• Title/Summary/Keyword: Landsat-8

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A Study for Estimation of High Resolution Temperature Using Satellite Imagery and Machine Learning Models during Heat Waves (위성영상과 머신러닝 모델을 이용한 폭염기간 고해상도 기온 추정 연구)

  • Lee, Dalgeun;Lee, Mi Hee;Kim, Boeun;Yu, Jeonghum;Oh, Yeongju;Park, Jinyi
    • Korean Journal of Remote Sensing
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    • v.36 no.5_4
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    • pp.1179-1194
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    • 2020
  • This study investigates the feasibility of three algorithms, K-Nearest Neighbors (K-NN), Random Forest (RF) and Neural Network (NN), for estimating the air temperature of an unobserved area where the weather station is not installed. The satellite image were obtained from Landsat-8 and MODIS Aqua/Terra acquired in 2019, and the meteorological ground weather data were from AWS/ASOS data of Korea Meteorological Administration and Korea Forest Service. In addition, in order to improve the estimation accuracy, a digital surface model, solar radiation, aspect and slope were used. The accuracy assessment of machine learning methods was performed by calculating the statistics of R2 (determination coefficient) and Root Mean Square Error (RMSE) through 10-fold cross-validation and the estimated values were compared for each target area. As a result, the neural network algorithm showed the most stable result among the three algorithms with R2 = 0.805 and RMSE = 0.508. The neural network algorithm was applied to each data set on Landsat imagery scene. It was possible to generate an mean air temperature map from June to September 2019 and confirmed that detailed air temperature information could be estimated. The result is expected to be utilized for national disaster safety management such as heat wave response policies and heat island mitigation research.

A Study on the Possibility of Geothermal Resources Assessment Using Landsat 7 ETM+ (Landsat 7 ETM+를 이용한 지열자원 평가 가능성 연구)

  • Oh, Il-Hwan;Lee, Tae-Jong;Kim, Kwang-Eun;Suh, Man-Cheol;Hong, Suk-Young
    • Proceedings of the KSRS Conference
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    • 2008.03a
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    • pp.113-118
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    • 2008
  • 본 연구는 Landsat 7 ETM+를 이용한 지열자원 평가 가능성 연구로써, 위성영상의 열적외 밴드에서 추출된 지표온도와 지열자료의 비교를 통해 위성영상이 초기 지열 탐사에 적용 가능한지를 평가하기 위하여 실시하였다. 지열자원 부존 가능성 평가를 위해 경상도지역(114-35)의 여름시기영상(2001년8월24일)과 겨울시기영상(2000년3월14일)사이의 DN(Digital Number) 값을 이용하였으며, 두 시기영상은 시추공 온도자료 및 지형자료와 함께 비교 분석을 실시하였다. 영상에서 지표온도 추출을 위해 1) NASA에서 제공하는 지표온도 산출 경험식 ( T = K $_2$ / ln ( K $_1$ / L $_{\lambda}$ + 1 ) )을 이용한 방법과 2) 기상청에서 제공하는 실제 지표면온도 관측자료(n=7)를 이용해 영상의 화소(Pixel) 값을 계산하여 실측값과 비교하였다. 3월과 8월 모두 Ground Truth 방법에 따라 추정한 지표면 온도값이 실측값과 더 가깝게 나타났고, 특히 3월은 NASA의 경험식을 이용했을 때 보다 실측 지표면 온도에 훨씬 더 가까운 것으로 나타났다. 지표온도의 일변화(Diurnal ${\triangle}$T)는 지표 열물성과 밀접한 관련이 있으므로, 일변화(Diurnal ${\triangle}$T) 보다는 지열의 영향이 더 클 것으로 기대되는 계절변화(Seasonal ${\triangle}$T)를 이용하여 지열 자료와 비교해 보았다. 그 결과, 계절변화(Seasonal ${\triangle}$T)는 고도에 영향을 받으며, 일사량에 의한 차이는 거의 일정하게 나타났다. 위성영상에서 계절변화(Seasonal ${\triangle}$T)와 심도 20m 온도를 비교해 본 결과결정계수(R$^2$)는 0.46으로 낮지만 심도 20m 온도가 높을수록 계절변화(Seasonal ${\triangle}$T)는 작아지는 경향을 보여 지열자원 탐사에 있어 위성영상 적용 가능성을 볼 수 있었다. 이번 연구는 기초단계로서 두 시기 위성영상을 이용하여 초기 지열자원탐사에 가능성만을 연구했지만, 지형과 특히 토지피복(함수량 등)에 의한 영향에 대해 좀 더 심도 있는 연구가 요구된다.

