• Journal of the Korean Institute of Landscape Architecture
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• v.38 no.2
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• pp.1-8
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• 2010

The purpose of the study was to evaluate the influence of landscaping pavements on WBGT(Wet-Bulb Globe Temperature) of outdoor spaces that lack ventilation and shade at summer midday. The relative humidity(RH), dry-bulb temperature(DT) and globe temperature(GT) were recorded every minute from June to October 2009 at a height of 1.2m above ten experimental beds with different pavements, by a measuring system consisting of an electric humidity sensor(GHM-15), resistance temperature detector(RTD, Pt-100), standard black globe(${\phi} 150mm$) and data acquisition systems(National Instrument's Labview and Compact FieldPoint). Additionally, the surface dry-bulb temperatures also were recorded and compared. The area of each experimental bed was 1.5m(W)${\times}$2.0m(L) and ten different kinds of pavement were used including grass, grass+cubic stone, grass+porous brick, brick, stone panels, cubic stone, interlocking blocks, clay brick, naked soil, gravel and concrete. To prevent interference from ventilation, a 1.5m height cubic steel frame was established around each bed and each vertical side of the frame was covered with transparent polyethylene film. Based on the records of the hottest period from noon to 3 PM on 26 days with a peak dry-bulb temperature over $30^{\circ}C$ at natural condition, the wet-bulb temperature(WT) and WBGT were calculated and compared. The major findings were as follows: 1. The average surface DT was $40.1^{\circ}C$, which is $9^{\circ}C$ higher than that of the natural condition. The surface DT of the pavements with grass were higher than those of concrete and interlocking block. The peak DT of the surface almost every pavement rose to above $50^{\circ}C$ during the hottest time. 2. The averages of DT, WT and GT were $40.1^{\circ}C$, $27.5^{\circ}C$ and $49.1^{\circ}C$, and the peak values rose to $48.1^{\circ}C$, $45.8^{\circ}C$ and $59.5^{\circ}C$, respectively. In spite of slight differences that resulted according to pavements, no coherent differentiating factor could be found. 3. The average WBGT of grass was the highest at $34.3^{\circ}C$ while the others were similar in the range of around $33{\pm}1^{\circ}C$. Meanwhile, the peak WBGT was highest with stone panel at $47.9^{\circ}C$. Though there were some differences according to pavements, and while grass seemed to be worst in terms of WBGT, it seems difficult to say ablolutely that grass was the worst because the measurement was conducted without ventilation and shade during summer daytime hours only, which had temperatures that rose to a dangerous degree(above $45^{\circ}C$ WBGT), withering the grass during the hottest period. The average WBGT resulted also showed that the thermal environment of the pavement without ventilation and shade were at an intolerable level for humans regardless of the pavement type. In summary, the results of this study show that ventilation and shade are more important factor than pavement type in terms of outdoor thermal comfort in summer daylight hours.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.252-252
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• 2017

