• Korean Journal of Environment and Ecology
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• v.36 no.5
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• pp.481-495
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• 2022

This study was designed to identify the actual state of naturalized plants and invasive alien species that cause disturbances to the ecosystem, plants which are introduced after forest restoration, and explore the implications resulting from the project. Onsite examination included 29 sites which have been subjected to forest restoration by the Korea Forest Service. Once these were chosen, activity took place twice a year in the spring (May-June) and in the summer (August-September) in 2020 and 2021. Areas not relevant to the project sites were excluded from this activity so that we could identify the plants that could be understood to have been introduced or brought into the site after the actual forest restoration. And the correlation was analyzed, between the naturalized flora within the project sites and the working types applied to the site through confirmation of completion of the restoration project. The naturalized plants appearing on the entire site cover a total of 109 taxa, which includes 29 families, 80 genera, 108 species and 1 subspecies, while invasive plants included 3 families, 7 genera and 8 species. The number of classifications and the naturalization rate gradually decreased over time, after the project. While there was no significant difference between the number of classification groups and the naturalization rate for naturalized plants between project sites, given the number of taxa of naturalized plants, organized by type of damage, there were relatively more naturalized plants that appeared in the severed section of the Baekdudaegan Mountain Range, as well as at quarry and facility sites. Seeding apparently results in naturalization rates as high as 15.545%, on average, based on comparisons of naturalization rates by sowing, seeding, planting, herb planting, and sod pitching channels, all of these being methods of vegetation for planting/greening of bareland and slopes within the project areas. With no seeding, it was 9.167%, higher than the average. As for other vegetation, there was no significant difference depending on application of the working type. This means that unlike the plants subjected to planting, the working type of seed planting which makes it difficult to identify whether a certain plant is a naturalized plant greatly affects the introduction of naturalized plants to the restoration sites, even when using herb planting and sod pitching to control plants and results. Therefore the study suggests that there be inspection by experts of seeds when sowing within restoration sites. The results of this study suggest good practices that will help to direct effective vegetation restoration and follow-up management.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1285-1300
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• 2022

Turbidity, the measure of the cloudiness of water, is used as an important index for water quality management. The turbidity can vary greatly in small river systems, which affects water quality in national rivers. Therefore, the generation of high-resolution spatial information on turbidity is very important. In this study, a turbidity retrieval model using the Korea Multi-Purpose Satellite-3 and -3A (KOMPSAT-3/3A) images was developed for high-resolution turbidity mapping of Han River system based on eXtreme Gradient Boosting (XGBoost) algorithm. To this end, the top of atmosphere (TOA) spectral reflectance was calculated from a total of 24 KOMPSAT-3/3A images and 150 Landsat-8 images. The Landsat-8 TOA spectral reflectance was cross-calibrated to the KOMPSAT-3/3A bands. The turbidity measured by the National Water Quality Monitoring Network was used as a reference dataset, and as input variables, the TOA spectral reflectance at the locations of in situ turbidity measurement, the spectral indices (the normalized difference vegetation index, normalized difference water index, and normalized difference turbidity index), and the Moderate Resolution Imaging Spectroradiometer (MODIS)-derived atmospheric products(the atmospheric optical thickness, water vapor, and ozone) were used. Furthermore, by analyzing the KOMPSAT-3/3A TOA spectral reflectance of different turbidities, a new spectral index, new normalized difference turbidity index (nNDTI), was proposed, and it was added as an input variable to the turbidity retrieval model. The XGBoost model showed excellent performance for the retrieval of turbidity with a root mean square error (RMSE) of 2.70 NTU and a normalized RMSE (NRMSE) of 14.70% compared to in situ turbidity, in which the nNDTI proposed in this study was used as the most important variable. The developed turbidity retrieval model was applied to the KOMPSAT-3/3A images to map high-resolution river turbidity, and it was possible to analyze the spatiotemporal variations of turbidity. Through this study, we could confirm that the KOMPSAT-3/3A images are very useful for retrieving high-resolution and accurate spatial information on the river turbidity.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1723-1735
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• 2022