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Analysis of Impacts of Land Cover Change on Runoff Using HSPF Model (HSPF 모형을 이용한 토지피복변화에 따른 유출 변화 분석)

  • Park, Min-Ji;Kwon, Hyung-Joong;Kim, Seong-Joon
    • Journal of Korea Water Resources Association
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    • v.38 no.6 s.155
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    • pp.495-504
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    • 2005
  • The objective of this study is to estimate the impacts of land cover change on the runoff behavior using Hydrologic Simulation Program-Fortran (HSPF) model and Landsat images. Land cover maps were prepared using three every ten years from 1980 to 2000 of the upper watershed ($258\;km^2$) of Gyeongan stream. Hydrologic parameters of HSPF were calibrated using observed data (1999 - 2000) and validated using observed data (2001, 2003) at Gyeongan gauge station. The simulation results showed that runoff volume and peak rate increased as $15.0\;km^2$ forest areas decreased and $19.3\;km^2$ urban areas increased for 20 years land use changes. The runoff volume showed a higher rate of increase in wet year (2003, 1709.4 mm) than in dry year (2001, 871.2 mm). The peak runoff increased $13.3\;\%$ in normal year (2000, 1257.3 mm) because the year has the highest rain intensity (241.3 mm/hr) among the test years. The runoff volume of a dry season and a wet season (May - September) in normal year 2000 increased $4.4\;\%$ and decreased $8.1\;\%$, respectively.

Generation of Time-Series Data for Multisource Satellite Imagery through Automated Satellite Image Collection (자동 위성영상 수집을 통한 다종 위성영상의 시계열 데이터 생성)

  • Yunji Nam;Sungwoo Jung;Taejung Kim;Sooahm Rhee
    • Korean Journal of Remote Sensing
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    • v.39 no.5_4
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    • pp.1085-1095
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    • 2023
  • Time-series data generated from satellite data are crucial resources for change detection and monitoring across various fields. Existing research in time-series data generation primarily relies on single-image analysis to maintain data uniformity, with ongoing efforts to enhance spatial and temporal resolutions by utilizing diverse image sources. Despite the emphasized significance of time-series data, there is a notable absence of automated data collection and preprocessing for research purposes. In this paper, to address this limitation, we propose a system that automates the collection of satellite information in user-specified areas to generate time-series data. This research aims to collect data from various satellite sources in a specific region and convert them into time-series data, developing an automatic satellite image collection system for this purpose. By utilizing this system, users can collect and extract data for their specific regions of interest, making the data immediately usable. Experimental results have shown the feasibility of automatically acquiring freely available Landsat and Sentinel images from the web and incorporating manually inputted high-resolution satellite images. Comparisons between automatically collected and edited images based on high-resolution satellite data demonstrated minimal discrepancies, with no significant errors in the generated output.

A Study on the Detection Method of Red Tide Area in South Coast using Landsat Remote Sensing (Landsat 위성자료를 이용한 남해안 적조영역 검출기법에 관한 연구)

  • Sur, Hyung-Soo;Song, In-Ho;Lee, Chil-Woo
    • Journal of the Korean Association of Geographic Information Studies
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    • v.9 no.4
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    • pp.129-141
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    • 2006
  • The image data amount is increasing rapidly that used geography, sea information etc. with great development of a remote sensing technology using artificial satellite. Therefore, people need automatic method that use image processing description than macrography for analysis remote sensing image. In this paper, we propose that acquire texture information to use GLCM(Gray Level Co-occurrence Matrix) in red tide area of artificial satellite remote sensing image, and detects red tide area by PCA(principal component analysis) automatically from this data. Method by sea color that one feature of remote sensing image of existent red tide area detection was most. but in this paper, we changed into 2 principal component accumulation images using GLCM's texture feature information 8. Experiment result, 2 principal component accumulation image's variance percentage is 90.4%. We compared with red tide area that use only sea color and It is better result.

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Change Detection Comparison of Multitemporal Infrared Satellite Imagery Using Relative Radiometric Normalization (상대 방사 정규화를 이용한 다시기 적외 위성영상의 변화탐지 비교)

  • Han, Dongyeob;Song, Jeongheon;Byun, Younggi
    • Korean Journal of Remote Sensing
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    • v.33 no.6_3
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    • pp.1179-1185
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    • 2017
  • The KOMPSAT-3A satellite acquires high-resolution MWIR images twice a day compared to conventional Earth observing satellites. New radiometric information of Earth's surface can be provided due to different characteristics from existing SWIR images or TIR images. In this study, the difference image of multitemporal images was generated and compared with existing infrared images to find the characteristics of KOMPSAT-3A MWIR satellite images. A co-registration was performed and the difference between pixel values was minimized by using PIFs (Pseudo Invariant Features) pixel-based relative normalization. The experiment using Sentinel-2 SWIR image, Landsat 8 TIR image, and KOMPSAT-3A MWIR image showed that the distinction between artifacts in the difference image of KOMPSAT-3A is prominent. It is believed that the utilization of KOMPSAT-3A MWIR images can be improved by using the characteristics of IR image.

