• 제목/요약/키워드: Prediction of growth environment

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A study of Improvement for Residential Environment according to Segementation of Residential Zoning (주거지역 종세분화에 따른 주거환경 개선에 관한 연구 - 바람길을 중심으로 -)

  • Kim, Dae-Wuk;Jung, Eung-Ho;Ryu, Ji-Won;Cha, Jae-Gyu;Lee, Jun-Young
    • Journal of the Korean housing association
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    • v.21 no.2
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    • pp.101-109
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    • 2010
  • Various environmental problems due to rapid industrialization and urbanization have worsened to such an extent that they threaten the environmental restitution of the globe and become a critical international issue. Korean government has presented the concept of green growth as a new state vision for the next 60 years and is making efforts to solve these environmental problems. Daegu Metropolitan City has faced various environmental problems including overpopulation of the city, traffic pollution, household waste accumulation and the green zone problem because of the increase of urbanization over the last few decades. As such urbanization continues, the quality of residential environments is rapidly deteriorating and the intensive use of the land leads to an increase of building area, raising the temperatures of cities. There have therefore been demands for healthy, pleasant and satisfying residential environments and for the improvement of existing residential environments, and this demand has been fully recognized by society. Nevertheless, current residential complex developments concentrate only on raising the efficiency of land use. In related laws of the past (Daegu Metropolitan City, Urban Planning Municipal Ordinance as of October 10, 2003) an attempt was made to impose a standard to segmentalize the building-to-land ratio, floor area ratio and regulations of number of floors vertically. However, these laws have now been abolished and the regulations are being eased. The purpose of this study was to analyze the characteristics of the floating wind before and after the vertical segmentation of residential areas (Daegu Metropolitan City, Urban Planning Municipal Ordinance as of October 10, 2003) by using KLAM_21, a model that enables analysis and prediction of the flow and generation of cold wind. The purpose is also to present a plan to improve the quality of residential areas when developing a building lot and redeveloping housing areas.

Land Cover Change and Urban Greenery Prediction in Jabotabek by using Remote Sensing

  • Zain, Alinda-Medrial;Takeuchi, Kazuhiko;Tsunekawa, Atsushi
    • Journal of the Korean Institute of Landscape Architecture International Edition
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    • no.1
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    • pp.59-66
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    • 2001
  • The tremendous growth of population and physical development in the largest urban agglomeration in Indonesia -the Jakarta Metropolitan Region, also known as Jabotabek (Jakarta, Bogor, Tanggerang, Bekasi)- has created many environmental problems, such as land use conversion, increasing urban temperature, water and air pollution, intrusion of seawater, and flooding. These problems have become more serious as the urban green space (trees, shrubs, and groundcovers) has decreased rapidly with the urbanization process. Urban green space directly benefits the urban environment through ameliorating air pollution, controlling temperature, contributing to the balance of the hydrological system, and providing space for recreation and relaxation. Because there is little hard data to support the claim of decreasing greenery in Jabotabek, it is necessary to measure the amount of urban green space. The paper describes the spatial analysis of urban green space within Jabotabek through the use of a geographical information system (GIS). We used GIS and remote sensing to determine land cover change and predicted greenery percentage. Interpretation of Landsat data for 1972, 1983, 1990, and 1997 showed that Jabotabek has experiences rapid development and associated depletion of green open space. The proportion of green open space fell by 23% from 1972 to 1997. We found a low percentage of urban green space in the center of Jakarta but a high percentage in fringe area. The amount of greenery is predicted by the Ratio Vegetation Index (RVI) model: predicted greenery (%) = [146.04] RVI - 134.96. We consider that our result will be useful for landscape planning to improve the environment of Jabotabek.

