• Title/Summary/Keyword: 위성레이더

Search Result 302, Processing Time 0.036 seconds

Spatial merging of satellite based soil moisture and in-situ soil moisture using conditional merging technique (조건부 합성방법을 이용한 위성관측 토양수분과 지상관측 토양수분의 합성)

  • Lee, Jaehyeon;Choi, Minha;Kim, Dongkyun
    • Journal of Korea Water Resources Association
    • /
    • v.49 no.3
    • /
    • pp.263-273
    • /
    • 2016
  • This study applied conditional merging (CM) spatial interpolation technique to obtain the satellite and in-situ composite soil moisture data. For the analysis, 24 gages of hourly in-situ data sets from the Rural Development Administration (RDA) of Korea and the satellite soil moisture data retrieved from Advanced Microwave Scanning Radiometer-Earth observing system (AMSR-E) were used. In order to verify the performance of the CM method, leave-one-out cross validation was used. The cross validation result was spatially interpolated to figure out spatial correlation of the CM method. The results derived from this study are as follow: (1) The CM method produced better soil moisture map over Korean Peninsula than AMSR-E did for the over 100 days out of total 113 days considered for the analysis. (2) The method of CM showed high correlation with gage density and better performance on the western side of Korean peninsula due to high spatial gauge density. (3) The performance of CM is not affected by the non-rainy season unlike to AMSR-E data is. Overall, the result of this study indicates that the CM method can be applied for predicting soil moisture at ungaged locations.

Application of SAR DATA to the Study on the Characteristics of Sedimentary Environments in a Tidal Flat (SAR 자료를 이용한 갯벌 퇴적환경 특성 연구)

  • Kim, Kye-Lim;Ryu, Joo-Hyung;Kim, Sang-Wan;Choi, Jong-Kuk
    • Korean Journal of Remote Sensing
    • /
    • v.26 no.5
    • /
    • pp.497-510
    • /
    • 2010
  • In this study, comparisons of the backscattering coefficients and the coherence values which had been extracted from SAR (Synthetic Aperture Radar) images such as JERS-1, ENVISAT and ALOS satellites with surface roughness, surface geometric and soil moisture content were carried out. As the results of analysis using the backscattering coefficient and coherence values from SAR images, the coherence was shown high in the region containing more of mud fraction due to higher viscosity of fine grain-size. A lot of tidal channels were well developed in the Ganghwa tidal flat, affecting the drainage of seawater and subsequent soil moisture content by exposure time of tidal flat. The backscattering coefficient. consequently, appeared to be lower in sand flat and mix flat with decrease of soil moisture. In contrast, most mud flats were distributed at high elevation so that soil moisture was not much influenced by seawater. The backscattering coefficient in mud flat seemed to have a relationship with the density of tidal channel. In addition, lowering backscattering coefficients in the all Ganghwa tidal flat was observed when surface remnant water increased according to the amount of rainfall. The correlation between backscattering coefficient, coherence and sediment environment factors in the Ganghwa tidal flat was investigated. In the future, more quantitative spatial analysis will be helpful to well understand the sedimentary influence of various sediment environment factors.

Baekdu Volcano Lake "Chun-ji" Ice Dynamic Monitoring Using TerraSAR-X Satellite Imagery (TerraSAR-X 위성영상을 활용한 백두산 천지 얼음 면적 변화 모니터링)

