• Title/Summary/Keyword: Spatial linear model

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Estimation of soil moisture based on sentinel-1 SAR data: focusing on cropland and grassland area (Sentienl-1 SAR 토양수분 산정 연구: 농지와 초지지역을 중심으로)

  • Cho, Seongkeun;Jeong, Jaehwan;Lee, Seulchan;Choi, Minha
    • Journal of Korea Water Resources Association
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    • v.53 no.11
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    • pp.973-983
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    • 2020
  • Recently, SAR (Synthetic Aperture Radar) is being highlighted as a solution to the coarse spatial resolution of remote sensing data in water resources research field. Spatial resolution up to 10 m of SAR backscattering coefficient has facilitated more elaborate analyses of the spatial distribution of soil moisture, compared to existing satellite-based coarse resolution (>10 km) soil moisture data. It is essential, however, to multilaterally analyze how various hydrological and environmental factors affect the backscattering coefficient, to utilize the data. In this study, soil moisture estimated by WCM (Water Cloud Model) and linear regression is compared with in-situ soil moisture data at 5 soil moisture observatories in the Korean peninsula. WCM shows suitable estimates for observing instant changes in soil moisture. However, it needs to be adjusted in terms of errors. Soil moisture estimated from linear regression shows a stable error range, but it cannot capture instant changes. The result also shows that the effect of soil moisture on backscattering coefficients differs greatly by land cover, distribution of vegetation, and water content of vegetation, hence that there're still limitations to apply preexisting models directly. Therefore, it is crucial to analyze variable effects from different environments and establish suitable soil moisture model, to apply SAR to water resources fields in Korea.

Video De-noising Using Adaptive Temporal and Spatial Filter Based on Mean Square Error Estimation (MSE 추정에 기반한 적응적인 시간적 공간적 비디오 디노이징 필터)

  • Jin, Changshou;Kim, Jongho;Choe, Yoonsik
    • Journal of Broadcast Engineering
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    • v.17 no.6
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    • pp.1048-1060
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    • 2012
  • In this paper, an adaptive temporal and spatial filter (ATSF) based on mean square error (MSE) estimation is proposed. ATSF is a block based de-noising algorithm. Each noisy block is selectively filtered by a temporal filter or a spatial filter. Multi-hypothesis motion compensated filter (MHMCF) and bilateral filter are chosen as the temporal filter and the spatial filter, respectively. Although there is no original video, we mathematically derivate a formular to estimate the real MSE between a block de-noised by MHMCF and its original block and a linear model is proposed to estimate the real MSE between a block de-noised by bilateral filter and its original block. Finally, each noisy block is processed by the filter with a smaller estimated MSE. Simulation results show that our proposed algorithm achieves substantial improvements in terms of both visual quality and PSNR as compared with the conventional de-noising algorithms.

PRISM-KNU Development and Monthly Precipitation Mapping in South Korea (PRISM-KNU의 개발과 남한 월강수량 분포도 작성)

  • PARK, Jong-Chul;KIM, Man-Kyu
    • Journal of the Korean Association of Geographic Information Studies
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    • v.19 no.2
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    • pp.27-46
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    • 2016
  • In this study, the parameter-elevation regressions on independent slopes model-Kongju National University(PRISM-KNU) system was developed to interpolate monthly precipitation data. One of the features of PRISM-KNU is that it can adjust the allowable range of slope according to the elevation range in the equation representing a linear relationship between the precipitation and elevation. The parameter value of the model was determined by using the optimization technique, and the result was applied to produce monthly precipitation data with a spatial resolution of $1{\times}1km$ from 2000 to 2014 in South Korea. In the result, the Kling-Gupta Efficiency for model evaluation was over 0.7 in 86% of the total cases simulated. In addition, a dramatic change in the spatial pattern of precipitation data was observed in the output of the Modified Korean PRISM, but such a phenomenon did not occur in the output of the PRISM-KNU. This study confirmed the appropriateness of the PRISM-KNU, and the result showed that the spatial consistency of the data produced by the model improved compared with that produced by the Modified Korean PRISM. It is expected that the PRISM-KNU and its output will be utilized in various studies in the future.

