Sentinel-1 & -2 위성영상 기반 식생지수와 Water Cloud Model을 활용한 토양수분 산정

정지훈,이용관,김진욱,장원진,김성준 한국수자원학회 2023 한국수자원학회논문집 Vol.56 No.3

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. 본 연구에서는 합성개구레이더(Synthetic Aperture Radar, SAR) 기반의 식생을 고려하는 후방산란모델 Water Cloud Model (WCM)을 활용한 토양수분 산정 연구를 수행하였다. 금강 상류의 용담댐유역을 포함한 40 × 50 km2 영역의 Sentinel-1 SAR 및 Sentinel-2 MSI (Multi-Spectral Instrument) 영상을 수집하여 연구에 활용하였다. WCM의 식생변수로는 Sentinel-1 기반의 식생지수 RVI (Radar Vegetation Index), 탈분극비(Depolarization Rario, DR)와 Sentinel-2 기반의 NDVI (Normalized Difference Vegetation Index)를 활용하였다. WCM의 정모델링(forward modeling)은 토양수분과 후방산란계수의 특성이 유사한 3개 Group으로 나누어 수행하였다. 토양수분과 후방산란계수의 선형적인 관계가 명확할수록 Group의 모의 성능이 더 높게 나타났으며, 식생지수 별로는 NDVI, RVI, DR 순으로 정확도가 높았다. 토양수분을 모의하기 위해 모의된 후방산란계수를 반전(inversion)하였으며, 모의 성능은 정모델링 결과와 비례하였다. WCM 모의의 오류는 실측 후방산란계수 기준 약 -12dB를 기점으로 증가하는 양상을 보였다.

Risk assessment model for water and mud inrush in deep and long tunnels based on normal gray cloud clustering method

Tian-zheng Li,Xiao-li Yang 대한토목학회 2018 KSCE JOURNAL OF CIVIL ENGINEERING Vol.22 No.5

In terms of the frequent occurrence and much trouble in governance of the disaster caused by water and mud inrush in deep andlong tunnels, the risk assessment model based on normal grey cloud clustering method was proposed. Taking the Jigongling Tunnelof Fanba Expressway as an example, firstly the evaluation target was divided into 8 clustering indices and 4 grey categoriesaccording to the grey clustering method. In order to avoid the defects that the traditional whitenization weight functions could notgive a good description of system's randomness and ambiguity, the cloud model was introduced to improve it. Then the whitenizationweight values were discretized by using the one-dimensional forward cloud generator to simulate the uncertainties in engineering,and the normal grey cloud whitenization weight functions were established. Afterwards, combined with the engineering data ofJigongling Tunnel collected on site, the clustering weight of each clustering index was analyzed under specific engineering and theclustering coefficient of the target was determined. Lastly the risk of water and mud inrush in Jigongling Tunnel was evaluated usingthe model. The results, which showed that the risk of water and mud inrush in target D1, D2 and D3 was respectively medium,extremely high and high, were compared with the excavation data. The two coincided with each other well which indicated that themodel had a certain engineering value and could provide reference for related engineering.

A Modified Water-Cloud Model With Leaf Angle Parameters for Microwave Backscattering From Agricultural Fields

Soon-Koo Kweon,Yisok Oh IEEE 2015 IEEE transactions on geoscience and remote sensing Vol.53 No.5

<P>This paper presents the development of an accurate and simple scattering model for radar backscatters of agricultural fields. We modified the water-cloud model (WCM) by adding new parameters (the average and standard deviation of leaf angle distribution) to accurately estimate the backscattering coefficients with the angular effect of scattering particles in a vegetation canopy. A relatively accurate radiative transfer model (RTM) and field measurements were used in this modification. The accuracy of the RTM was verified with the C-band ground-based scatterometer data of a cornfield, the X-band synthetic aperture radar data and ground-based scatterometer data of a bean field, and the in situ measured ground-truth data of those fields. The newly modified WCM (MWCM) was also verified with the measurement data. It was found that the root-mean-square errors between the MWCM and the measurements were less than 1.5 dB for all backscatter data from the agricultural vegetation fields.</P>

레이더 및 광학 위성영상 식생지수를 이용한 Water Cloud Model 기반 토양수분 추정 연구

정지훈 ( Jeehun Chung ),김원진 ( Wonjin Kim ),우소영 ( Soyoung Woo ),이용관 ( Yonggwan Lee ),김성준 ( Seongjoon Kim ) 한국농공학회 2022 한국농공학회 학술대회초록집 Vol.2022 No.-

