• Title/Summary/Keyword: Landsat

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Glacier Change in the Yigong Zangbo Basin, Tibetan Plateau, China

  • Ke, Chang-Qing;Lee, Hoonyol;Han, Yan-Fei
    • Korean Journal of Remote Sensing
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    • v.35 no.4
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    • pp.491-502
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    • 2019
  • Distinguishing debris-covered glaciers from debris-free glaciers is difficult when using only optical remote sensing images to extract glacier boundaries.According to the features that the surface temperature of debris-covered glacier is lower than surrounding objects, and higher than clean glaciers, glacial changes in the Yigong Zangbo basin was analyzed on the basis of visible, near-infrared and thermal-infrared band images of Landsat TM and OLI/TIRS in the support of ancillary digital elevation model (DEM). The results indicated that glacier area gradually declined from $928.76km^2$ in 1990 to $918.46km^2$ in 2000 and $901.51km^2$ in 2015. However, debris-covered glacier area showed a slight increase from $63.39km^2$ in 1990 to $66.24km^2$ in 2000 and $71.16km^2$ in 2015. During 25 years, the glacier length became shorter continuously with terminus elevation rising up. The area of moraine lakes in 1990 was $1.43km^2$, which increased to $1.98km^2$ in 2000 and $3.41km^2$ in 2015. In other words, the total area of the moraine lakes in 2015 is 2.38 times of that in 1990. This increase in moraine lake area could be the result of accelerated glacier melt and retreat, which is consistent with the significant warming trend in recent decades in the basin.

Spatial and temporal dynamic of land-cover/land-use and carbon stocks in Eastern Cameroon: a case study of the teaching and research forest of the University of Dschang

  • Temgoua, Lucie Felicite;Solefack, Marie Caroline Momo;Voufo, Vianny Nguimdo;Belibi, Chretien Tagne;Tanougong, Armand
    • Forest Science and Technology
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    • v.14 no.4
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    • pp.181-191
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    • 2018
  • This study was carried out in the teaching and research forest of the University of Dschang in Belabo, with the aim of analysing land-cover and land-use changes as well as carbon stocks dynamic. The databases used are composed of three Landsat satellite images (5TM of 1984, 7ETM + of 2000 and 8OLI of 2016), enhanced by field missions. Satellite images were processed using ENVI and ArcGIS software. Interview, focus group discussion methods and participatory mapping were used to identify the activities carried out by the local population. An inventory design consisting of four transects was used to measure dendrometric parameters and to identify land-use types. An estimation of carbon stocks in aboveground and underground woody biomass was made using allometric models based on non-destructive method. Dynamic of land-cover showed that the average annual rate of deforestation is 0.48%. The main activities at the base of this change are agriculture, house built-up and logging. Seven types of land-use were identified; adult secondary forests (64.10%), young secondary forests (7.54%), wetlands (7.39%), fallows (3.63%), savannahs (9.59%), cocoa farms (4.28%) and mixed crop farms (3.47%). Adult secondary forests had the highest amount of carbon ($250.75\;t\;C\;ha^{-1}$). This value has decreased by more than 60% for mixed crop farms ($94.67\;t\;C\;ha^{-1}$), showing the impact of agricultural activities on both forest cover and carbon stocks. Agroforestry systems that allow conservation and introduction of woody species should be encouraged as part of a participatory management strategy of this forest.

Analysis of the Relationship between Three-Dimensional Built Environment and Urban Surface Temperature (도시의 3차원 물리적 환경변수와 지표온도의 관계 분석)

  • Li, Yige;Lee, Sugie;Han, Jaewon
    • Journal of Korea Planning Association
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    • v.54 no.2
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    • pp.93-108
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    • 2019
  • This study examines the relationship between three-dimensional urban built environment and urban surface temperature using LANDSAT 8 satellite image data in Seoul city. The image was divided into 600m×600m grid units as an unit of analysis. Due to the high level of spatial dependency in surface temperature, this study uses spatial statistics to take into account spatial auto-correlation. The spatial error model shows the best goodness of fit. The analysis results show that the three-dimensional built environment and transport environment as well as natural environment have statistically significant associations with surface temperature. First, natural environment variables such as green space, streams and river, and average elevation show statistically significant negative association with surface temperature. Second, the building area shows a positive association with surface temperature. In addition, while sky view factor (SVF) has a positive association with surface temperature, surface roughness (SR) shows a negative association with it. Third, transportation related variables such as road density, railway density, and traffic volume show positive associations with surface temperature. Moreover, this study finds that SVF and SR have different effects on surface temperature in regard to the levels of total floor areas in built environment. The results indicate that interactions between floor area ratio (FAR) and three-dimensional built environmental variables such as SVF and SR should be considered to reduce urban surface temperature.