Development of Species Distribution Models and Evaluation of Species Richness in Jirisan region (지리산 지역의 생물종 분포모형 구축 및 종풍부도 평가)

  • Kwon, Hyuk Soo;Seo, Chang Wan;Park, Chong Hwa
    • Journal of Korean Society for Geospatial Information Science
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    • v.20 no.3
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    • pp.11-18
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    • 2012
  • Increasing concern about biodiversity has lead to a rise in demand on the spatial assessment of biological resources such as biodiversity assessment, protected area selection, habitat management and restoration in Korea. The purpose of this study is to create species richness map through data collection and modeling techniques for wildlife habitat assessment. The GAM (Generalized Additive Model) is easy to interpret and shows better relationship between environmental variables and a response variable than an existing overlap analysis and GLM (Generalized Linear Model). The study area delineated by a large watershed contains Jirisan national park, Mt. Baekun and Sumjin river with three kinds of protected areas (a national park, a landscape ecology protected area and an otter protected area). We collected the presence-absence data for wildlife (mammals and birds) using a stratified random sampling based on a land cover in the study area and implemented natural and socio-environmental data affecting wildlife habitats. After doing a habitat use analysis and specifying significant factors for each species, we built habitat suitability models using a presence-absence model and created habitat suitability maps for each species. Biodiversity maps were generated by taxa and all species using habitat suitability maps. Significant factors affecting each species habitat were different according to their habitat selection. Although some species like a water deer or a great tit were distributed at the low elevation, most potential habitats for mammals and birds were found at the edge of a national park boundary or near a forest around the medium elevation of a mountain range. This study will be used for a basis on biodiversity assessment and proected area selection carried out by Ministry of Environment.

Physicochemical water quality characteristics in relation to land use pattern and point sources in the basin of the Dongjin River and the ecological health assessments using a fish multi-metric model

  • Jang, Geon-Su;An, Kwang-Guk
    • Journal of Ecology and Environment
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    • v.40 no.1
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    • pp.34-44
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    • 2016
  • Background: Little is known about how chemical water quality is associated with ecological stream health in relation to landuse patterns in a watershed. We evaluated spatial characteristics of water quality characteristics and the ecological health of Dongjin-River basin, Korea in relation to regional landuse pattern. The ecological health was assessed by the multi-metric model of Index of Biological Integrity (IBI), and the water chemistry data were compared with values obtained from the health model. Results: Nutrient and organic matter pollution in Dongjin-River basin, Korea was influenced by land use pattern and the major point sources, so nutrients of TN and TP increased abruptly in Site 4 (Jeongeup Stream), which is directly influenced by wastewater treatment plants along with values of electric conductivity (EC), bacterial number, and sestonic chlorophyll-a. Similar results are shown in the downstream (S7) of Dongjin River. The degradation of chemical water quality in the downstream resulted in greater impairment of the ecological health, and these were also closely associated with the landuse pattern. Forest region had low nutrients (N, P), organic matter, and ionic content (as the EC), whereas urban and agricultural regions had opposite in the parameters. Linear regression analysis of the landuse (arable land; $A_L$) on chemicals indicated that values of $A_L$ had positive linear relations with TP ($R^2=0.643$, p < 0.01), TN ($R^2=0.502$, p < 0.05), BOD ($R^2=0.739$, p < 0.01), and suspended solids (SS; ($R^2=0.866$, p < 0.01), and a negative relation with TDN:TDP ratios ($R^2=0.719$, p < 0.01). Conclusions: Chemical factors were closely associated with land use pattern in the watershed, and these factors influenced the ecological health, based on the multimetric fish IBI model. Overall, the impairments of water chemistry and the ecological health in Dongjin-River basin were mainly attributes to point-sources and land-use patterns.

A spatial prediction for the flowering and autumnal dates in Korea (국내 벚꽃 개화 및 단풍 시기에 대한 공간예측)

  • Jin, Hyang Gon;Kim, Sang Wan;Kim, Yongku
    • The Korean Journal of Applied Statistics
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    • v.30 no.3
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    • pp.417-426
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    • 2017
  • It is important to predict the flowering dates of Japanese cherry and autumnal dates in Korea. Flowering date is decided by heating requirement with daily maximum and minimum temperature used to calculate the pre-determined heating requirements for flowering. Recent, changes in climate have impacted the flowering season of Japanese cherry in Korea. When compared with the current normal, the flowering of Japanese cherry is expected to be about 10 days earlier than in near future normal years. In this paper, we first consider a linear model based on meteorological data that predicts the flowering date and then incorporate a spatial structure into the model. Real data analysis indicates that the proposed approach provides more reasonable predicted dates.