본 연구의 목적은 레이더 기반의 지표 후방산란모델 Water Cloud Model(WCM)을 기반으로 레이더 및 광학 위성영상의 식생지수를 이용해 토양수분을 추정하는 것이다. 연구지역은 금강 유역 상류 40×50 km² 면적을 대상으로 하였으며, 해당 지역을 포함하는 Sentinel-1 SAR(Synthetic Aperture Radar) 및 Sentinel-2 MSI(Multi-Spectral Instrument) 영상을 각 12일, 10일 간격으로 4년 간(2017~2020) 수집하였다. 위성영상의 전처리는 SNAP(SentiNel Application Platform)을 활용하여 Sentinel-1의 VH 및 VV 편파 영상, Sentinel-2의 적색 및 근적외선 파장대 영상을 추출하였다. 또한, 추정된 토양수분의 검증을 위해 6개 지점에서 지표 하 10 cm에서 TDR(Time Domain Reflectometry)로 측정된 토양수분 자료를 수집하였다. Forward modeling을 위해 식생지수 NDVI(Normalized Difference Vegetation Index), RVI(Radar Vegetation Index) 및 탈분극비(Depolarization Ratio, DR)를 활용해 VV 편파 후방산란계수를 모의하였다. WCM의 매개변수는 비선형최소제곱법(Nonlinear least square)을 활용해 보정하였다. Forward modeling 결과 NDVI, DR, RVI 순으로 식생층에 의한 양방향 감쇠가 잘 설명되었으며, 모의된 VV 편파 후방산란계수는 Sentinel-1 VV 편파 후방산란계수와의 비교를 통해 검증하였다. 검증된 후방산란계수를 inversion 하여 토양수분으로 변환하였고, 추정토양수분과 실측 토양수분은 NDVI 0.6 이상에서 bias가 급격히 증가하는 경향을 나타냈다.

레이더 및 광학 위성영상 식생지수를 이용한 Water Cloud Model 기반 토양수분 추정 연구

정지훈 ( Jeehun Chung ),김원진 ( Wonjin Kim ),우소영 ( Soyoung Woo ),이용관 ( Yonggwan Lee ),김성준 ( Seongjoon Kim ) 한국농공학회 2022 한국농공학회 학술대회초록집 Vol.2022 No.-

본 연구의 목적은 레이더 기반의 지표 후방산란모델 Water Cloud Model(WCM)을 기반으로 레이더 및 광학 위성영상의 식생지수를 이용해 토양수분을 추정하는 것이다. 연구지역은 금강 유역 상류 40×50 km² 면적을 대상으로 하였으며, 해당 지역을 포함하는 Sentinel-1 SAR(Synthetic Aperture Radar) 및 Sentinel-2 MSI(Multi-Spectral Instrument) 영상을 각 12일, 10일 간격으로 4년 간(2017~2020) 수집하였다. 위성영상의 전처리는 SNAP(SentiNel Application Platform)을 활용하여 Sentinel-1의 VH 및 VV 편파 영상, Sentinel-2의 적색 및 근적외선 파장대 영상을 추출하였다. 또한, 추정된 토양수분의 검증을 위해 6개 지점에서 지표 하 10 cm에서 TDR(Time Domain Reflectometry)로 측정된 토양수분 자료를 수집하였다. Forward modeling을 위해 식생지수 NDVI(Normalized Difference Vegetation Index), RVI(Radar Vegetation Index) 및 탈분극비(Depolarization Ratio, DR)를 활용해 VV 편파 후방산란계수를 모의하였다. WCM의 매개변수는 비선형최소제곱법(Nonlinear least square)을 활용해 보정하였다. Forward modeling 결과 NDVI, DR, RVI 순으로 식생층에 의한 양방향 감쇠가 잘 설명되었으며, 모의된 VV 편파 후방산란계수는 Sentinel-1 VV 편파 후방산란계수와의 비교를 통해 검증하였다. 검증된 후방산란계수를 inversion 하여 토양수분으로 변환하였고, 추정토양수분과 실측 토양수분은 NDVI 0.6 이상에서 bias가 급격히 증가하는 경향을 나타냈다.