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Large-Scale Environmental Effects on the Mass Assembly of Dark Matter Halos

  • Jung, Intae;Lee, Jaehyun;Yi, Sukyoung K.
    • The Bulletin of The Korean Astronomical Society
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    • v.38 no.1
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    • pp.32.2-32.2
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    • 2013
  • We examine large-scale environmental effects on the formation and the mass growth of dark matter halos. To facilitate this, we constructed dark matter halo merger trees from a cosmological N-body simulation, which enabled us to trace the merger information and the assembly history of individual halos. In fact, since the massive halos are more likely to be distributed in denser regions than in less dense regions (Mo & White, 1996), the large-scale environment dependence of the properties of halos can be partly originated from the halo mass effect. In order to avoid such contamination, caused by the mass dependence of halo properties, we carefully measured the local overdensity as the indicator of large-scale environment, which was calculated to be as independent of halo mass as possible. Small halos (${\sim}10^{11-12}M_{\odot}$), which usually host isolated single galaxies, show a notable difference on the formation time of galaxies depending on their large-scale environments, which reconfirms halo assembly bias (Gao & White, 2007). Furthermore, we investigate how this environmental effect on small halos is correlated with the mass assembly history of galaxies by using our semi-analytic model. We found that assembly bias in small halos does not have significant effects on the formation time or on the star formation history of galaxies residing in those halos except for the individual stellar mass of galaxies at z = 0. On average, isolated galaxies in high-density regions tend to be slightly more massive than those in low-density regions. Although the observational data from the current galaxy surveys is not yet sufficient for testing this prediction, future galaxy surveys will be able to explore these small galaxies more thoroughly.

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A Numerical Prediction of Nutrient circulation in Hakata Bay by Sediment-Water Ecological Model(SWEM) (수-저질생태계모델에 의한 박다만의 물질순환예측)

  • Lee In-Cheol;Ryu Cheong-Ro
    • Journal of the Korean Society for Marine Environment & Energy
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    • v.4 no.2
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    • pp.3-14
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    • 2001
  • In order to predict nutrient circulation in Hakata bay, we have developed an ecosystem model named the Sediment-Water Ecological Model (SWEM). The model, consisting of two sub-models with hydrodynamic and biological models, simulates the circulation process of nutrient between water column and sediment, such as nutrient regeneration from sediments as well as ecological structures on the growth of phytoplankton and zooplankton. This model was applied to prevent eutrophication in Hakata bay, located in western Japan. The calculated results of the tidal currents by the hydrodynamic model showed good agreement with the observed currents. Moreover, SWEM simulated reasonably well the seasonal variations of water quality, and reproduced spatial heterogeneity of water quality in the bay, observed in the field. According to the simulation of phosphorus circulation at the head of the bay, it was predicted that the regeneration process of phosphorus across the sediment-water interface had a strong influence on the water quality of the bay.

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Abundance of Harmful Algae, Cochlodinium polykrikoides, Gyrodinium impudicum and Gymnodinium catenatum in the Coastal Area of South Sea of Korea and Their Effects of Temperature, Salinity, Irradiance and Nutrient on the Growth in Culture (남해안 연안에서 적조생물, Cochlodinium polykikoides, Gyrodinium impudicum, Gymnodinium catenatum의 출현상황과 온도, 염분, 조도 및 영양염류에 따른 성장특성)