  • Park, Sung-Jae;Lee, Seulki;Lee, Chang-Wook
    • Korean Journal of Remote Sensing
    • /
    • v.35 no.2
    • /
    • pp.327-336
    • /
    • 2019
  • The caldera lake "Chun-ji" is located at the summit of Baekdu volcano, which is in the border of China and North Korea. Chun-ji Lake has altitude 2,189 m above sea level. The Chun-ji is freezing in the winter when the water temperature goes down to zero for a year, and it melts in the season when the water temperature goes up again. However,since it is located at a high altitude, there are many cloudy days, and it is difficult to observe with optical images. For this reason, radar images, which are less influenced by weather than optical images, are more effective for observing the ice of heaven and earth. In this study, 75 TerraSAR-X images from chun-ji area were used for analysis from 2015 to 2017, and the calculated ice area and temperature changes were analyzed. As a result, the ice of the caldera lake formed was formed in early December and slowly melted until mid-April. During this period, temperatures in the Samjiyeon area were about $-10^{\circ}C$ when ice was produced, and the temperature was about $0^{\circ}C$ in mid-April when it was thawing. Correlation coefficients between ice surface area and temperature in winter 2015 and 2016, where global ice is produced,show a high correlation of -0.82 and -0.75. In addition to the results of this study, it can be used as an indicator to monitor the volcanic activity by comparing the result of the recent volcanic activity with the result of the increase in water temperature using various imagery.

An Artificial Intelligence Approach to Waterbody Detection of the Agricultural Reservoirs in South Korea Using Sentinel-1 SAR Images (Sentinel-1 SAR 영상과 AI 기법을 이용한 국내 중소규모 농업저수지의 수표면적 산출)

  • Choi, Soyeon;Youn, Youjeong;Kang, Jonggu;Park, Ganghyun;Kim, Geunah;Lee, Seulchan;Choi, Minha;Jeong, Hagyu;Lee, Yangwon
    • Korean Journal of Remote Sensing
    • /
    • v.38 no.5_3
    • /
    • pp.925-938
    • /
    • 2022
  • Agricultural reservoirs are an important water resource nationwide and vulnerable to abnormal climate effects such as drought caused by climate change. Therefore, it is required enhanced management for appropriate operation. Although water-level tracking is necessary through continuous monitoring, it is challenging to measure and observe on-site due to practical problems. This study presents an objective comparison between multiple AI models for water-body extraction using radar images that have the advantages of wide coverage, and frequent revisit time. The proposed methods in this study used Sentinel-1 Synthetic Aperture Radar (SAR) images, and unlike common methods of water extraction based on optical images, they are suitable for long-term monitoring because they are less affected by the weather conditions. We built four AI models such as Support Vector Machine (SVM), Random Forest (RF), Artificial Neural Network (ANN), and Automated Machine Learning (AutoML) using drone images, sentinel-1 SAR and DSM data. There are total of 22 reservoirs of less than 1 million tons for the study, including small and medium-sized reservoirs with an effective storage capacity of less than 300,000 tons. 45 images from 22 reservoirs were used for model training and verification, and the results show that the AutoML model was 0.01 to 0.03 better in the water Intersection over Union (IoU) than the other three models, with Accuracy=0.92 and mIoU=0.81 in a test. As the result, AutoML performed as well as the classical machine learning methods and it is expected that the applicability of the water-body extraction technique by AutoML to monitor reservoirs automatically.

An Efficient Interferometric Radar Altimeter (IRA) Signal Processing to Extract Precise Three-dimensional Ground Coordinates (정밀 3차원 지상좌표 추출을 위한 IRA의 효율적인 신호처리 기법)

  • Lee, Dong-Taek;Jung, Hyung-Sup;Yoon, Geun-Won
    • Korean Journal of Remote Sensing
    • /
    • v.27 no.5
    • /
    • pp.507-520
    • /
    • 2011
  • Conventional radar altimeter system measured directly the distance between the satellite and the ocean surface and frequently used by aircraft for approach and landing. The radar altimeter is good at flat surface like sea whereas it is difficult to determine precise three dimensional ground coordinates because the ground surface, unlike ocean, is very indented. To overcome this drawback of the radar altimeter, we have developed and validated the interferometric radar altimeter signal processing which is combined with new synthetic aperture and interferometric signal processing algorithm to extract precise three-dimensional ground coordinates. The proposed algorithm can accurately measure the three dimensional ground coordinates using three antennas. In a set of 70 simulations, the averages of errors in x, y and z directions were approximately -0.40 m, -0.02 m and 4.22 m, respectively and the RMSEs were about 3.40 m, 0.30 m and 6.20 m, respectively. The overall results represent that the proposed algorithm is effective for accurate three dimensional ground positioning.

