• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.46-46
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• 2017

We developed a rice simulation model for remote-sensing (SIMRIW-RS, Homma et al., 2007) to evaluate rice production and management on a regional scale. Here, we reports its application trial to estimate rice production in farmers' fields in Sendai, Japan. The remote-sensing data for the application was periodically obtained by multispectral camera (RGB + NIR and RedEdge) attached with unmanned air vehicle (UAV). The airborne images was 8 cm in resolution which was attained by the flight at an altitude of 115 m. The remote-sensing data was relatively corresponded with leaf area index (LAI) of rice and its spatial and temporal variation, although the correspondences had some errors due to locational inaccuracy. Calibration of the simulation model depended on the first two remote-sensing data (obtained around one month after transplanting and panicle initiation) well predicted rice growth evaluated by the third remote-sensing data. The parameters obtained through the calibration may reflect soil fertility, and will be utilized for nutritional management. Although estimation accuracy has still needed to be improved, the rice yield was also well estimated. These results recommended further data accumulation and more accurate locational identification to improve the estimation accuracy.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.23 no.1
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• pp.86-89
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• 1978

The competitive effects of annual weeds on soybeans (Glycine max. (L.) Merr. 'Gwang Gyo') were Studied on silt clay loam soil. Weeds allowed to grow in the row for 2, 4, 6, 8, 10 weeks after soybean planting and full season reduced soybean yields 6.5, 3.2, 10.7, 8, 8.24.4, and 44%. respectively. Reduction in leaf area index (LAI) and crop growth rate (CGR) of soybeans were closely correlated to percent soybean yield reduction. Weed com petition showed to reduce the number of soybean pods per plant, the number of branches per plant, and plant height.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.23 no.2
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• pp.150-153
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• 1978

A study was conducted to determine the critical period of weed-free maintenance required to produce maximum soybean yields. Leaf area index(LAI). crop growth rate (CGR), and number of pods per plant were increased with extended weed-free maintenance period. Consequently, maximum soybean yields were obtained when weeds were controlled for more than six weeks, but a relatively high level of ;soybean production was attained with only two weeks of weed free maintenance.

• Journal of The Korean Society of Agricultural Engineers
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• v.56 no.5
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• pp.55-65
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• 2014

Radar remote sensing is appropriate for rice monitoring because the areas where this crop is cultivated are often cloudy and rainy. Especially, Synthetic Aperture Radar (SAR) can acquire remote sensing information with a high temporal resolution in tropical and subtropical regions due to its all-weather capability. This paper analyzes the relationships between backscattering coefficients of rice measured by RADARSAT-2 SAR and growth parameters during a rice growth period. And we applied the relationships to crop monitoring of paddy rice in North Korea. As a result, plant height and Leaf Area Index (LAI) increased until Day Of Year (DOY) 234 and then decreased, while fresh weight and dry weight increased until DOY 253. Correlation coefficients revealed that Horizontal transmit and Horizontal receive polarization (HH)-polarization backscattering coefficients were correlated highly with plant height (r=0.95), fresh weight (r=0.92), vegetation water content (r=0.91), LAI (r=0.90), and dry weight (r=0.89). Based on the observed relationships between backscattering coefficients and variables of cultivation, prediction equations were developed using the HH-polarization backscattering coefficients. Concerning the evaluation for the applicability of the LAI distribution from RADARSAT-2, the LAI statistic was evaluated in comparison with LAI distribution from RapidEye image. And LAI distributions in Pyongyang were presented to show spatial variability for unaccessible areas.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.4
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• pp.476-482
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• 2014

In this study, we analyzed the effect of corn growth on the radar backscattering coefficient. At first, we measured the backscattering coefficients of various corn fields using a polarimetric scatterometer system. The backscattering coefficients of the corn fields were also computed using the 1st-order VRT(Vector Radiative Transfer) model with field-measured input parameters. Then, we analyzed the experimental and numerical backscattering coefficients of corn fields. As a result, we found that the backscatter from an underlying soil layer is dominant for early growing stage. On the other hand, for vegetative stage with a higher LAI(Leaf-Area-Index), the backscatter from vegetation canopy becomes dominant, and its backscattering coefficients increase as incidence angle increases because of the effect of leaf angle distribution. It was also found that the estimated backscattering coefficients agree quite well with the field-measured radar backscattering coefficients with an RMSE(Root Mean Square Error) of 1.32 dB for VV-polarization and 0.99 dB for HH-polarization. Finally, we compared the backscattering characteristics of vegetation and soil layers with various LAI values.

