• Title/Summary/Keyword: normalized coefficient

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A Simple Method for Classifying Land Cover of Rice Paddy at a 1 km Grid Spacing Using NOAA-AVHRR Data (NOAA-AVHRR 자료를 이용한 1 km 해상도 벼논 피복의 간이분류법)

  • 구자민;홍석영;윤진일
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.3 no.4
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    • pp.215-219
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    • 2001
  • Land surface parameterization schemes for atmospheric models as well as decision support tools for ecosystem management require a frequent updating of land cover classification data for regional to global scales. Rice paddies have not been treated independently from other agricultural land classes in many classification systems, despite their atmospheric and ecological significance. A simple but improved method over conventional land cover classification schemes for rice paddy is suggested. Normalized difference vegetation index (NDVI) was calculated for the land area of South Korea at a 1km by 1 km resolution from the visible and the near-infrared channel reflectances of NOAA-AVHRR (Advanced Very High Resolution Radiometer). Monthly composite images of daily maximum NDVI were prepared for May and August, and used to classify 4 major land cover classes : urban, farmland, forests and water body. Among the pixels classified as "forests" in August, those classified as "water body" in May were assigned a "rice paddy" class. The distribution pattern of "rice paddy" pixels was very similar to the reported rice acreage of 1,455 Myons, which is the smallest administrative land unit in Korea. The correlation coefficient between the estimated and the reported acreage of Myons was 0.7, while 0.5 was calculated from the USGS classification.calculated from the USGS classification.

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Estimation of Spatial Evapotranspiration Using Terra MODIS Satellite Image and SEBAL Model - A Case of Yongdam Dam Watershed - (Terra MODIS 위성영상과 SEBAL 모형을 이용한 공간증발산량 산정 연구 - 용담댐 유역을 대상으로 -)

  • Lee, Yong-Gwan;Kim, Sang-Ho;Ahn, So-Ra;Choi, Min-Ha;Lim, Kwang-Suop;Kim, Seong-Joon
    • Journal of the Korean Association of Geographic Information Studies
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    • v.18 no.1
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    • pp.90-104
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    • 2015
  • The purpose of this paper is to build a spatio-temporal evapotranspiration(ET) estimation model using Terra MODIS satellite image and by calibrating with the flux tower ET data from watershed. The fundamentals of spatial ET model, Surface Energy Balance Algorithm for Land(SEBAL) was adopted and modified to estimate the daily ET of Yongdam Dam watershed in South Korea. The daily Normalized Distribution Vegetation Index(NDVI), Albedo, and Land Surface Temperature(LST) from MODIS and the ground measured wind speed and solar radiation data were prepared for 2 years(2012-2013). The SEBAL was calibrated with the forest ET measured by Deokyusan flux tower in the study watershed. Among the model parameters, the important parameters were surface albedo, NDVI and surface roughness in order for momentum transport during calculation of sensible heat flux. As a result of the final calibration, the monthly averaged albedo and NDVI were used because the daily values showed big deviation with unrealistic change. The determination coefficient($R^2$) between SEBAL and flux data was 0.45. The spatial ET reflected the geographical characteristics showing the ET of lowland areas was higher than the highland ET.

Fish fauna and characteristics of Carassius auratus population in the Boryeong Reservoir (보령호의 어류상 및 붕어 개체군 특성)

  • Choi, Won Sub;Han, Jung Soo;Choi, Jun Kil;Lee, Hwang Goo
    • Korean Journal of Environmental Biology
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    • v.38 no.4
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    • pp.667-677
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    • 2020
  • This study was conducted to investigate the fish fauna and characteristics of the Carassius auratus population in the Boryeong Reservoir in Chungcheongnam-do from October 2017 to June 2018. The collected fish were identified as 3,506 individuals of 15 species from a total of nine families. The dominant and subdominant species were H. nipponensis with 1,706 (48.6%) individuals and C. auratus with 1,021 (29.1%) individuals, respectively. The biomass of C. auratus (246,130g), P. fulvidraco(50,610g), C. cuvieri (14,730 g), S. asotus (11,560 g), and C. carpio (10,930 g) was analyzed. The results of the community analysis showed a dominant index value of 0.87 (±0.2), a diversity index value of 0.78 (±0.5), an evenness index value of 0.47 (±0.2), and a richness index value of 0.99 (±0.5). The length-weight analysis of C. auratus showed a regression coefficient b of 3.06, and a condition factor (K) of 0.0004 with a positive slope. The frequency distribution of the total length analysis of the C. auratus population inhabiting the Boryeong Reservoir showed a high distribution of lengths between 140-160 mm and a low distribution between 230-280 mm. The normalized difference water index (NDWI) was analyzed over the Boryeong Reservoir water surface from 2013 to 2014 using Landsat 8 channel data. The areas where the NDWI was decreased were located at the inflow site of Ungcheon Stream.