  • LEE Chang Kyu;KIM Hyung Chul;LEE Sam-Geun;JUNG Chang Su;KIM Hak Gyoon;LIM Wol Ae
    • Korean Journal of Fisheries and Aquatic Sciences
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    • v.34 no.5
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    • pp.536-544
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    • 2001
  • Three harmful algal bloom species with similar morphology, Cochlodinium polykrikoides, Gyodinium impudicum and Gymodinium catenatum have damaged to aquatic animals or human health by either making massive blooms or intoxication of shellfishes in a food chain. Eco-physiological and hydrodynamic studies on the harmful algae offer useful informations in the understanding their bloom mechanism by giving promising data for the prediction and modelling of harmful algal blooms event. Thus, we studied the abundance of these species in the coastal area of South Sea of Korea and their effects of temperature, salinity, irradiance and nutrient on the growth for the isolates. The timing for initial appearance of the three species around the coastal area of Namhaedo, Narodo and Wando was between Bate July and late August in 1999 when water temperature ranged from $22.8^{\circ}C\;to\;26.5^{\circ}C$ Vegetative cells of C. polykrikoides and G. impudicum were abundant until late September when water temperature had been dropped to less than $23^{\circ}C$. By contrast, vegetative cell of G. catenatum disappeared before early September, showing shorter period of abundance than the other two species in the South Sea. Both G. impudicum and G. catenatum revealed comparatively low density with a maximal cell density of 3,460 cells/L and 440 cells/L, respectively without making any bloom, while C. polykrikoides made massive blooms with a maximal cell density more than $40\times10^6$cells/L, The three species showed a better growth at the relatively higher water temperature ranging from 22 to $28^{\circ}C$ with their maximal growth rate at $25^{\circ}C$ in culture, which almost corresponded with the water temperature during the outbreak of C. polykrikoides in the coastal area of South Sea. Also, they all showed a relatively higher growth at the salinity from 30 to $35\%$. Specially, G. impudicum showed the euryhalic characteristics among the species, On the other hand, growth rate of G. catenatum decreased sharply with the increase of water temperature at the experimental ranges more than $35\%$. The higher of light intensities showed the better growth rates for the three species, Moreover, C. polykrikoides and G. impudirum continued their exponential growth even at 7,500 lux, the highest level of light intensity in the experiment, Therefore, It is assumed that C. polykrikoides has a physiological capability to adapt and utilize higher irradiance resulting in the higher growth rate without any photo inhibition response at the sea surface where there is usually strong irradiance during its blooming season. Although C. poiykikoides and G. impudicum continued their linear growth with the increase of nitrate ($NO_3^-$) and ammonium ($NH_4^-$) concentrations at less than the $40{\mu}M$, they didn't show any significant differences in growth rates with the increase of nitrate and ammonium concentrations at more than $40{\mu}M$, signifying that the nitrogen critical point for the growth of the two species stands between 13.5 and $40{\mu}M$. Also, even though both of the two species continued their linear growth with the increase of phosphate ($PO_4^{2-}$) concentrations at less than the $4.05{\mu}M$, there were no any significant differences in growth rates with the increase of phosphate concentrations at more than $4.05{\mu}M$, signifying that the phosphate critical point for the growth of the two species stands between 1.35 and $4.05{\mu}M$. On the other hand, C. polykrikoides has made blooms at the oligotrophic environment near Narodo and Namhaedo where the concentration of DIN and DIP are less than 1.2 and $0.3{\mu}M$, respectively. We attributed this phenomenon to its own ecological characteristics of diel vertical migration through which C. polykrikoides could uptake enough nutrients from the deep sea water near bottom during the night time irrespective of the lower nutrient pools in the surface water.

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A Study on the Thermal Prediction Model cf the Heat Storage Tank for the Optimal Use of Renewable Energy (신재생 에너지 최적 활용을 위한 축열조 온도 예측 모델 연구)

  • HanByeol Oh;KyeongMin Jang;JeeYoung Oh;MyeongBae Lee;JangWoo Park;YongYun Cho;ChangSun Shin
    • Smart Media Journal
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    • v.12 no.10
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    • pp.63-70
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    • 2023
  • Recently, energy consumption for heating costs, which is 35% of smart farm energy costs, has increased, requiring energy consumption efficiency, and the importance of new and renewable energy is increasing due to concerns about the realization of electricity bills. Renewable energy belongs to hydropower, wind, and solar power, of which solar energy is a power generation technology that converts it into electrical energy, and this technology has less impact on the environment and is simple to maintain. In this study, based on the greenhouse heat storage tank and heat pump data, the factors that affect the heat storage tank are selected and a heat storage tank supply temperature prediction model is developed. It is predicted using Long Short-Term Memory (LSTM), which is effective for time series data analysis and prediction, and XGBoost model, which is superior to other ensemble learning techniques. By predicting the temperature of the heat pump heat storage tank, energy consumption may be optimized and system operation may be optimized. In addition, we intend to link it to the smart farm energy integrated operation system, such as reducing heating and cooling costs and improving the energy independence of farmers due to the use of solar power. By managing the supply of waste heat energy through the platform and deriving the maximum heating load and energy values required for crop growth by season and time, an optimal energy management plan is derived based on this.