레이다를 이용한 토양 수분함유량 측정에서 초목 층의 영향 분석

박신명(Sinmyong Park),오이석(Yisok Oh) 한국전자파학회 2016 한국전자파학회논문지 Vol.27 No.7

본 논문에서는 초목 층 산란모델과 지표면 산란 모델을 이용하여 초목 층에서 수분함유량 측정에 초목 층과 레이다 파라미터가 갖는 영향에 대하여 분석하였다. 1<SUP>st</SUP>-order RTM(Radiative Transfer Model)을 이용하여 여러 상태의 초목 층밀도와 입사각, 주파수, 편파를 갖는 데이터베이스를 생성하고, WCM(Water Cloud Model)과 Oh 모델을 이용하여 후방산란계수로부터 지표면 수분함유량을 추출하였다. 수분함유량 추출 에러를 예측하기 위해 추출한 수분함유량과 RTM의 입력 변수인 수분함유량을 비교하였다. 수분함유량 추출 에러로부터 초목 층에서의 수분함유량 측정에서 초목 층 밀도와 입사각, 주파수, 편파에 따른 초목 층과 레이다 파라미터의 영향을 분석하였다. This paper presents the effect of vegetation layer and radar parameters on soil moisture measurement using the vegetation layer scattering model and surface scattering model. The database of backscattering coefficients for various vegetation layer densities, incidence angles, frequencies, and polarizations is generated using 1<SUP>st</SUP>-order RTM(Radiative Transfer Model). Then, surface soil moisture contents were estimated from the backscattering coefficients in the database using the WCM(Water Cloud Model) and Oh model. The retrieved soil moisture contents were compared with the soil moisture contents in the input parameters of the RTM to estimate the retrieval errors. The effects of vegetation layer and radar parameters on soil moisture measurement are analyzed using the retrieval errors.

An Integrated Evaluation Method for the Grouting Effect in Karst Areas

Qing Jin,Zehua Bu,Dongdong Pan,Haiyan Li,Zhaofeng Li,Yichi Zhang 대한토목학회 2021 KSCE Journal of Civil Engineering Vol.25 No.8

Our proposed integrated evaluation method for the grouting effect in karst areas is based on the cloud model (CM), the analytic hierarchical process (AHP), and a fuzzy comprehensive evaluation system. Our method fully considers the fuzziness and randomness of the evaluation indices, and bridges the gap between qualitative information and a quantitative evaluation value. The evaluation index system for the grouting effect is established by integrating metrics related to the construction technology, apparent parameters, and observational data from inspection holes and geophysical exploration techniques. First, the weight of each index is calculated using the AHP, which has been modified by the CM. Then, we calculate the cloud model membership degree for each index. Finally, we determine the comprehensive evaluation level by examining the similarity measures between the various cloud models. In this case study, we use our integrated method to evaluate the initial results of the grouting treatment project in the China Resources Cement (Pingnan) Limestone Mine. Our results are validated by subsequent monitoring results for this project. This study provides valuable insight into the treatment of water inflow in karst areas.

Soil moisture retrieval in farmland using C-band SAR and optical data

Xin Zhao,Ni Huang,Zheng Niu,Venkatesh Raghavan,Xianfeng Song 대한공간정보학회 2017 Spatial Information Research Vol.25 No.3

Soil moisture retrieval in vegetation-covered area with space borne synthetic aperture radar is a challenging process due to the impact of vegetation on the multiple scattering of electromagnetic wave. In this paper, a semi-empirical method is proposed to estimate farmland soil moisture by active microwave remote sensing and optical remote sensing. By integrating the vegetation water content estimated from optical data and thermal infrared data into a coupling model based on a water–cloud model, the influence of vegetation on microwave backscattering coefficient was eliminated and thus soil moisture in vegetation-covered area was accurately retrieved. The experiment of soil moisture retrieval was carried out using Radarsat-2 and Landsat 8 datasets in western Great Khingan Mountains, Inner Mongolia, China. The research showed that the accuracy of the coupling model is high and the R2 is up to 0.69 using HH polarization. Moreover, the effects of crop types on soil moisture retrieval, particularly barley, could also be distinguished using the coupling model.

An Empirical Model for Backscattering Coefficients of Vegetation Fields at 5.4 GHz

오이석,Chang Jisung Geba,Shoshany Maxim 한국전자파학회 2022 Journal of Electromagnetic Engineering and Science Vol.22 No.2

A new, simple empirical model for microwave backscattering from vegetation fields at 5.4 GHz is proposed in this paper. First, a modified radiative transfer model (RTM) is used to generate a database of multi-polarized backscattering coefficients of various vegetation fields at 5.4 GHz with wide ranges of vegetation biomasses and soil moistures. Second, we propose a functional form of an empirical model that is a simplified water cloud model (WCM) after closely examining the behaviors of the well-known WCM based on an extensive database that includes the modified RTM outputs, scatterometer measurements, SAR datasets, and in situ measured ground-truth data for various vegetation fields. Finally, the unknown constant parameters of the empirical model are determined for each soil moisture condition based on the extensive database. The new empirical model is verified with the database itself, and also with independent Sentinel-1 synthetic aperture radar (SAR) data and in situ measured ground-truth data.

중규모 모델에서의 비단열 자료초기화를 위한 3차원 구름 분석 및 민감도 실험

김용상(Yong-Sang Kim),조천호(Chun-Ho Cho),박옥란(Oak-Ran Park) 한국기상학회 2004 Asia-Pacific Journal of Atmospheric Sciences Vol.40 No.5