Analysis of Plant Height, Crop Cover, and Biomass of Forage Maize Grown on Reclaimed Land Using Unmanned Aerial Vehicle Technology

  • Dongho, Lee;Seunghwan, Go;Jonghwa, Park
    • Korean Journal of Remote Sensing
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    • v.39 no.1
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    • pp.47-63
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    • 2023
  • Unmanned aerial vehicle (UAV) and sensor technologies are rapidly developing and being usefully utilized for spatial information-based agricultural management and smart agriculture. Until now, there have been many difficulties in obtaining production information in a timely manner for large-scale agriculture on reclaimed land. However, smart agriculture that utilizes sensors, information technology, and UAV technology and can efficiently manage a large amount of farmland with a small number of people is expected to become more common in the near future. In this study, we evaluated the productivity of forage maize grown on reclaimed land using UAV and sensor-based technologies. This study compared the plant height, vegetation cover ratio, fresh biomass, and dry biomass of maize grown on general farmland and reclaimed land in South Korea. A biomass model was constructed based on plant height, cover ratio, and volume-based biomass using UAV-based images and Farm-Map, and related estimates were obtained. The fresh biomass was estimated with a very precise model (R2 =0.97, root mean square error [RMSE]=3.18 t/ha, normalized RMSE [nRMSE]=8.08%). The estimated dry biomass had a coefficient of determination of 0.86, an RMSE of 1.51 t/ha, and an nRMSE of 12.61%. The average plant height distribution for each field lot was about 0.91 m for reclaimed land and about 1.89 m for general farmland, which was analyzed to be a difference of about 48%. The average proportion of the maize fraction in each field lot was approximately 65% in reclaimed land and 94% in general farmland, showing a difference of about 29%. The average fresh biomass of each reclaimed land field lot was 10 t/ha, which was about 36% lower than that of general farmland (28.1 t/ha). The average dry biomass in each field lot was about 4.22 t/ha in reclaimed land and about 8 t/ha in general farmland, with the reclaimed land having approximately 53% of the dry biomass of the general farmland. Based on these results, UAV and sensor-based images confirmed that it is possible to accurately analyze agricultural information and crop growth conditions in a large area. It is expected that the technology and methods used in this study will be useful for implementing field-smart agriculture in large reclaimed areas.

Determinations of P, S-Wave Velocities and Pore Water Pressure Buildup with B-value for Nearly Saturated Sands (비배수 조건에서 반복하중을 받는 사질토의 B값(간극수압계수)에 따른 P파, S파 속도 및 간극수압 측정)

  • Lee, Sei-Hyun;Choo, Yun-Wook;Youn, Jun-Ung;Kim, Dong-Soo
    • Journal of the Korean Geotechnical Society
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    • v.23 no.2
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    • pp.71-83
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    • 2007
  • Liquefaction resistance depends strongly upon the degree of saturation, which is expressed in terms of the pore pressure coefficient, B. The B-value has been widely used to quantify the state of saturation of laboratory samples. However, it is practically impossible to determine in situ state of saturation by using the B-value. So, P-wave velocity can be alternatively used as a convenient index for evaluating the in situ state of saturation. In this paper, the Stokoe type torsional shear (TS) testing system was modified to saturate the specimen, with which it is also possible to measure P ($V_p$), S-wave velocity ($V_s$) and the excess pore water pressure buildup In order to examine the effect of B-value for nearly saturated sands. A series of the tests were carried out at 3 relative densities (40%, 50% and 75%) and various B-values using Toyoura sand. Based on the test results, the variations of $V_p\;and\;V_s$ with B-value were analyzed and compared with a existing theoretically derived formula. The normalized pore water pressure, $du/{\sigma}{_0}'$ and cyclic threshold shear strain, ${\gamma}^c_{th}$ with B-value were also analyzed. Additionally the test results related to pore water pressure were analyzed by $V_p$ to apply to the field seismic analysis.