• Journal of The Korean Society of Grassland and Forage Science
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• v.5 no.1
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• pp.13-21
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• 1985

This experiment was carried out to study the effect of the autumnal cutting times on the regrowth, the accumulated carbohydrate and dry matter yield of Italian ryegrass The results were summarized as follows: 1. In dry matter yield, the plot of earlier cutting was shown the highest yield (p<0.05), and that of the last-cutting was shown lower yield of dry matter than that the none-cutting plot. 2. TSC (Total Water Soluble Carbohydrate) content slightly decreased after the first cutting and gradually increased according to the regrowth, and then decreased again to the second cutting time. And also the TSC content levels of stubble, stem and leaf at one week before falling to sub-zero temperature were all the highest in the eariler cutting plot (p<0.01), and there was significant correlation between the TSC content level and the second harvested dry matter yield (p<0.05). 3. CGR (Crop Growth Rate) was decreased below $8^{\circ}C$. RLGR (Relative Leaf area Growth Rate) and NAR (Net Assimilation Rate) were both high during 30 days after regrowth, and low after regrowth in all plots. LAI (Leaf Area Index) rapidly increased during 50 days after cutting, and then slowly increased in all the plots, and maximum LAI was 3.4-5.8. Also dry matter yield increased in the plots having a high LAI to 70 days after cutting. 4. It was recognized that there were significant correlation between TSC, LAI, CGR, NAR, LWR (Leaf Weight Ratio) and the second harvested dry matter yield during the low temperature periods, and the degree of contribution to dry matter yield was in order of LWR>LAI>TSC>NAR>CGR.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.365-365
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• 2019

가뭄은 전 세계적으로 농업을 비롯한 사회, 경제적으로 큰 피해를 주는 자연 재해이며, 향후 피해 저감을 위해 가뭄의 경향을 파악하고 지역별 가뭄 특성을 파악할 필요가 있다. 위성영상을 활용한 가뭄 판단은 광역적 범위를 대상으로 다양한 밴드를 활용한 데이터를 주기적이고 일정한 수준으로 취득 가능하다는 장점이 있다. 농업 가뭄 분야의 위성영상 활용은 미계측 지역에 대한 정확한 데이터 취득이 어려운 지점데이터의 단점을 보완할 수 있다. 위성영상을 활용한 가뭄 지수로는 Leaf Area Index (LAI), Vegetation Health Index (VHI), Enhanced Vegetation Index (EVI) 등 다양한 지수들이 있으며, 본 연구에서는 단기 가뭄 판단에 활용되고 있는 Evaporative Stress Index (ESI)를 활용하였다. 국내 행정구역 기반의 가뭄 판단을 위해 Moderate Resolution Imaging Spectramadiometer (MODIS)위성의 MOD16A2 영상을 사용하였다. MOD16A2는 land surface temperature (LST)과 LAI의 계산을 통한 실제 증발산량과 FAO-56 Penman-Monteith 공식을 사용한 잠재증발산량을 포함한 다양한 데이터를 8일 주기의 500m 해상도로 제공하고 있다. 2001년부터 2018년까지 500m 해상도의 ESI를 산정하였으며, 국내의 과거 가뭄 경향 분석과 지역별 특성 파악을 위한 표준화를 수행하였다. 그 결과 과거 극심한 가뭄이 있었던 해 (2000-2001년, 2015-2017년 등)에 대한 농업 가뭄 경향 분석이 가능하였으며, 지역별 특성을 파악한 결과 상습가뭄 지역에서 가뭄 경향을 확인하였다. 농업 가뭄 분야에서 ESI의 활용은 가뭄 조기 경보 시스템 개발 및 위성영상 기반 가뭄 모니터링 기술 개발 등에 활용 가능할 것으로 기대된다.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.2
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• pp.95-106
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• 2010

The performance of Community Land Model version 3.5 - Dynamic Global Vegetation Model (CLM-DGVM) was evaluated through a comparison with the observation over temperate deciduous forest in Gwangneung, Korea. Influence of plant phenology, composition of plant functional type, and climate variability on carbon exchanges was also examined through sensitivity test. To get equilibrium carbon storage, the model was run for 400 years driven by the observed atmospheric data at the deciduous forest of the year 2006. We run the model for 2006 with the equilibrium carbon storage at Gwangneung forest and compared the model output with the observation. A comparison of leaf area index (LAI) between the model and observation indicated that the simulated phenology poorly represented the timing of budburst, leaf-fall, and evolution of LAI. Senescence of the phenology was delayed about four weeks and the simulated maximum LAI (of 5.8 $m^2$ $m^{-2}$) was greater than the observed value (of 4.5 $m^2$ $m^{-2}$). The overestimated LAI contributed to overestimation of both gross primary productivity (GPP) and ecosystem respiration $(R_e)$ through increased photosynthesis and foliar autotropic respiration $(R_a)$, respectively. Despite the discrepancy between the simulated and observed LAI, the simulated tree carbon storage amounts were comparable with the reported values at the site. Change in plant phenology from the simulated to the observed reduced more than six weeks of the plant growth period, resulting in the decreased amount of GPP and $R_e$. These values, however, were still higher (~10% of GPP and 40% of $R_e$) than the observed values. The effect of change in plant functional type composition (from dominant temperate deciduous forest to the coexistence of temperate deciduous and needle leaf forests) on the estimated amount of GPP and $R_e$ was marginal. The influence of climate variability on carbon storage amounts was not significant. The simulated inter-annual variation of GPP and $R_e$ from 1994 to 2003 depended on annual mean air temperature and total radiation but not on precipitation. Other deficiencies of CLM3.5-DGVM have been discussed.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.288-288
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• 2021