Nowadays water shortage is becoming one of the biggest problems in the Korea. Many different methods are developed for conservation of water. Soil water management has become the most indispensable factor for augmenting the crop productivity especially on soybean (Glycine max L.) because of their high susceptibility to both water stress and water logging at various growth stages. The farmers have been using irrigation techniques through manual control which farmers irrigate lands at regular intervals. Automatic irrigation systems are convenient, especially for those who need to travel. If automatic irrigation systems are installed and programmed properly, they can even save you money and help in water conservation. Automatic irrigation systems can be programmed to provide automatic irrigation to the plants which helps in saving money and water and to discharge more precise amounts of water in a targeted area, which promotes water conservation. The objective of this study was to determine the possible effect of automatic irrigation systems based on soil moisture on soybean growth. This experiment was conducted on an upland field with sandy loam soils in Department of Southern Area Crop, NICS, RDA. The study had three different irrigation methods; sprinkle irrigation (SI), surface drip irrigation (SDI) and fountain irrigation (FI). SI was installed at spacing of $7{\times}7m$ and $1.8m^3/hr$ as square for per irrigation plot, a lateral pipe of SDI was laid down to 1.2 m row spacing with $2.3L\;h^{-1}$ discharge rate, the distance between laterals was 20 cm spacing between drippers and FI was laid down in 3m interval as square for per irrigation plot. Soybean (Daewon) cultivar was sown in the June $20^{th}$, 2016, planted in 2 rows of apart in 1.2 m wide rows and distance between hills was 20 cm. All agronomic practices were done as the recommended cultivation. This automatic irrigation system had valves to turn irrigation on/off easily by automated controller, solenoids and moisture sensor which were set the reference level as available soil moisture levels of 30% at 10cm depth. The efficiency of applied irrigation was obtained by dividing the total water stored in the effective root zone to the applied irrigation water. Results showed that seasonal applied irrigation water amounts were $60.4ton\;10a^{-1}$ (SI), $47.3ton\;10a^{-1}$ (SDI) and $92.6 ton\;10a^{-1}$ (FI), respectively. The most significant advantage of SDI system was that water was supplied near the root zone of plants drip by drip. This system saved a large quantity of water by 27.5% and 95.6% compared to SI, FI system. The average soybean yield was significantly affected by different irrigation methods. The soybean yield by different irrigation methods were $309.7kg\;10a^{-1}$ from SDI $282.2kg\;10a^{-1}$ from SI, $289.4kg\;10a^{-1}$ from FI, and $206.3kg\;10a^{-1}$ from control, respectively. SDI resulted in increase of soybean yield by 50.1%, 7.0% 9.8% compared to non-irrigation (control), FI and SI, respectively. Therefore, the automatic irrigation system supplied water only when the soil moisture in the soil went below the reference. Due to the direct transfer of water to the roots water conservation took place and also helped to maintain the moisture to soil ratio at the root zone constant. Thus the system is efficient and compatible to changing environment. The automatic irrigation system provides with several benefits and can operate with less manpower. In conclusion, improving automatic irrigation system can contribute greatly to reducing production costs of crops and making the industry more competitive and sustainable.

• Korean Journal of Ecology and Environment
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• v.51 no.1
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• pp.105-123
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• 2018

Currently, satellite images act as essential and important data in water resources, environment, and ecology as well as information of geographic information system. In this paper, we will investigate basic characteristics of satellite images, especially application examples in water resources. In recent years, researches on spatial and temporal characteristics of large-scale regions utilizing the advantages of satellite imagery have been actively conducted for fundamental hydrological components such as evapotranspiration, soil moisture and natural disasters such as drought, flood, and heavy snow. Furthermore, it is possible to analyze temporal and spatial characteristics such as vegetation characteristics, plant production, net primary production, turbidity of water bodies, chlorophyll concentration, and water quality by using various image information utilizing various sensor information of satellites. Korea is planning to launch a satellite for water resources and environment in the near future, so various researches are expected to be activated on this field.

• Korean Journal of Food Science and Technology
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• v.37 no.5
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• pp.768-775
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• 2005

Lentinus edodes powder was added at 1-3%(w/w) to improve functional properties of jocheong. Content of crude protein, ash, crude lipids, total mineral, free sugar and reducing sugar increased with increasing amount of L. edodes powder, while viscosity and solid and carbohydrate contents decreased. Through amino acid analysis, 17 amino acids were identified and quantified, glutamic acid being the major amino acid. No significant differences were observed in fatty acid composition and pH between control and L. edodes powder-added jocheong. Addition of mushroom powder in jocheong decreased lightness, yellowness and redness in Hunter's color value. Sensor score of jucheong containing 1% of L. edodes powder was similar to that of control. Results showed jocheong containing less than 2% L. edodes powder gave highest scores in quality characteristics and sensory evaluation.

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.145-154
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• 2022