Gravity-Geologic Prediction of Bathymetry in the Drake Passage, Antarctica (Gravity-Geologic Method를 이용한 남극 드레이크 해협의 해저지형 연구)

  • 김정우;도성재;윤순옥;남상헌;진영근
    • Economic and Environmental Geology
    • /
    • v.35 no.3
    • /
    • pp.273-284
    • /
    • 2002
  • The Gravity-Geologic Method (GGM) was implemented for bathymetric determinations in the Drake Passage, Antarctica, using global marine Free-air Gravity Anomalies (FAGA) data sets by Sandwell and Smith (1997) and local echo sounding measurements. Of the 6548 bathymetric sounding measurements, two thirds of these points were used as control depths, while the remaining values were used as checkpoints. A density contrast of 9.0 gm/㎤ was selected based on the checkpoints predictions with changes in the density contrast assumed between the seawater and ocean bottom topographic mass. Control depths from the echo soundings were used to determine regional gravity components that were removed from FAGA to estimate the gravity effects of the bathymetry. These gravity effects were converted to bathymetry by inversion. In particular, a selective merging technique was developed to effectively combine the echo sounding depths with the GGM bathymetiy to enhance high frequency components along the shipborne sounding tracklines. For the rugged bathymetry of the research area, the GGM bathymetry shows correlation coefficients (CC) of 0.91, 0.92, and 0.85 with local shipborne sounding by KORDI, GEODAS, and a global ETOPO5 model, respectively. The enhanced GGM by selective merging shows imploved CCs of 0.948 and 0.954 with GEODAS and Smith & Sandwell (1997)'s predictions with RMS differences of 449.8 and 441.3 meters. The global marine FAGA data sets and other bathymetric models ensure that the GGM can be used in conjunction with shipborne bathymetry from echo sounding to extend the coverage into the unmapped regions, which should generate better results than simply gridding the sparse data or relying upon lower resolution global data sets such as ETOPO5.

Soil moisture estimation using the water cloud model and Sentinel-1 & -2 satellite image-based vegetation indices (Sentinel-1 & -2 위성영상 기반 식생지수와 Water Cloud Model을 활용한 토양수분 산정)

  • Chung, Jeehun;Lee, Yonggwan;Kim, Jinuk;Jang, Wonjin;Kim, Seongjoon
    • Journal of Korea Water Resources Association
    • /
    • v.56 no.3
    • /
    • pp.211-224
    • /
    • 2023
  • In this study, a soil moisture estimation was performed using the Water Cloud Model (WCM), a backscatter model that considers vegetation based on SAR (Synthetic Aperture Radar). Sentinel-1 SAR and Sentinel-2 MSI (Multi-Spectral Instrument) images of a 40 × 50 km2 area including the Yongdam Dam watershed of the Geum River were collected for this study. As vegetation descriptor of WCM, Sentinel-1 based vegetation index RVI (Radar Vegetation Index), depolarization ratio (DR), and Sentinel-2 based NDVI (Normalized Difference Vegetation Index) were used, respectively. Forward modeling of WCM was performed by 3 groups, which were divided by the characteristics between backscattering coefficient and soil moisture. The clearer the linear relationship between soil moisture and the backscattering coefficient, the higher the simulation performance. To estimate the soil moisture, the simulated backscattering coefficient was inverted. The simulation performance was proportional to the forward modeling result. The WCM simulation error showed an increasing pattern from about -12dB based on the observed backscattering coefficient.

