• Korean Journal of Remote Sensing
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• v.35 no.4
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• pp.545-560
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• 2019

Unlike other critical forest diseases, pine pitch canker in Korea has shown rather mild symptoms of partial loss of crown foliage and leaf discoloration. This study used high-resolution satellite images to detect and monitor canopy decline by pine pitch canker. To enhance the subtle change of canopy reflectance in pitch canker damaged tree crowns, multi-temporal analysis was applied to two KOMPSAT multispectral images obtained in 2011 and 2015. To assure the spectral consistency between the two images, radiometric corrections of atmospheric and shadow effects were applied prior to multi-temporal analysis. The normalized difference vegetation index (NDVI) of each image and the NDVI difference (${\Delta}NDVI=NDVI_{2015}-NDVI_{2011}$) between two images were derived. All negative ΔNDVI values were initially considered any pine stands, including both pitch canker damaged trees and other trees, that showed the decrease of crown foliage from 2011 to 2015. Next, $NDVI_{2015}$ was used to exclude the canopy decline unrelated to the pitch canker damage. Field survey data were used to find the spectral characteristics of the damaged canopy and to evaluate the detection accuracy from further analysis.Although the detection accuracy as assessed by limited number of field survey on 21 sites was 71%, there were also many false alarms that were spectrally very similar to the damaged canopy. The false alarms were mostly found at the mixed stands of pine and young deciduous trees, which might invade these sites after the pine canopy had already opened by any crown damages. Using both ${\Delta}NDVI$ and $NDVI_{2015}$ could be an effective way to narrow down the potential area of the pitch canker damage in Korea.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.24 no.4
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• pp.61-75
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• 2021

Roadside greenery in the city is not only a means of reducing fine dust, but also an indispensable element of the city in various aspects such as improvement of urban thermal environment, noise reduction, ecosystem connectivity, and aesthetics. However, in studies dealing with the effect of reducing fine dust through trees in existing urban spaces, microscopic aspects such as the adsorption effect of plants were dealt with, structural changes such as the width of urban buildings and streets, and the presence or absence of trees, Impact studies that reflect the actual form of In this study, the effect of greenery composition applicable to urban space on PM2.5 was simulated through the microclimate epidemiologic model ENVI-met, and field measurements were performed in parallel to verify the results. In addition, by analyzing the results of fine dust background concentration, wind speed, and leaf area index, the sensitivity to major influencing variables was tested. As a result of the study, it was confirmed that the fine dust reduction effect was the highest in the case with a high planting amount, and the reduction effect was the greatest at a low background concentration. Based on this, the cost of planting street green areas and the effect of reducing PM2.5 were compared. The results of this study can contribute as a basis for considering the effect of pedestrian space on air quality when planning and designing street green spaces.

• 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.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.9-18
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• 2024

Small streams, despite their rich ecosystems, face challenges in vegetation assessment due to the limitations of traditional, time-consuming methods. This study presents a groundbreaking approach, combining unmanned aerial vehicles(UAVs), convolutional neural networks(CNNs), and the vegetation differential vegetation index (VDVI), to revolutionize both assessment and management of stream vegetation. Focusing on Idong Stream in South Korea (2.7 km long, 2.34 km² basin area)with eight diverse revetment methods, we leveraged high-resolution RGB images captured by UAVs across five dates (July-December). These images trained a ResNeXt101 CNN model, achieving an impressive 89% accuracy in classifying vegetation cover(soil,water, and vegetation). This enabled detailed spatial and temporal analysis of vegetation distribution. Further, VDVI calculations on classified vegetation areas allowed assessment of vegetation vitality. Our key findings showcase the power of this approach:(a) TheCNN model generated highly accurate cover maps, facilitating precise monitoring of vegetation changes overtime and space. (b) August displayed the highest average VDVI(0.24), indicating peak vegetation growth crucial for stabilizing streambanks and resisting flow. (c) Different revetment methods impacted vegetation vitality. Fieldstone sections exhibited initial high vitality followed by decline due to leaf browning. Block-type sections and the control group showed a gradual decline after peak growth. Interestingly, the "H environment block" exhibited minimal change, suggesting potential benefits for specific ecological functions.(d) Despite initial differences, all sections converged in vegetation distribution trends after 15 years due to the influence of surrounding vegetation. This study demonstrates the immense potential of UAV-based remote sensing and CNNs for revolutionizing small-stream vegetation assessment and management. By providing high-resolution, temporally detailed data, this approach offers distinct advantages over traditional methods, ultimately benefiting both the environment and surrounding communities through informed decision-making for improved stream health and ecological conservation.