Production of Digital Climate Maps with 1km resolution over Korean Peninsula using Statistical Downscaling Model (통계적 상세화 모형을 활용한 한반도 1km 농업용 전자기후도 제작)

  • Jina Hur;Jae-Pil Cho;Kyo-Moon Shim;Sera Jo;Yong-Seok Kim;Min-Gu Kang;Chan-Sung Oh;Seung-Beom Seo;Eung-Sup Kim
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.25 no.4
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    • pp.404-414
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    • 2023
  • In this study, digital climate maps with high-resolution (1km, daily) for the period of 1981 to 2020 were produced for the use as reference data within the procedures for statistical downscaling of climate change scenarios. Grid data for the six climate variables including maximum temperature, minimum temperature, precipitation, wind speed, relative humidity, solar radiation was created over Korean Peninsula using statistical downscaling model, so-called IGISRM (Improved GIS-based Regression Model), using global reanalysis data and in-situ observation. The digital climate data reflects topographical effects well in terms of representing general behaviors of observation. In terms of Correlation Coefficient, Slope of scatter plot, and Normalized Root Mean Square Error, temperature-related variables showed satisfactory performance while the other variables showed relatively lower reproducibility performance. These digital climate maps based on observation will be used to downscale future climate change scenario data as well as to get the information of gridded agricultural weather data over the whole Korean Peninsula including North Korea.

Assessment of the Utility of Remote Sensing Techniques for Monitoring Compliance with Direct Payment Programs (직불제 이행점검 모니터링을 위한 원격탐사 기법 활용성 평가)

  • Hoyong Ahn;Jae-Hyun Ryu;Kyungdo Lee
    • Korean Journal of Remote Sensing
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    • v.39 no.6_1
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    • pp.1467-1475
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    • 2023
  • The public-interest direct payment program involves providing direct payments to agricultural producers and rural residents through public funds, premised on performing public functions such as environmental conservation, stable food supply, and maintaining rural communities via agricultural activities. Scientific estimation of crop cultivation areas and production levels is crucial for formulating agricultural policies linked to regulating food supply, which increasingly impacts the national economy. Conducting comprehensive on-site inspections for compliance monitoring of direct payment programs has shown very low efficiency in relation to budget and time. The expansion of areas subject to compliance monitoring and various challenges in on-site inspections necessitate streamlining current monitoring methods and devising effective strategies. As a solution, the application of Remote Sensing technology and spatial information utilization, allowing swift acquisition of necessary information for policies without overall on-site visits, is being discussed as an efficient compliance monitoring method. Therefore, this study evaluated the potential use of remote sensing for improving operational efficiency in monitoring compliance with public-interest direct payment programs. Using satellite images during farming seasons in Gimje and Hapcheon, vegetation indices and spatial variations were utilized to identify cultivated areas, presence of mixed crops, validated against on-site inspection data.

Qualitative and Quantitative Magnetic Resonance Imaging Phenotypes May Predict CDKN2A/B Homozygous Deletion Status in Isocitrate Dehydrogenase-Mutant Astrocytomas: A Multicenter Study

  • Yae Won Park;Ki Sung Park;Ji Eun Park;Sung Soo Ahn;Inho Park;Ho Sung Kim;Jong Hee Chang;Seung-Koo Lee;Se Hoon Kim
    • Korean Journal of Radiology
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    • v.24 no.2
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    • pp.133-144
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    • 2023
  • Objective: Cyclin-dependent kinase inhibitor (CDKN)2A/B homozygous deletion is a key molecular marker of isocitrate dehydrogenase (IDH)-mutant astrocytomas in the 2021 World Health Organization. We aimed to investigate whether qualitative and quantitative MRI parameters can predict CDKN2A/B homozygous deletion status in IDH-mutant astrocytomas. Materials and Methods: Preoperative MRI data of 88 patients (mean age ± standard deviation, 42.0 ± 11.9 years; 40 females and 48 males) with IDH-mutant astrocytomas (76 without and 12 with CDKN2A/B homozygous deletion) from two institutions were included. A qualitative imaging assessment was performed. Mean apparent diffusion coefficient (ADC), 5th percentile of ADC, mean normalized cerebral blood volume (nCBV), and 95th percentile of nCBV were assessed via automatic tumor segmentation. Logistic regression was performed to determine the factors associated with CDKN2A/B homozygous deletion in all 88 patients and a subgroup of 47 patients with histological grades 3 and 4. The discrimination performance of the logistic regression models was evaluated using the area under the receiver operating characteristic curve (AUC). Results: In multivariable analysis of all patients, infiltrative pattern (odds ratio [OR] = 4.25, p = 0.034), maximal diameter (OR = 1.07, p = 0.013), and 95th percentile of nCBV (OR = 1.34, p = 0.049) were independent predictors of CDKN2A/B homozygous deletion. The AUC, accuracy, sensitivity, and specificity of the corresponding model were 0.83 (95% confidence interval [CI], 0.72-0.91), 90.4%, 83.3%, and 75.0%, respectively. On multivariable analysis of the subgroup with histological grades 3 and 4, infiltrative pattern (OR = 10.39, p = 0.012) and 95th percentile of nCBV (OR = 1.24, p = 0.047) were independent predictors of CDKN2A/B homozygous deletion, with an AUC accuracy, sensitivity, and specificity of the corresponding model of 0.76 (95% CI, 0.60-0.88), 87.8%, 80.0%, and 58.1%, respectively. Conclusion: The presence of an infiltrative pattern, larger maximal diameter, and higher 95th percentile of the nCBV may be useful MRI biomarkers for CDKN2A/B homozygous deletion in IDH-mutant astrocytomas.