A Study on Monitoring Surface Displacement Using SAR Data from Satellite to Aid Underground Construction in Urban Areas (위성 SAR 자료를 활용한 도심지 지하 교통 인프라 건설에 따른 지표 변위 모니터링 적용성 연구)

  • Woo-Seok Kim;Sung-Pil Hwang;Wan-Kyu Yoo;Norikazu Shimizu;Chang-Yong Kim
    • The Journal of Engineering Geology
    • /
    • v.34 no.1
    • /
    • pp.39-49
    • /
    • 2024
  • The construction of underground infrastructure is garnering growing increasing research attention owing to population concentration and infrastructure overcrowding in urban areas. An important associated task is establishing a monitoring system to evaluate stability during infrastructure construction and operation, which relies on developing techniques for ground investigation that can evaluate ground stability, verify design validity, predict risk, facilitate safe operation management, and reduce construction costs. The method proposed here uses satellite imaging in a cost-effective and accurate ground investigation technique that can be applied over a wide area during the construction and operation of infrastructure. In this study, analysis was performed using Synthetic Aperture Radar (SAR) data with the time-series radar interferometric technique to observe surface displacement during the construction of urban underground roads. As a result, it was confirmed that continuous surface displacement was occurring at some locations. In the future, comparing and analyzing on-site measurement data with the points of interest would aid in confirming whether displacement occurs due to tunnel excavation and assist in estimating the extent of excavation impact zones.

Rainfall Characteristics in the Tropical Oceans: Observations using TRMM TMI and PR (열대강우관측(TRMM) 위성의 TMI와 PR에서 관측된 열대해양에서의 강우 특성)

  • Seo, Eun-Kyoung
    • Journal of the Korean earth science society
    • /
    • v.33 no.2
    • /
    • pp.113-125
    • /
    • 2012
  • The estimations of the surface rain intensity and rain-related physical variables derived from two independent Tropical Rainfall Measuring Mission (TRMM) satellite sensors, TRMM Microwave Imager (TMI) and Precipitation Radar (PR), were compared over four different oceans. The precipitating clouds developed most frequently in the warmest sea surface temperature (SST) region of the west Pacific, which is 1.5 times more frequent than in the east Pacific and the tropical Atlantic oceans. However, the east Pacific exhibited the most intense rain intensity for the convective and mixed rain types while the tropical Atlantic showed the most intense rain intensity for all TMI rainy pixels. It was found that the deviation of TMI-derived rain rate yielded a big difference in region-to-region and rain type-to-type if the PR rain intensity value is assumed to be closer to the truth. Furthermore, the deviation by rain types showed opposite signs between convective and non-convective rain types. It was found that the region-to-region deviation differences reached more than 200% even though the selected tropical oceans have relatively similar geophysical environments. Therefore, the validation for the microwave rain estimation needs to be performed according to both rain types and climate regimes, and it also requires more sophisticated TMI algorithm which reflects the locality of rainfall characteristics.

Persistent Scatterer Selection and Network Analysis for X-band PSInSAR (X-band PSInSAR를 위한 고정산란체 추출 및 네트워크 분석 기법)

  • Kim, Sang-Wan;Cho, Min-Ji
    • Korean Journal of Remote Sensing
    • /
    • v.27 no.5
    • /
    • pp.521-534
    • /
    • 2011
  • The high-resolution X-band SAR systems such as COSMO-SkyMED and TerraSAR-X have been launched recently. In addition KOMPSAT-5 will be launched in the early of 2012. In this study we developed the new method for persistent scatterer candidate (PSC) selection and network construction, which is more suitable for PSInSAR analysis using multi-temporal X-band SAR data. PSC selection consists in two main steps: first, selection of initial PSCs based on amplitude dispersion index, mean amplitude, mean coherence. second, selection of final PSCs based on temporal coherence directly estimated from network analysis of initial PSCs. To increase the stability of network the Multi- TIN and complex network for non-urban area were addressed as well. The proposed algorithm was applied to twenty-one TerraSAR-X SAR of New Orleans. As a result many PSs were successfully extracted even in non-urban area. This research can be used as the practical application of KOMPSAT-5 for surface displacement monitoring using X-band PSInSAR.