Landslides are one of the most prevalent natural disasters, threating both humans and property. Also landslides can cause damage at the national level, so effective prediction and prevention are essential. Research to produce a landslide susceptibility map with high accuracy is steadily being conducted, and various models have been applied to landslide susceptibility analysis. Pixel-based machine learning models such as frequency ratio models, logistic regression models, ensembles models, and Artificial Neural Networks have been mainly applied. Recent studies have shown that the kernel-based convolutional neural network (CNN) technique is effective and that the spatial characteristics of input data have a significant effect on the accuracy of landslide susceptibility mapping. For this reason, the purpose of this study is to analyze landslide vulnerability using a pixel-based deep neural network model and a patch-based convolutional neural network model. The research area was set up in Gangwon-do, including Inje, Gangneung, and Pyeongchang, where landslides occurred frequently and damaged. Landslide-related factors include slope, curvature, stream power index (SPI), topographic wetness index (TWI), topographic position index (TPI), timber diameter, timber age, lithology, land use, soil depth, soil parent material, lineament density, fault density, normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were used. Landslide-related factors were built into a spatial database through data preprocessing, and landslide susceptibility map was predicted using deep neural network (DNN) and CNN models. The model and landslide susceptibility map were verified through average precision (AP) and root mean square errors (RMSE), and as a result of the verification, the patch-based CNN model showed 3.4% improved performance compared to the pixel-based DNN model. The results of this study can be used to predict landslides and are expected to serve as a scientific basis for establishing land use policies and landslide management policies.

• Journal of Bio-Environment Control
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• v.31 no.1
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• pp.43-51
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• 2022

This study was conducted to investigate the effect of ventilation at high temperature on the control of powdery mildew, silverleaf whitefly two-spotted spider mite occurred at Korean melon cultivation greenhouse, and on leaf rolling and flowering of the plant in summer season. 'Alchanggul' grafted onto 'Hidden Power' rootstock was planted on soil bed with the distance of 40 cm. Three ventilation temperatures of 45℃, 40℃, and 35℃ as set points were compared. Ventilation treatment was done by control of side window operation from 18th June to 13th July when silverleaf whitefly, mite, and powdery mildew were occurred in all greenhouses. The temperature inside greenhouse was increased up to the set temperature point on sunny days and maintained for about 9 hours with high relative humidity at 45℃ condition. The differences of day maximum air temperature and day minimum RH were the highest at 45℃ treatment. After 11 days of treatments, the damage by powdery mildew and two-spotted spider mite was almost recovered at 45℃ treatment but not at 40 and 35℃. The population of silverleaf whitefly and two-spotted spider mite were significantly decreased at 45℃ treatment at 14 days after treatment, while powdery mildew symptom was not significantly decreased. Leaf rolling was observed at high temperature but not severe at 45℃ treatment. After 26 days of treatments, female flowers did not bloom at all at 45℃ treatment, and the number of male flowers was 1.2 among 15 nodes of newly grown shoots. As the result, it indicates that ventilation at the high temperature of 45℃ for about 2 to 3 weeks can be an applicable method to control above mentioned pests and disease, and to recover the vegetative growth of Korean melon by reducing flowering of the plant.

• Korean small business review
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• v.42 no.4
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• pp.69-102
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• 2020