• Applied Biological Chemistry
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• v.16 no.1
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• pp.18-30
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• 1973

The flag and lower leaves (4th or 5th) of rice plant from the field of NPK simple trial and from three low productive area were analyzed in order to find out certain diagnostic criteria of nutritional status at harvest. 1. Nutrient contents in the leaves from no fertilizer, minus nutrient and fertilizer plots revealed each criterion for induced deficiency (severe deficient case induced by other nutrients), deficiency (below the critical concentration), insufficiency (hidden hunger region), sufficiency (luxuary consumption stage) and excess (harmful or toxic level). 2. Nitrogen contents for the above five status was less than 1.0%, 1.0 to 1.2, 1.2 to 1.6, 1.6 to 1.9 and greater than 1.9, respectively. 3. It was less than 0.3%, 0.3 to 0.4, 0.4 to 0.55 and greater than 0.55 for phosphorus $(P_2O_5)$ but excess level was not clear. 4. It was below 0.5%, 0.5 to 0.9, 0.9 to 1.2, 1.2 to 1.4 and above 1.4 for potassium. 5. It was below 4%, 4 to 6, 6 to 11 and above 11 for silicate $(SiO_2)$ and no excess was appeared. 6. Potassium in flag leaf seemed to crow out nitrogen to ear resulting better growth of ear by the inhibition of overgrowth of flag leaf. 7. Phosphorus accelerated the transport of Mg, Si, Mn and K in this order from lower leaf to flag, and retarded that of Ca and N in this order at flowering while potassium accelerated in the order of Mn, and Ca, and retarded in the order of Mg, Si, P and N at milky stage. 8. Transport acceleration index (TAI) expressed as (F_2L_1-F_1L_2)\;100/F_1L_1$ where F and L stand for other nutrient cotents in flag and lower leaf and subscripts indicate the rate of a nutrient applied, appears to be suitable for the effect of the nutrient on the translocation of others. 9. The content of silicate $(SiO_2)$ in the flag was lower than that of lower leaf in the early season cultivation indicating hinderance in translocation or absorption. It was reverse in the normal season cultivation. 10. The infection rate of Helminthosporium frequently occurred in the potassium deficient field seemed to be related more to silicate and nitrogen content than potassium in the flag leaf. 11. Deficiency of a nutrient occured simultaniously with deficiency of a few other ones. 12. Nutritional disorder under the field condition seems mainly to be attributed to macronutrients and the role of micronutrient appears to be none or secondary.

• Journal of The Korean Society of Grassland and Forage Science
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• v.4 no.1
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• pp.13-17
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• 1983

This experiment was carried out in order to know the relationship between morphological characters and dry matter yield at vegetative growth stage in Meadow fescue grown under plant basis. 1. The dry weight of a plant (PW) indicated positive significant correlation with plant height (pH), leaf area (LA) and stem area (SA). It means that increase in dry of a plant was resulted from interactions among above morphological characters. 2. Stem area (SA) is an important morphological character for increasing the dry weight of a plant. 3. The varieties could be classified into 3 types based on plant type index (PTI, dry weight of a plant/ (no. of tiller)$^2$), it were M in tiller weight type, Leto, First and Trader in medium type and, Bundy and Tammisto in tiller number type, respectively. 4. The variety with tiller weight type had more havier tiller and larger stem thickness than those of variety with tiller number type. But, tiller number type showed higher plant height. 5. In order to obtain the highest yield in tiller weight type, there were necessary to increasing the number of tillers and higher plant height.