Characteristics of Growth and Development of Empirical Stand Yield Model on Pinus densiflora in Central Korea (중부지방소나무의 생장특성 및 경험적 임분수확모델 개발)

  • Jeon, Ju Hyeon;Son, Yeong Mo;Kang, Jin Taek
    • Journal of Korean Society of Forest Science
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    • v.106 no.2
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    • pp.267-273
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    • 2017
  • This study was conducted to construct a empirical yield table for Pinus densiflora in real forest. Since existing normal yield tables have been derived by studying and analyzing communities in ideal environment for tree growth, those tables provide more over-estimated values than ones from real forest. Because of this, there are some difficulties to apply the tables to empirical forest except for normal forest. In this study, therefore, we estimated stand growth for real forest on P. densiflora as the representative species of conifers. We used 1,957 sample plot data of P. densiflora in central Korea from National Forest Inventory (NFI) system, and analyzed through estimation, recovery and prediction in order by using Weibull function as a diameter distribution model. Weilbull and Schumacher models were applied for estimating mean DBH and mean basel area and it was found that the site index for P. densiflora in central Korea ranges from 8 to 14 at reference age 30. According to site 12 in the stand yield table, the Mean Annual Increment (MAI) of P. densiflora was $4.42m^3/ha$ at 30 years of age. Compared to existing volume table constructed before, it is showed that MAI of this study were lower. According to the paired t-test that is conducted with the gap of volume values between normal forest and real forest by site index and age, the P-value was less than 0.001 which is recognized to have a statistically significant difference. Based on the results in this study, it is considered to be helpful for practical management and management policy on P. densiflora in central Korea.

Prediction of Greenhouse Strawberry Production Using Machine Learning Algorithm (머신러닝 알고리즘을 이용한 온실 딸기 생산량 예측)

  • Kim, Na-eun;Han, Hee-sun;Arulmozhi, Elanchezhian;Moon, Byeong-eun;Choi, Yung-Woo;Kim, Hyeon-tae
    • Journal of Bio-Environment Control
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    • v.31 no.1
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    • pp.1-7
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    • 2022
  • Strawberry is a stand-out cultivating fruit in Korea. The optimum production of strawberry is highly dependent on growing environment. Smart farm technology, and automatic monitoring and control system maintain a favorable environment for strawberry growth in greenhouses, as well as play an important role to improve production. Moreover, physiological parameters of strawberry plant and it is surrounding environment may allow to give an idea on production of strawberry. Therefore, this study intends to build a machine learning model to predict strawberry's yield, cultivated in greenhouse. The environmental parameter like as temperature, humidity and CO2 and physiological parameters such as length of leaves, number of flowers and fruits and chlorophyll content of 'Seolhyang' (widely growing strawberry cultivar in Korea) were collected from three strawberry greenhouses located in Sacheon of Gyeongsangnam-do during the period of 2019-2020. A predictive model, Lasso regression was designed and validated through 5-fold cross-validation. The current study found that performance of the Lasso regression model is good to predict the number of flowers and fruits, when the MAPE value are 0.511 and 0.488, respectively during the model validation. Overall, the present study demonstrates that using AI based regression model may be convenient for farms and agricultural companies to predict yield of crops with fewer input attributes.