Shedding new light on the research trend on entrepreneurial ecosystems in the 40-year history of the Asia Pacific Journal of Small Business, this study aims at exploring a potential measurement framework of ecological inputs and outputs in an entrepreneurial ecosystem that promotes entrepreneurship at geographical and spatial levels. As a result of the analysis of research on the entrepreneurial ecosystem in the journal, we found that prior studies emphasized the managerial importance of various ecological factors on the premise of possible causalities between the factors and entrepreneurship. However, empirical research to verify the premised causality has been underexplored yet. This literature gap may lead to unbalanced development of conceptual and case studies that identify requirements for successful entrepreneurial ecosystems based on experiential facts, thereby hindering the generalization of the research results for practical implications. In that there is a growing interest in creating and operating productive entrepreneurial ecosystems as an innovation engine that drives national and regional economic growth, it is necessary to explore and develop the measurement framework for ecological factors that can be used in future empirical research. Hereupon, we apply a conceptual model of 'input-output-outcome-impact' to categorize individual environmental factors identified in prior studies. Based on the model. We operationalize ecological input factors as the financial, intellectual, institutional, and social capitals, and ecological output factors as the establishment-based, innovation-based, and performance-based entrepreneurship. Also, we propose several longitudinal databases that future empirical research can use in analyzing the potential causality between the ecological input and output factors. The proposed framework of entrepreneurial ecosystems, which focuses on measuring ecological input and output factors, has a high application value for future research that analyzes the causality.

• Journal of Korean Society of Forest Science
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• v.111 no.2
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• pp.201-223
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• 2022

Currently, species extinctions are increasing due to climate change and continued anthropogenic impact. We selected 300 species for conservation with emphasis on plants co-occurring in the Baekdudaegan area, which is a large ecological axis of Korea. We aimed to investigate the vegetation community and environmental characteristics of Zabelia tyaihyonii in the limestone habitat among the target plant species in the Baekdudaegan region to derive effective conservation strategies. In Danyang-gun, Yeongwol-gun, and Jecheon-si, we selected 36 investigation sites where Z. tyaihyonii was present. We investigated the vegetation, flora, soil and physical environment. We also found notable plants such as Thalictrum petaloideum, Sillaphyton podagraria, and Neillia uekii at the investigation sites. We classified forest vegetation community types into 4 vegetation units and 7 species group types. With canonical correspondence analysis (CCA) of the vegetation community and habitat factors, we determined the overall explanatory power to be 75.2%, and we classified the environmental characteristics of the habitat of Z. tyaihyonii into a grouping of three. Among these, we detected a relationship between the environmental factors elevation, slope, organic matter, rock ratio, pH, potassium, and sodium. We identified numerous rare and endemic plants, including Thalictrum petaloideum, in the investigation site, and determined that these groups needed to be preserved at the habitat level. In the classification of the vegetation units analyzed based on the emerging plants and the CCA, we reaffirmed the uniqueness and specificity of the vegetation community in the habitat of Z. tyaihyonii. We anticipate that our results will be used as scientific evidence for the empirical conservation of the native habitats of Z. tyaihyonii.

• The Journal of Engineering Geology
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• v.32 no.4
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• pp.697-723
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• 2022

Data-driven models to predict groundwater levels 30 days in advance were developed for 12 groundwater monitoring stations in the middle-Jeju watershed, Jeju Island. Stacked long short-term memory (stacked-LSTM), a deep learning technique suitable for time series forecasting, was used for model development. Daily time series data from 2001 to 2022 for precipitation, groundwater usage amount, and groundwater level were considered. Various models were proposed that used different combinations of the input data types and varying lengths of previous time series data for each input variable. A general procedure for deep-learning-based model development is suggested based on consideration of the comparative validation results of the tested models. A model using precipitation, groundwater usage amount, and previous groundwater level data as input variables outperformed any model neglecting one or more of these data categories. Using extended sequences of these past data improved the predictions, possibly owing to the long delay time between precipitation and groundwater recharge, which results from the deep groundwater level in Jeju Island. However, limiting the range of considered groundwater usage data that significantly affected the groundwater level fluctuation (rather than using all the groundwater usage data) improved the performance of the predictive model. The developed models can predict the future groundwater level based on the current amount of precipitation and groundwater use. Therefore, the models provide information on the soundness of the aquifer system, which will help to prepare management plans to maintain appropriate groundwater quantities.

• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.504-512
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• 2022

To examine the distribution of internal solar radiation within various locations in multi-span greenhouses, the solar radiation, light transmittance, and accumulated radiation at the central and lateral sections were analyzed by dividing 8:30 to 12:30 in the morning and 12:35 to 16:30 in the afternoon. The growth and yield of tomatoes within these sections were also compared. In the morning, the solar radiation of the central section and the side section was 275.2 W·m^-2 and 314.9 W·m^-2, while in the afternoon, it was 314.9 W·m^-2 and 313.9 W·m^-2, respectively. The light transmittance and accumulated radiation were also low, confirming the low distribution of solar radiation in the central (connecting) section of the multi-span greenhouses. The growth survey revealed no significant difference. The final yield of tomatoes per plant was 4,828 g in the central section and 4,851 g in the lateral section, but there was no significant difference in the central section compared to the lateral section by 0.5%. However, the amount of solar radiation as per time in the central section is higher than the light compensation point, 60 W·m^-2, and slightly lower than the light saturation point of tomatoes, i.e., 281 W·m^-2. The results of this study can help in greenhouse design based on the insolation environment.

• Ecology and Resilient Infrastructure
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• v.9 no.3
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• pp.163-173
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• 2022

Climate change is a key factor that greatly influences changes in the biological seasons and geographical distribution of species. In the ecological field, the BioClimatic predictor (BioClim), which is most related to the physiological characteristics of organisms, is used for vulnerability assessment. However, BioClim values are not provided other than the future period climate average values for each GCM for the Shared Socio-economic Pathways (SSPs) scenario. In this study, BioClim data suitable for domestic conditions was produced using 1 km resolution SSPs scenario detailed data produced by Rural Development Administration, and based on the data, a species distribution model was applied to mainly grow in southern, Gyeongsangbuk-do, Gangwon-do and humid regions. Appropriate habitat distributions were predicted every 30 years for the base years (1981 - 2010) and future years (2011 - 2100) of the Acer pictum subsp. mono. Acer pictum subsp. mono appearance data were collected from a total of 819 points through the national natural environment survey data. In order to improve the performance of the MaxEnt model, the parameters of the model (LQH-1.5) were optimized, and 7 detailed biolicm indices and 5 topographical indices were applied to the MaxEnt model. Drainage, Annual Precipitation (Bio12), and Slope significantly contributed to the distribution of Acer pictum subsp. mono in Korea. As a result of reflecting the growth characteristics that favor moist and fertile soil, the influence of climatic factors was not significant. Accordingly, in the base year, the suitable habitat for a high level of Acer pictum subsp. mono is 3.41% of the area of Korea, and in the near future (2011 - 2040) and far future (2071 - 2100), SSP1-2.6 accounts for 0.01% and 0.02%, gradually decreasing. However, in SSP5-8.5, it was 0.01% and 0.72%, respectively, showing a tendency to decrease in the near future compared to the base year, but to gradually increase toward the far future. This study confirms the future distribution of vegetation that is more easily adapted to climate change, and has significance as a basic study that can be used for future forest restoration of climate change-adapted species.

• Journal of Bio-Environment Control
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• v.32 no.1
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• pp.48-56
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• 2023

High-pressure sodium (HPS) lamps have been widely used as a useful supplemental light source to emit sufficient photosynthetically active radiation and provide a radiant heat, which contribute the heat requirement in greenhouses. The objective of this study to analyze the thermal characteristics of HPS lamp and thermal behavior in supplemented greenhouse, and evaluate the performance of a horizontal leaf temperature of sweet pepper plants using computational fluid dynamics (CFD) simulation. We simulated horizontal leaf temperature on upper canopy according to three growth stage scenarios, which represented 1.0, 1.6, and 2.2 plant height, respectively. We also measured vertical leaf and air temperature accompanied by heat generation of HPS lamps. There was large leaf to air temperature differential due to non-uniformity in temperature. In our numerical calculation, thermal energy of HPS lamps contributed of 50.1% the total heat requirement on Dec. 2022. The CFD model was validated by comparing measured and simulated data at the same operating condition. Mean absolute error and root mean square error were below 0.5, which means the CFD simulation values were highly accurate. Our result about vertical leaf and air temperature can be used in decision making for efficient thermal energy management and crop growth.