Indoor RSSI Characterization using Statistical in Wireless Sensor Network (무선 센서네트워크에서의 통계적 방법에 의한 실내 RSSI 측정)

  • Pu, Chuan-Chin;Chung, Wan-Young
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.11 no.11
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    • pp.2172-2178
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    • 2007
  • In indoor environment, the combination of the two variations, large scale(path loss) and small scale(fading), leads to non-linear variation of RSSI(received signal strength indicator) values as distance varied. This has been one of the difficulties for indoor location estimation. This paper presents new findings on indoor RSSI characterization for more accurate model building. Experiments have been done statistically to find overall trend of RSSI values at different places and times within the same room. From experiments, it has been shown that the variation of RSSI values can be determined by both spatial and temporal factors. These two factors are directly indicated by the two main parameters of path loss model. The results show that all sensor nodes which are located at different places share the same characterization value for the temporal parameter whereas different values for the spatial parameters. The temporal parameter also has a large scale variation effect that is slowly time varying due to environmental changes. Using this relationship, the characterization for location estimation can be more efficient and accurate.

REDUCED-ORDER BASED DISTRIBUTED FEEDBACK CONTROL OF THE BENJAMIN-BONA-MAHONY-BURGERS EQUATION

  • Jia, Li-Jiao;Nam, Yun;Piao, Guang-Ri
    • East Asian mathematical journal
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    • v.34 no.5
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    • pp.661-681
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    • 2018
  • In this paper, we discuss a reduced-order modeling for the Benjamin-Bona-Mahony-Burgers (BBMB) equation and its application to a distributed feedback control problem through the centroidal Voronoi tessellation (CVT). Spatial distcritization to the BBMB equation is based on the finite element method (FEM) using B-spline functions. To determine the basis elements for the approximating subspaces, we elucidate the CVT approaches to reduced-order bases with snapshots. For the purpose of comparison, a brief review of the proper orthogonal decomposition (POD) is provided and some numerical experiments implemented including full-order approximation, CVT based model, and POD based model. In the end, we apply CVT reduced-order modeling technique to a feedback control problem for the BBMB equation.

Study on the First On-Orbit Solar Calibration Measurement of Ocean Scanning Multi-spectral Imager (OSMI)

  • Cho, Young-Min
    • Journal of the Optical Society of Korea
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    • v.5 no.1
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    • pp.9-15
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    • 2001
  • The ocean Scanning Multi-spectral Imager (OSMI) is a payload on the KOrea Multi-Purpose SATellite (KOMPSAT) to perform worldwide ocean color monitoring f the study of biological oceanography. OSMI performs solar and dark calibrations for on-orbit instrument calibration. The purpose of the solar calibration is to monitor the degradation of imaging performance for each pixel of 6 spectral bands and to correct the degradation effect on OSMI image during the ground station date processing. The design, the operation concept, and the radiometric characteristics of the solar calibration are investigated. A linear model of image response and a solar calibration radiance model are proposed to study the instrument characteristics using the solar calibration data. The performance of spectral responsivity and spatial response uniformity. The first solar calibration data and the analysis results are important references for further study on the on-orbit stability of OSMI response during its lifetime.

R Based Parallelization of a Climate Suitability Model to Predict Suitable Area of Maize in Korea (국내 옥수수 재배적지 예측을 위한 R 기반의 기후적합도 모델 병렬화)

  • Hyun, Shinwoo;Kim, Kwang Soo
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.19 no.3
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    • pp.164-173
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    • 2017
  • Alternative cropping systems would be one of climate change adaptation options. Suitable areas for a crop could be identified using a climate suitability model. The EcoCrop model has been used to assess climate suitability of crops using monthly climate surfaces, e.g., the digital climate map at high spatial resolution. Still, a high-performance computing approach would be needed for assessment of climate suitability to take into account a complex terrain in Korea, which requires considerably large climate data sets. The objectives of this study were to implement a script for R, which is an open source statistics analysis platform, in order to use the EcoCrop model under a parallel computing environment and to assess climate suitability of maize using digital climate maps at high spatial resolution, e.g., 1 km. The total running time reduced as the number of CPU (Central Processing Unit) core increased although the speedup with increasing number of CPU cores was not linear. For example, the wall clock time for assessing climate suitability index at 1 km spatial resolution reduced by 90% with 16 CPU cores. However, it took about 1.5 time to compute climate suitability index compared with a theoretical time for the given number of CPU. Implementation of climate suitability assessment system based on the MPI (Message Passing Interface) would allow support for the digital climate map at ultra-high spatial resolution, e.g., 30m, which would help site-specific design of cropping system for climate change adaptation.