Monitoring of Vegetation Recovery According to Natural and Artificial Restoration Methods After Forest Fire Damage Using Satellite Imagery (위성영상을 이용한 산불피해 이후 자연복원과 인공복원 방법에 따른 식생회복 모니터링)

  • Hwang, Yeong In;Kang, Won Seok;Park, Ki Hyung;Lee, Kyeong Cheol;Han, Sang Gyun;Kweon, Hyeong Keun
    • Journal of Practical Agriculture & Fisheries Research
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    • v.24 no.3
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    • pp.33-43
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    • 2022
  • This study was conducted to monitor the vegetation recovery in the areas damaged by the forest fires on the east coast that occurred in April 2000. The study site was a forest fire-damaged area in Samcheok-si, Gangwon-do, and 21 monitoring areas (12 natural restoration sites, 9 artificial restoration sites) were selected to analyze the vegetation recovery trend since 1998. The vegetation recovery trend was compared by calculating the values according to the year using the difference Normalized Burn Ratio (dNBR) and Normalized Difference Vegetation Index (NDVI) based on satellite images (Landsat TM/ETM+ and Sentinel-2A). As the result of this study, all 21 sites, vegetation was recovered, and both groups showed the greatest recovery in summer. In the case of the dNBR, the artificial restored sites showed higher values than the natural restored sites, and in the case of the NDVI, the natural restored sites were higher than the artificially restored sites in summer and autumn. However, the difference between the two groups of natural and artificial restoration sites was not significant. Therefore, the direction of forest restoration after forest fire damage can be effectively restored if properly implemented for the purpose of restoration of the target site.

Satellite-derived high-resolution land cover classification using machine learning techniques: Focusing on inland wetlands in Korea (머신러닝 기법을 활용한 인공위성 자료 기반 고해상도 토지피복 분류: 국내 내륙습지를 중심으로)

  • Beomseo Kim;Seunghyun Hwang;Jeemi Sung;Hyeon-Joon Kim;Jongjin Baik;Changhyun Jun
    • Proceedings of the Korea Water Resources Association Conference
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    • 2023.05a
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    • pp.423-423
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    • 2023
  • 습지 생태계는 탄소저장고, 대기 온·습도 조절 등의 기능을 수행하는 만큼 면밀한 관리가 요구된다. 습지의 규모와 생태계는 밀접한 연관성을 가지므로 그 규모를 우선적으로 파악할 필요가 있으며, 이를 위해 지표면의 상태를 산지, 습지, 수역 등의 항목으로 구분한 토지피복지도가 고려될 수 있다. 현재, 환경부에서 운영 중인 환경공간정보서비스(https://egis.me.go.kr/)에서는 각각 30 m, 5 m, 1 m의 공간 해상도와 7, 22, 41가지 분류 항목을 갖는 대분류, 중분류, 세분류로 구분된 토지피복지도를 제공하며 이러한 자료들은 모두 1년 이상의 시간 해상도를 갖는다. 습지의 경우, 계절에 따른 환경 변화로 인한 규모의 변동성이 크게 나타날 수 있기 때문에 1년 이하의 시간 해상도를 갖는 고품질 토지피복 분류 정보가 요구된다. 따라서 본 연구에서는 기존 자료의 낮은 시간 해상도 보완을 목표로, 1개월과 30 m의 시·공간 해상도를 갖는 토지피복지도를 구축하기 위한 방법론을 제안하고자 한다. 이를 위해 Landsat-8 등과 같은 다양한 인공위성 자료를 수집하고, Support Vector Machine 등과 같은 머신러닝 기법을 적용하였다. 최종적으로 습지보전법에서 지정한 습지보호지역 중 내륙습지 26개소를 대상으로, 본 연구로부터 산출된 토지피복지도를 기존 환경공간정보서비스 내 대분류 토지피복지도와 비교·평가하였다.

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Assessment of Flood Vulnerability: Baramarae Intertidal Area in Anmyeondo, Korea (침수 취약성 평가: 안면도 바람아래 조간대 지역을 사례로)

  • KIM, Jang-soo;JANG, Dong-Ho
    • Journal of The Geomorphological Association of Korea
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    • v.17 no.2
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    • pp.29-39
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    • 2010
  • Climate change recently causes rapid rises in sea level in Baramarae intertidal area and the rises present several socio-economic impacts to the affected area. We have assessed the vulnerability of the region by the rise of the sea level. Using quantitative GIS method on multi-temporal satellite images, we have first estimated the elevation (Digital Elevation Model: DEM) of Baramarae intertidal area and hence we were possibly able to identify the flooded areas under the IPCC SRES scenarios. As sea level rises by 20cm, 30cm, 40cm, 50cm and 60 cm, the estimated flooded areas of the tidal flat are 68ha, 85ha, 103ha, 121ha and 139ha, respectively. The most affected area is the tidal flat in Gagyeongju Village (Gonam-li, Gonam-myeon, Taean, Chungnam), because it has not only lower altitude but also, perhaps more significantly smooth slope. The potential affected areas are currently populated by farming of oysters and short-necked clams and therefore the areas expect significant economic loss by rise of sea level.