수문 모델링을 이용하여 미계측 유역의 유출을 예측하고 나아가 수문 현상을 이해하기 위해서는 기존과는 다른 새로운 모형 보정 전략과 평가 방법이 필요하다. 위성 관측자료의 가용성 증가는 미계측 유역에서 수문 모형의 예측 성능을 확보할 기회를 제공한다. 유역 내 증발산 과정은 물 순환 과정을 설명하는 주요한 부분 중 하나이다. 또한 식생에 대한 정보는 증발산 과정과 밀접한 연관을 가지기 때문에 간접적으로 유역의 증발산 과정을 이해할 수 있는 중요한 정보이다. 본 연구는 미계측 유역의 하천유량을 예측하기 위해 위성 관측 기반의 식생 정보만을 이용하여 보정된 생태 수문 모형의 잠재력을 조사한다. 이러한 보정 방법은 관측된 하천유량 자료가 있어야 하지 않기에 미계측 유역의 하천유량 예측에 특히 유용할 것이다. 모델링 실험은 관측 하천유량 자료가 존재하는 5개의 댐 유역(남강댐, 안동댐, 합천댐, 임하댐)에 대해 수행되었다. 본 연구에서는 식생동역학이 결합 된 집체형 수문 모델을 이용하였으며, MODIS 잎면적지수(Leaf Area Index, LAI) 자료를 이용하여 모형을 보정하였다. 보정된 모형으로부터 생산된 일 유량 결과는 관측 유량 자료와 비교된다. 또한, 전통적인 관측 유량 기반의 모형 보정 방법과 비교된다. 그 결과 LAI 시계열을 이용한 모형의 보정으로 획득한 유량의 적합도는 남강댐, 안동댐, 합천댐 유역에서 KGE가 임계치 이상으로 나타나 만족스러운 결과를 보여주지만, 임하댐 유역은 KGE가 임계치 이하로 계산되었다. 그러나 해당 유역에 대해 관측 유량을 기반으로 모형 보정 결과 또한 좋지 않은 적합도를 보여주기에 이는 LAI 자료 기반 접근법의 문제가 아닌 입력정보 또는 모형 자체에 포함된 오차로 인해 해당 유역의 특성을 반영하기에 어려운 것으로 판단된다. 이러한 결과는 증발산 과정에 주요한 식생 정보의 제약만으로도 비교적 만족스럽게 유역의 수문 순환을 재현할 수 있다는 가능성을 보여준다.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.75-75
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• 2022

Traditional agriculture mostly focused on activity in the field, but current agriculture faces problems such as reduction of agricultural inputs, labor shortage and so on. Accordingly, traditional agricultural experiments generally considered the simple treatment effects, but current agricultural experiments need to consider the several and complicate treatment effects. To analyze such several and complicate treatment effects, data collection has the first priority. Remote sensing is a quite effective tool to collect information in agriculture, and recent easier availability of UAVs (Unmanned Aerial Vehicles) enhances the effectiveness. LAI (Leaf Area Index) is one of the most important information for evaluating the condition of crop growth. In this study, we utilized UAV with multispectral camera to evaluate plant-based LAI of sweetcorn in a small-scale field experiment and discussed the feasibility of a new experimental design to analyze the several and complicate treatment effects. The plant-based SR measured by UAV showed the highest correlation coefficient with LAI measured by a canopy analyzer in 2018 and 2019. Application of linear mix model showed that plant-based SR data had higher detection power due to its huge number of data although SR was inferior to evaluate LAI than the canopy analyzer. The distribution of plant-based data also statistically revealed the border effect in treatment plots in the traditional experimental design. These results suggest that remote sensing with UAVs has the advantage even in a small-scale experimental plot and has a possibility to provide a new experimental design if combined with various analytical applications such as plant size, shape, and color.