Influence of Sulfur and Fluorine Compounds on the Growth and Yield of Rice Plants;I. Growth Retardation and Yield Reduction under Various Stressed Conditions in the Field (황화물(黃化物) 및 불화물(弗化物)이 수도생육(水稻生育)과 수량(收量)에 미치는 영향(影響);I. 오염지역(汚染地域)에서의 생육장해(生育障害) 및 수량감소(收量減少))

  • Park, Wan-Cheol;Shin, Eung-Bai;Kim, Kwang-Ho
    • Korean Journal of Environmental Agriculture
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    • v.6 no.2
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    • pp.53-65
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    • 1987
  • The study was performed to investigate the effect of gaseous emissions of sulfur dioxide and hydrogen fluoride on the growth of rice plants under stressed field conditions consisting of 88 industrial plants operating with 285 smoke stacks emitting pollutants. As for the relationship between yields and yield components it is believed that the panicles per hill is the single most important component affecting the rate of yield of the rice plant. Based on the standard partial regression coefficient analysis, panicles per hill has the largest contribution to yield and the average contribution of 54%. Other components such as spikelets per panicle, percent fertility and 1000 grain weight are also contributing factors to yield, although far less so. Fluorine content in the leaf appear to have more negative effect on panicles per hill, percent fertility and subsequent overall yield than does sulfur content in the leaf. It is constantly observed and interesting to note that fluorine and sulfur content in the leaf appears to have no effect on spikelets per panicle and 1000 grain weight. Reduction in yield seems to be affected mainly by panicles per hill which are, in turn, affected more by fluorine content in the leaf as demonstrated by the standard partial coefficient analysis. Regarding the prediction sum of the square of the regression equation, the lowest value was found when nine variables were used for the analysis. The variables taken into consideration were the monthly sulfur and fluorine content in the leaf as well as the monthly percent of leaf damage during the months of June, July and August. A significant correlation is found between the actual and predicted yields by the regression equations selected as a result of a prediction sum of the square analysis.

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Prediction Model of Pine Forests' Distribution Change according to Climate Change (기후변화에 따른 소나무림 분포변화 예측모델)

  • Kim, Tae-Geun;Cho, Youngho;Oh, Jang-Geun
    • Korean Journal of Ecology and Environment
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    • v.48 no.4
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    • pp.229-237
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    • 2015
  • This study aims to offer basic data to effectively preserve and manage pine forests using more precise pine forests' distribution status. In this regard, this study predicts the geographical distribution change of pine forests growing in South Korea, due to climate change, and evaluates the spatial distribution characteristics of pine forests by age. To this end, this study predicts the potential distribution change of pine forests by applying the MaxEnt model useful for species distribution change to the present and future climate change scenarios, and analyzes the effects of bioclimatic variables on the distribution area and change by age. Concerning the potential distribution regions of pine forests, the pine forests, aged 10 to 30 years in South Korea, relatively decreased more. As the area of the region suitable for pine forest by age was bigger, the decreased regions tend to become bigger, and the expanded regions tend to become smaller. Such phenomena is conjectured to be derived from changing of the interaction of pine forests by age from mutual promotional relations to competitive relations in the similar climate environment, while the regions suitable for pine forests' growth are mostly overlap regions. This study has found that precipitation affects more on the distribution of pine forests, compared to temperature change, and that pine trees' geographical distribution change is more affected by climate's extremities including precipitation of driest season and temperature of the coldest season than average climate characteristics. Especially, the effects of precipitation during the driest season on the distribution change of pine forests are irrelevant of pine forest's age class. Such results are expected to result in a reduction of the pine forest as the regions with the increase of moisture deficiency, where climate environment influencing growth and physiological responses related with drought is shaped, gradually increase according to future temperature rise. The findings in this study can be applied as a useful method for the prediction of geographical change according to climate change by using various biological resources information already accumulated. In addition, those findings are expected to be utilized as basic data for the establishment of climate change adaptation policies related to forest vegetation preservation in the natural ecosystem field.