Estimation of Forest Carbon Stock in South Korea Using Machine Learning with High-Resolution Remote Sensing Data (고해상도 원격탐사 자료와 기계학습을 이용한 한국 산림의 탄소 저장량 산정)

  • Jaewon Shin;Sujong Jeong;Dongyeong Chang
    • Atmosphere
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    • v.33 no.1
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    • pp.61-72
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    • 2023
  • Accurate estimation of forest carbon stocks is important in establishing greenhouse gas reduction plans. In this study, we estimate the spatial distribution of forest carbon stocks using machine learning techniques based on high-resolution remote sensing data and detailed field survey data. The high-resolution remote sensing data used in this study are Landsat indices (EVI, NDVI, NDII) for monitoring vegetation vitality and Shuttle Radar Topography Mission (SRTM) data for describing topography. We also used the forest growing stock data from the National Forest Inventory (NFI) for estimating forest biomass. Based on these data, we built a model based on machine learning methods and optimized for Korean forest types to calculate the forest carbon stocks per grid unit. With the newly developed estimation model, we created forest carbon stocks maps and estimated the forest carbon stocks in South Korea. As a result, forest carbon stock in South Korea was estimated to be 432,214,520 tC in 2020. Furthermore, we estimated the loss of forest carbon stocks due to the Donghae-Uljin forest fire in 2022 using the forest carbon stock map in this study. The surrounding forest destroyed around the fire area was estimated to be about 24,835 ha and the loss of forest carbon stocks was estimated to be 1,396,457 tC. Our model serves as a tool to estimate spatially distributed local forest carbon stocks and facilitates accounting of real-time changes in the carbon balance as well as managing the LULUCF part of greenhouse gas inventories.

Detection and Monitoring of Multi Natural Disaster Considering on Heatwave and Drought (폭염 및 가뭄을 고려한 복합자연재해 감지 및 모니터링)

  • Lee, Hee-Jin;Nam, Won-Ho;Jeon, Min-Gi;Svoboda, Mark D.
    • Proceedings of the Korea Water Resources Association Conference
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    • 2022.05a
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    • pp.311-311
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    • 2022
  • 전 세계적으로 기후변화 및 산업화로 인해 대규모 홍수, 가뭄, 폭염, 산불 등의 재해가 빈번하게 발생하고 있으며, 이러한 재해 및 재난을 조기에 발견하고 최소화를 위한 대응 체계 및 관리방안의 필요성이 증대되고 있다. 이러한 자연재해들의 특징은 추가 재해를 유발할 수 있다는 것으로 재해의 강도가 증가할 뿐만 아니라 여러 가지 재난 및 재해를 동시에 유발하는 형태로 변화하기 때문에, 단일자연재해 평가 기술을 바탕으로 복합자연재해에 대한 분석 및 감지가 진행되어야 한다. 최근 기후변화로 인한 기상 패턴의 변화 및 가뭄 발생빈도의 증가가 뚜렷하며, 국외에서는 폭염과 가뭄을 고려한 복합자연재해로 'Flash Drought'로 정의된 돌발가뭄에 대한 연구가 이루어지고 있다. 폭염과 가뭄은 단순 강우 부족으로 인한 가뭄, 높은 기온으로 인한 폭염 등이 서로 독립적으로 발생하는 경우와 강우부족과 폭염의 지속으로 인한 상호연관성이 존재하는 복합자연재해 등으로 구분할 수 있다. 돌발가뭄은 강수 부족 또는 폭염이 지속되거나 강도가 높아질 경우, 지면온도가 상승하여 토양수분이 필요 이상으로 증발하여 단기간에 발생하는 초단기 가뭄으로 복합자연재해에 해당하며, 이러한 돌발가뭄은 농업분야에서 작물 생장 및 영농기 활동에 큰 영향을 미치기 때문에 모니터링 및 감지 기술이 필요하다. 본 연구에서는 수문기상학적 요소를 활용하여 폭염 및 가뭄을 고려한 복합자연재해에 대한 상관분석을 수행하였다. 기상청에서 제공하는 기상자료(일최고기온/평균기온/최저기온, 강수량, 상대습도, 일조량 등)에 대한 전국 76개소 대상 기상자료를 구축하였으며, Sentinel, Landsat, MODIS(Moderate Resolution Imaging Spectroradiometer) 등과 같은 위성영상 자료를 구축하여 폭염과 가뭄에 대한 각각의 인자를 선정하고 상관 관계를 분석하였다. 본 연구의 결과는 향후 복합자연재해 감지 및 예측 기술 개발에 활용하여 재해 예방 및 대응에 대한 기초자료로 활용될 수 있을 것으로 판단된다.