Data-driven Modeling for Valve Size and Type Prediction Using Machine Learning (머신 러닝을 이용한 밸브 사이즈 및 종류 예측 모델 개발)

  • Chanho Kim;Minshick Choi;Chonghyo Joo;A-Reum Lee;Yun Gun;Sungho Cho;Junghwan Kim
    • Korean Chemical Engineering Research
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    • v.62 no.3
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    • pp.214-224
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    • 2024
  • Valves play an essential role in a chemical plant such as regulating fluid flow and pressure. Therefore, optimal selection of the valve size and type is essential task. Valve size and type have been selected based on theoretical formulas about calculating valve sizing coefficient (Cv). However, this approach has limitations such as requiring expert knowledge and consuming substantial time and costs. Herein, this study developed a model for predicting valve sizes and types using machine learning. We developed models using four algorithms: ANN, Random Forest, XGBoost, and Catboost and model performances were evaluated using NRMSE & R2 score for size prediction and F1 score for type prediction. Additionally, a case study was conducted to explore the impact of phases on valve selection, using four datasets: total fluids, liquids, gases, and steam. As a result of the study, for valve size prediction, total fluid, liquid, and gas dataset demonstrated the best performance with Catboost (Based on R2, total: 0.99216, liquid: 0.98602, gas: 0.99300. Based on NRMSE, total: 0.04072, liquid: 0.04886, gas: 0.03619) and steam dataset showed the best performance with RandomForest (R2: 0.99028, NRMSE: 0.03493). For valve type prediction, Catboost outperformed all datasets with the highest F1 scores (total: 0.95766, liquids: 0.96264, gases: 0.95770, steam: 1.0000). In Engineering Procurement Construction industry, the proposed fluid-specific machine learning-based model is expected to guide the selection of suitable valves based on given process conditions and facilitate faster decision-making.

JINGLE - V. Dust properties of nearby galaxies derived from hierarchical Bayesian SED fitting

  • Isabella Lamperti;Amelie Saintonge;Ilse De Looze;Gioacchino Accurso;Christopher J. R. Clark;Matthew W. L. Smith;Christine D. Wilson;Elias Brinks;Toby Brown;Martin Bureau;David L. Clements;Stephen Eales;David H. W. Glass;Ho Seong Hwang;Jong Chul Lee;Lihwai Lin;Michal J. Michalowski;Mark Sargent;Thomas G. Williams;Ting Xiao;Chentao Yang
    • Monthly Notices of the Royal Astronomical Society
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    • v.489 no.3
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    • pp.4389-4417
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    • 2019
  • We study the dust properties of 192 nearby galaxies from the JINGLE survey using photometric data in the 22-850 ㎛ range. We derive the total dust mass, temperature T, and emissivity index β of the galaxies through the fitting of their spectral energy distribution (SED) using a single modified blackbody model (SMBB). We apply a hierarchical Bayesian approach that reduces the known degeneracy between T and β. Applying the hierarchical approach, the strength of the T-β anticorrelation is reduced from a Pearson correlation coefficient R = -0.79 to R = -0.52. For the JINGLE galaxies we measure dust temperatures in the range 17-30 K and dust emissivity indices β in the range 0.6-2.2. We compare the SMBB model with the broken emissivity law modified blackbody (BMBB) and the two modified blackbody (TMBB) models. The results derived with the SMBB and TMBB are in good agreement, thus applying the SMBB, which comes with fewer free parameters, does not penalize the measurement of the cold dust properties in the JINGLE sample. We investigate the relation between T and β and other global galaxy properties in the JINGLE and Herschel Reference Survey (HRS) sample. We find that β correlates with the stellar mass surface density (R = 0.62) and anticorrelates with the H i mass fraction (MH i/M*, R = -0.65), whereas the dust temperature correlates strongly with the star formation rate normalized by the dust mass (R = 0.73). These relations can be used to estimate T and β in galaxies with insufficient photometric data available to measure them directly through SED fitting.