result of the analysis, it was confirmed that the urbanized area increased by 15% and the vegetation decreased by more than 28%. Expansion and intensification of the heat island phenomenon due to urban development were observed, and it was confirmed that the ecological level of the area where the heat island phenomenon occurred was very low. Therefore, It can suggest the need for a policy to improve the residential environment according to the quantitative change of the thermal environment due to rapid urbanization.

A Study on Land Surface Temperature Changes in Redevelopment Area Using Landsat Satellite Images : Focusing on Godeok-dong and Dunchon-dong in Gangdong-gu, Seoul (Landsat 위성영상을 활용한 재건축 지역의 지표 온도 변화에 관한 연구 : 서울특별시 강동구의 고덕동과 둔촌동을 중심으로)

  • Jihoon HAN;Chul SON
    • Journal of the Korean Association of Geographic Information Studies
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    • v.26 no.2
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    • pp.42-54
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    • 2023
  • The population is concentrated in the metropolitan areas in Korea, and low-density residential areas are transforming into high density residential areas through redevelopment to meet this demand. However, large-scale redevelopment in a short period of time has a negative impact on the urban climate, such as generating a heat island effect due to the reduction of urban green areas. In this study, the change in surface temperature from 2013 to 2022 in the redevelpment areas of Godeok-dong and Dunchon-dong, Gangdong-gu, Seoul, was analyzed using Landsat 8 satellite images. In the Godeok-dong area, the difference in surface temperature was analyzed for the target redevelopment area, forest area, mixed forest and urban area, and low density residential area. In the Dunchon-dong area, the difference in surface temperature was analyzed for the target redevelopment area, forest area, and low density residential area. The difference in surface temperature was analyzed through multiple regression analysis conducted yearly over the three different stages in redevelopment period. The results from the multiple regression analysis show that in both areas, the land surface temperature of target redevelopment area was higher than that of the forest area and lower than low density residential area. It can be seen that these results occurred because the low-density residential area in Godeok-dong and Dunchon-dong had a lower green area ratio and a higher building-to-land ratio than the target redevelopment area. The results of this study suggest that even if low-density residential areas are transforming into high-density areas, adjusting the management of green areas and building-to-land ratio can contribute to lessen urban heat island effect.

Analysis on the Snow Cover Variations at Mt. Kilimanjaro Using Landsat Satellite Images (Landsat 위성영상을 이용한 킬리만자로 만년설 변화 분석)

  • Park, Sung-Hwan;Lee, Moung-Jin;Jung, Hyung-Sup
    • Korean Journal of Remote Sensing
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    • v.28 no.4
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    • pp.409-420
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    • 2012
  • Since the Industrial Revolution, CO2 levels have been increasing with climate change. In this study, Analyze time-series changes in snow cover quantitatively and predict the vanishing point of snow cover statistically using remote sensing. The study area is Mt. Kilimanjaro, Tanzania. 23 image data of Landsat-5 TM and Landsat-7 ETM+, spanning the 27 years from June 1984 to July 2011, were acquired. For this study, first, atmospheric correction was performed on each image using the COST atmospheric correction model. Second, the snow cover area was extracted using the NDSI (Normalized Difference Snow Index) algorithm. Third, the minimum height of snow cover was determined using SRTM DEM. Finally, the vanishing point of snow cover was predicted using the trend line of a linear function. Analysis was divided using a total of 23 images and 17 images during the dry season. Results show that snow cover area decreased by approximately $6.47km^2$ from $9.01km^2$ to $2.54km^2$, equivalent to a 73% reduction. The minimum height of snow cover increased by approximately 290 m, from 4,603 m to 4,893 m. Using the trend line result shows that the snow cover area decreased by approximately $0.342km^2$ in the dry season and $0.421km^2$ overall each year. In contrast, the annual increase in the minimum height of snow cover was approximately 9.848 m in the dry season and 11.251 m overall. Based on this analysis of vanishing point, there will be no snow cover 2020 at 95% confidence interval. This study can be used to monitor global climate change by providing the change in snow cover area and reference data when studying this area or similar areas in future research.

Retrieving Volcanic Ash Information Using COMS Satellite (MI) and Landsat-8 (OLI, TIRS) Satellite Imagery: A Case Study of Sakurajima Volcano (천리안 위성영상(MI)과 Landsat-8 위성영상(OLI, TIRS)을 이용한 화산재 정보 산출: 사쿠라지마 화산의 사례연구)