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Recoverability analysis of Forest Fire Area Based on Satellite Imagery: Applications to DMZ in the Western Imjin Estuary (위성영상을 이용한 서부임진강하구권역 내 DMZ 산불지역 회복성 분석)

  • Kim, Jang Soo;Oh, Jeong-Sik
    • Journal of The Geomorphological Association of Korea
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    • v.28 no.1
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    • pp.83-99
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    • 2021
  • Burn severity analysis using satellite imagery has high capabilities for research and management in inaccessible areas. We extracted the forest fire area of the DMZ (Demilitarized Zone) in the western Imjin Estuary which is restricted to access due to the confrontation between South and North Korea. Then we analyzed the forest fire severity and recoverability using atmospheric corrected Surface Reflectance Level-2 data collected from Landsat-8 OLI (Operational Land Imagery) / TIRS (Thermal Infrared Sensor). Normalized Burn Ratio (NBR), differenced NBR (dNBR), and Relative dNBR (RdNBR) were analyzed based on changes in the spectral pattern of satellite images to estimate burn severity area and intensity. Also, we evaluated the recoverability after a forest fire using a land cover map which is constructed from the NBR, dNBR, and RdNBR analyzed results. The results of dNBR and RdNBR analysis for the six years (during May 30, 2014 - May 30, 2020) showed that the intensity of monthly burn severity was affected by seasonal changes after the outbreak and the intensity of annual burn severity gradually decreased after the fire events. The regrowth of vegetation was detected in most of the affected areas for three years (until May 2020) after the forest fire reoccurred in May 2017. The monthly recoverability (from April 2014 to December 2015) of forests and grass fields was increased and decreased per month depending on the vegetation growth rate of each season. In the case of annual recoverability, the growth of forest and grass field was reset caused by the recurrence of a forest fire in 2017, then gradually recovered with grass fields from 2017 to 2020. We confirmed that remote sensing was effectively applied to research of the burn severity and recoverability in the DMZ. This study would also provide implications for the management and construction statistics database of the forest fire in the DMZ.

The 2009-based detailed distribution pattern and area of Phragmites communis-dominant and Suaeda japonica-dominant communities on the Suncheon-bay and Beolgyo estuarine wetlands (순천만과 벌교 하구 연안습지의 2009년 기준 갈대 및 칠면초 우세 군집 분포양상과 면적 제시)

  • Hong, Seok Hwi;Chun, Seung Soo;Eom, Jin Ah
    • Journal of Wetlands Research
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    • v.17 no.1
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    • pp.26-37
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    • 2015
  • Halophyte distribution pattern and area in the Suncheon-bay and Beolgyo estuary coastal wetlands were analyzed using KOMPSAT-2 landsat images were taken in 2008 and 2009, and field investigations were fulfilled for confirming the precise boundaries of individual halophyte areas. The salt-marsh vegetation in those areas can be classified mainly into two dominant communities: Suaeda japonica-dominant and Phragmites communis-dominant communities. In order to identify sedimentary characteristics, tidal-flat surface leveling and sedimentary facies analysis had been conducted. The sedimentary facies of marsh area are mostly silty clayey and clay facies with a little seasonal change and its slope is very gentle (0.0007~0.002 in gradient). Phragmites communis and Suaeda japonica communities were distributed in the mud-flat zone between 0.7 m and 1.8 m higher than MSL (mean sea level): zone of 1.1~1.8 m in the former and zone of 0.7~1.3 m in the latter. In the Suncheon-bay estuarine wetland, on the basis of 2009 distribution, Phragmites communis-dominant and Suaeda japonica-dominant communities are about $0.79km^2$ and $0.22km^2$ in distribution area, respectively. On the other hand, Bulgyo estuarine marsh shows that the distribution areas of Phragmites communis-dominant and Suaeda japonica-dominant communities are about $0.31km^2$ and 0.031km2 in distribution area, respectively. Individual 105 and 60 dominant community areas and their distribution patterns can be well defined and indicated in the Suncheon-bay and Bulgyo estuarine marshes, respectively. The distribution pattern and area of hylophyte communities analyzed in this study based on 2008/2009 satellite images would be valuable as a base of future monitoring of salt-marsh related studies in the study area which is the most important salt-marsh research site in Korea.