Seasonal Variation of Water Temperature Before and After Weir Construction Using Satellite Image in the Nakdong River (낙동강유역에서 위성영상을 이용한 보 건설 전후 수온의 계절변화)

  • Kim, Sang-Woo;Kim, Hae-Dong;Lim, Jin-Wook;Ahn, Ji-Suk
    • Journal of Environmental Science International
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    • v.24 no.11
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    • pp.1417-1430
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    • 2015
  • In this study we were to explore the seasonal variation of water temperature distributions before and after weir construction at Gumi, Chilgok, Gangjung(Goryung), Dalsung in the Nakdong River using Landsat satellite images. Relationship between in-situ water temperature and radiance values of Landsat-5, 7, 8 satellite images showed high correlation. Seasonal variation of water temperature in Nakdong River showed that the fluctuation ranges of water temperature before weir construction were larger than those after weir construction. This indicated that the variation of water temperature is due to the difference of heat storage volume by weir construction and dredging work. In particular, the water temperature after weirs construction in autumn was 4-8 times lower than that before weirs construction. Water temperature after weir construction decreased in spring and summer at the downstream of Gumi weir and Gangjung(Goryung) weir, and the upstream of Dalsung weir. In autumn and winter, the water temperature after weir construction increased in the upstream and downstream of the whole weirs except upstream of Gumi weir. Relationship between water temperature and meteorological elements (air temperature, wind speed, sunshine, radiation) showed high correlation of above 94% in air temperature, and then radiation was high correlation before and after 65%.

Analysis about technology requirements for Development of Disaster Detecting Satellite Sensor (재난전조감지를 위한 위성센서 기술요구조건 분석)

  • Woo, Han-Byol;Joo, Young-Do;Choi, Myung-Jin;Jang, Su-Min
    • The Journal of the Korea institute of electronic communication sciences
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    • v.10 no.11
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    • pp.1205-1216
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    • 2015
  • Since concentration of greenhouse gas increases continuously from human's fossil fuel use, urbanization, and cultivation, it is trend that climate change is appearing. In Addition, in 20th century, occurrence of disaster is accidental and huge, and damage level also increases gradually. Therefore, in order to preserve the territory and to protect people's life and property against new type disasters, disaster detection satellite (payloads) development is required urgently. In this paper, we conduct a research and development for the prompt preemptive action when occurred a disaster, in particularly, about the disaster observation optimized at Korea's geographical features for the irregular future disasters. For the payload design which is specialized detect disasters, we create a tech tree of satellite imagery applications based 10 disaster types, and analyze the satellite sensor technologies referred to Landsat-8, Worldview-3 and ALOS-2.

Lithological and Structural Lineament Mapping from Landsat 8 OLI Images in Ras Kammouna Arid Area (Eastern Anti-Atlas, Morocco)

  • Es-Sabbar, Brahim;Essalhi, Mourad;Essalhi, Abdelhafid;Mhamdi, Hicham Si
    • Economic and Environmental Geology
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    • v.53 no.4
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    • pp.425-440
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    • 2020
  • The study area is located in the southern part of the M'aider Paleozoic basin in the Moroccan Eastern Anti-Atlas. It is an arid region, characterized by minimal vegetation cover, which can provide an ideal environment to apply remote sensing. In this study, remote sensing and field investigations were integrated for lithological and structural lineaments mapping. The Landsat 8 OLI data were processed in order to understand the role of lithology and geological structures in the distribution of mineral deposits in the study area. To achieve this purpose, the Color Composite (CC), the Principal Component Analysis (PCA) and Band Rationing transformation (BR) tests were performed. The results of remote sensing techniques coupled with field investigations have shown that the zones of high lineaments densities are highly correlated with the occurrences of barite mineralization. These findings depict a spatial relationship between structural lineaments and the mineralization distribution zones. Therefore, the barite and Iron oxides mineralization veins, which occur mainly in the Ras Kammouna district, seem to have a structural control. The methodological approach used in this study examining lithological mapping and lineament extractions can be used to explore mineral deposits in arid regions to a high degree of efficiency.

Matching Points Extraction Between Optical and TIR Images by Using SURF and Local Phase Correlation (SURF와 지역적 위상 상관도를 활용한 광학 및 열적외선 영상 간 정합쌍 추출)

  • Han, You Kyung;Choi, Jae Wan
    • Journal of Korean Society for Geospatial Information Science
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    • v.23 no.1
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    • pp.81-88
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    • 2015
  • Various satellite sensors having ranges of the visible, infrared, and thermal wavelengths have been launched due to the improvement of hardware technologies of satellite sensors development. According to the development of satellite sensors with various wavelength ranges, the fusion and integration of multisensor images are proceeded. Image matching process is an essential step for the application of multisensor images. Some algorithms, such as SIFT and SURF, have been proposed to co-register satellite images. However, when the existing algorithms are applied to extract matching points between optical and thermal images, high accuracy of co-registration might not be guaranteed because these images have difference spectral and spatial characteristics. In this paper, location of control points in a reference image is extracted by SURF, and then, location of their corresponding pairs is estimated from the correlation of the local similarity. In the case of local similarity, phase correlation method, which is based on fourier transformation, is applied. In the experiments by simulated, Landsat-8, and ASTER datasets, the proposed algorithm could extract reliable matching points compared to the existing SURF-based method.