  • Choi, Yoon-Ho;Lee, Won-Jin;Park, Sun-Cheon;Sun, Jongsun;Lee, Duk Kee
    • Korean Journal of Remote Sensing
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    • v.33 no.5_1
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    • pp.587-598
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    • 2017
  • Volcanic ash is a fine particle smaller than 2 mm in diameters. It falls after the volcanic eruption and causes various damages to transportation, manufacturing industry and respiration of living things. Therefore diffusion information of volcanic ash is highly significant for preventing the damages from it. It is advantageous to utilize satellites for observing the widely diffusing volcanic ash. In this study volcanic ash diffusion information about two eruptions of Mt. Sakurajima were calculated using the geostationary satellite, Communication, Ocean and Meteorological Satellite (COMS) Meteorological Imager (MI) and polar-orbiting satellite, Landsat-8 Operational Land Imager (OLI) and the Thermal InfraRed Sensor (TIRS). The direction and velocity of volcanic ash diffusion were analyzed by extracting the volcanic ash pixels from COMS-MI images and the height was retrieved by adjusting the shadow method to Landsat-8 images. In comparison between the results of this study and those of Volcanic Ash Advisories center (VAAC), the volcanic ash tend to diffuse the same direction in both case. However, the diffusion velocity was about four times slower than VAAC information. Moreover, VAAC only provide an ash height while our study produced a variety of height information with respect to ash diffusion. The reason for different results is measured location. In case of VAAC, they produced approximate ash information around volcano crater to rapid response, while we conducted an analysis of the ash diffusion whole area using ash observed images. It is important to measure ash diffusion when large-scale eruption occurs around the Korean peninsula. In this study, it can be used to produce various ash information about the ash diffusion area using different characteristics satellite images.

Seasonal Variation of Thermal Effluents Dispersion from Kori Nuclear Power Plant Derived from Satellite Data (위성영상을 이용한 고리원자력발전소 온배수 확산의 계절변동)

  • Ahn, Ji-Suk;Kim, Sang-Woo;Park, Myung-Hee;Hwang, Jae-Dong;Lim, Jin-Wook
    • Journal of the Korean Association of Geographic Information Studies
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    • v.17 no.4
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    • pp.52-68
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    • 2014
  • In this study, we investigated the seasonal variation of SST(Sea Surface Temperature) and thermal effluents estimated by using Landsat-7 ETM+ around the Kori Nuclear Power Plant for 10 years(2000~2010). Also, we analyzed the direction and range of thermal effluents dispersion by the tidal current and tide. The results are as follows, First, we figured out the algorithm to estimate SST through the linear regression analysis of Landsat DN(Digital Number) and NOAA SST. And then, the SST was verified by compared with the in situ measurement and NOAA SST. The determination coefficient is 0.97 and root mean square error is $1.05{\sim}1.24^{\circ}C$. Second, the SST distribution of Landsat-7 estimated by linear regression equation showed $12{\sim}13^{\circ}C$ in winter, $13{\sim}19^{\circ}C$ in spring, and $24{\sim}29^{\circ}C$ and $16{\sim}24^{\circ}C$ in summer and fall. The difference of between SST and thermal effluents temperature is $6{\sim}8^{\circ}C$ except for the summer season. The difference of SST is up to $2^{\circ}C$ in August. There is hardly any dispersion of thermal effluents in August. When it comes to the spread range of thermal effluents, the rise range of more than $1^{\circ}C$ in the sea surface temperature showed up to 7.56km from east to west and 8.43km from north to south. The maximum spread area was $11.65km^2$. It is expected that the findings of this study will be used as the foundational data for marine environment monitoring on the area around the nuclear power plant.

Red Tide Detection through Image Fusion of GOCI and Landsat OLI (GOCI와 Landsat OLI 영상 융합을 통한 적조 탐지)

  • Shin, Jisun;Kim, Keunyong;Min, Jee-Eun;Ryu, Joo-Hyung
    • Korean Journal of Remote Sensing
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    • v.34 no.2_2
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    • pp.377-391
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    • 2018
  • In order to efficiently monitor red tide over a wide range, the need for red tide detection using remote sensing is increasing. However, the previous studies focus on the development of red tide detection algorithm for ocean colour sensor. In this study, we propose the use of multi-sensor to improve the inaccuracy for red tide detection and remote sensing data in coastal areas with high turbidity, which are pointed out as limitations of satellite-based red tide monitoring. The study area were selected based on the red tide information provided by National Institute of Fisheries Science, and spatial fusion and spectral-based fusion were attempted using GOCI image as ocean colour sensor and Landsat OLI image as terrestrial sensor. Through spatial fusion of the two images, both the red tide of the coastal area and the outer sea areas, where the quality of Landsat OLI image was low, which were impossible to observe in GOCI images, showed improved detection results. As a result of spectral-based fusion performed by feature-level and rawdata-level, there was no significant difference in red tide distribution patterns derived from the two methods. However, in the feature-level method, the red tide area tends to overestimated as spatial resolution of the image low. As a result of pixel segmentation by linear spectral unmixing method, the difference in the red tide area was found to increase as the number of pixels with low red tide ratio increased. For rawdata-level, Gram-Schmidt sharpening method estimated a somewhat larger area than PC spectral sharpening method, but no significant difference was observed. In this study, it is shown that coastal red tide with high turbidity as well as outer sea areas can be detected through spatial fusion of ocean colour and terrestrial sensor. Also, by presenting various spectral-based fusion methods, more accurate red tide area estimation method is suggested. It is expected that this result will provide more precise detection of red tide around the Korean peninsula and accurate red tide area information needed to determine countermeasure to effectively control red tide.