• Korean Journal of Ecology and Environment
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• v.46 no.4
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• pp.561-569
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• 2013

This study examines locational environment factors that may affect the vegetation structure in the forests of Naejang National Park. To that end, we selected LAI (Leaf Area Index), diameter at breast height, and tree height as structural variables as well as altitude above sea level, gradient, slope direction, soil moisture, topographic location, and amount of solar radiation as locational environment factors, using the method of canonical correlation analysis in order to find out correlation between them. As to the simple correlation between the locational environment factors and structural variables, the correlation coefficient was relatively low (0.6). The values of LAI, measured along the ridge with higher altitudes, decreased as the soil moisture and solar radiation increased. However, LAI increased as the gradient increased and the slope direction faced the north (farther from the east). In respect of the diameter at breast height, the diameter decreased as the altitude and gradient increased. But the diameter increased as the moisture and solar radiation increased. The tree height decreased as the moisture increased and the site was closer to the ridge. These various correlations show a variety of locational environment factors in the national park, implying that the structural variables are affected by complex locational environment factors. This study conducted a canonical correlation analysis on locational environment factors which may affect the vegetation structure, and the result showed that LAI increased and tree height & diameter at breast height decreased as the solar radiation & moisture decreased and altitude increased. Although more factors that may affect vegetation structure (e.g. climate) should be taken into account, this study is significant in that the vegetation structure, which can adapt to more unfavorable conditions in terms of solar radiation, moisture, and higher altitudes, could be inferred in a statistical way. The results of this study, especially the locational environment factors based on DEM, can be used for assessing diversity of vegetation structure in a forest and for monitoring the structure in a national park on a regular basis so as to establish more effective maintenance plans of a park.

• Journal of Bio-Environment Control
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• v.26 no.3
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• pp.151-157
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• 2017

The objectives of this study were to determine the impact of soil water content on the growth, stomatal conductance, and photosynthesis of Kimchi cabbage and to evaluate proper parameters for development of growth models. There were five levels of irrigation amount treatments (0, 200, 300, 400, and 500 mL/d/plant) and those were commenced at one day after transplanting (DAT). We measured soil water content, stomatal conductance, photosynthesis characteristics, and the A-Ci curve. The growth of Kimchi cabbage as affected by irrigation amount was evaluated at 38 days after transplanting, however, the growth with 0 and 200 mL/d/plant irrigation amount treatments measured at 29 DAT. The relationship between soil water content and stomatal conductance was highly correlated ($r^2=0.999$) and the function represented by y = 6097.4x - 4.2984. The stomatal conductance of Kimchi cabbage leaves showed $300mmol{\cdot}m^{-2}{\cdot}s^{-1}$ when the soil water content was below $0.05m^3/m^3$. The stomatal conductance was rapidly decreased by scarcity of soil moisture. A-Ci curve indicated normal curve in fully irrigation treatment (500 mL/d/plant), however, $CO_2$ couldn't diffuse through the intercellular Kimchi cabbage leaves treated with 0 mL/d/plant. The dry weight of full irrigation treatment was greater approximately 6.8 times than that of deficit irrigation (0 mL/d/plant). In addition, leaf area index showed a logarithmic function (y = 16.573 + 3.398 ln x) with soil water content and that of R-squared represents 0.913. Results indicated that the soil water content was highly correlated with stomatal conductance and leaf area index. Indeed, the scarcity soil moisture reduced photosynthesis and retarded growth.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.4
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• pp.327-336
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• 2019

Soybean is one of the most important crops of which the grains contain high protein content and has been consumed in various forms of food. Soybean plants are generally cultivated on the field and their yield and quality are strongly affected by climate change. Recently, the abnormal climate conditions, including heat wave and heavy rainfall, frequently occurs which would increase the risk of the farm management. The real-time assessment techniques for quality and growth of soybean would reduce the losses of the crop in terms of quantity and quality. The objective of this work was to develop a simple model to estimate the growth of soybean plant using a multispectral sensor mounted on a rotor-wing unmanned aerial vehicle(UAV). The soybean growth model was developed by using simple linear regression analysis with three phenotypic data (fresh weight, dry weight, leaf area index) and two types of vegetation indices (VIs). It was found that the accuracy and precision of LAI model using GNDVI (R²= 0.789, RMSE=0.73 ㎡/㎡, RE=34.91%) was greater than those of the model using NDVI (R²= 0.587, RMSE=1.01 ㎡/㎡, RE=48.98%). The accuracy and precision based on the simple ratio indices were better than those based on the normalized vegetation indices, such as RRVI (R²= 0.760, RMSE=0.78 ㎡/㎡, RE=37.26%) and GRVI (R²= 0.828, RMSE=0.66 ㎡/㎡, RE=31.59%). The outcome of this study could aid the production of soybeans with high and uniform quality when a variable rate fertilization system is introduced to cope with the adverse climate conditions.