Automatic Target Recognition (ATR) technology is emerging as a core technology of Future Combat Systems (FCS). Conventional ATR is performed based on IMINT (image information) collected from the SAR sensor, and various image-based deep learning models are used. However, with the development of IT and sensing technology, even though data/information related to ATR is expanding to HUMINT (human information) and SIGINT (signal information), ATR still contains image oriented IMINT data only is being used. In complex and diversified battlefield situations, it is difficult to guarantee high-level ATR accuracy and generalization performance with image data alone. Therefore, we propose a knowledge graph-based ATR method that can utilize image and text data simultaneously in this paper. The main idea of the knowledge graph and deep model-based ATR method is to convert the ATR image and text into graphs according to the characteristics of each data, align it to the knowledge graph, and connect the heterogeneous ATR data through the knowledge graph. In order to convert the ATR image into a graph, an object-tag graph consisting of object tags as nodes is generated from the image by using the pre-trained image object recognition model and the vocabulary of the knowledge graph. On the other hand, the ATR text uses the pre-trained language model, TF-IDF, co-occurrence word graph, and the vocabulary of knowledge graph to generate a word graph composed of nodes with key vocabulary for the ATR. The generated two types of graphs are connected to the knowledge graph using the entity alignment model for improvement of the ATR performance from images and texts. To prove the superiority of the proposed method, 227 documents from web documents and 61,714 RDF triples from dbpedia were collected, and comparison experiments were performed on precision, recall, and f1-score in a perspective of the entity alignment..

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.449-461
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• 2021

Analysis Ready Data (ARD) for optical satellite images represents a pre-processed product by applying spectral characteristics and viewing parameters for each sensor. The atmospheric correction is one of the fundamental and complicated topics, which helps to produce Top-of-Atmosphere (TOA) and Top-of-Canopy (TOC) reflectance from multi-spectral image sets. Most remote sensing software provides algorithms or processing schemes dedicated to those corrections of the Landsat-8 OLI sensors. Furthermore, Google Earth Engine (GEE), provides direct access to Landsat reflectance products, USGS-based ARD (USGS-ARD), on the cloud environment. We implemented the Orfeo ToolBox (OTB) atmospheric correction extension, an open-source remote sensing software for manipulating and analyzing high-resolution satellite images. This is the first tool because OTB has not provided calibration modules for any Landsat sensors. Using this extension software, we conducted the absolute atmospheric correction on the Landsat-8 OLI images of Railroad Valley, United States (RVUS) to validate their reflectance products using reflectance data sets of RVUS in the RadCalNet portal. The results showed that the reflectance products using the OTB extension for Landsat revealed a difference by less than 5% compared to RadCalNet RVUS data. In addition, we performed a comparative analysis with reflectance products obtained from other open-source tools such as a QGIS semi-automatic classification plugin and SAGA, besides USGS-ARD products. The reflectance products by the OTB extension showed a high consistency to those of USGS-ARD within the acceptable level in the measurement data range of the RadCalNet RVUS, compared to those of the other two open-source tools. In this study, the verification of the atmospheric calibration processor in OTB extension was carried out, and it proved the application possibility for other satellite sensors in the Compact Advanced Satellite (CAS)-500 or new optical satellites.

• Journal of Korea Water Resources Association
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• v.56 no.4
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• pp.235-243
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• 2023

Due to the revision of the River Act and the enactment of the Act on the Investigation, Planning, and Management of Water Resources, a regular bed change survey has become mandatory and a system is being prepared such that local governments can manage water resources in a planned manner. Since the topography of a bed cannot be measured directly, it is indirectly measured via contact-type depth measurements such as level survey or using an echo sounder, which features a low spatial resolution and does not allow continuous surveying owing to constraints in data acquisition. Therefore, a depth measurement method using remote sensing-LiDAR or hyperspectral imaging-has recently been developed, which allows a wider area survey than the contact-type method as it acquires hyperspectral images from a lightweight hyperspectral sensor mounted on a frequently operating drone and by applying the optimal bandwidth ratio search algorithm to estimate the depth. In the existing hyperspectral remote sensing technique, specific physical quantities are analyzed after matching the hyperspectral image acquired by the drone's path to the image of a surface unit. Previous studies focus primarily on the application of this technology to measure the bathymetry of sandy rivers, whereas bed materials are rarely evaluated. In this study, the existing hyperspectral image-based water depth estimation technique is applied to rivers with vegetation, whereas spatio-temporal hyperspectral imaging and cross-sectional hyperspectral imaging are performed for two cases in the same area before and after vegetation is removed. The result shows that the water depth estimation in the absence of vegetation is more accurate, and in the presence of vegetation, the water depth is estimated by recognizing the height of vegetation as the bottom. In addition, highly accurate water depth estimation is achieved not only in conventional cross-sectional hyperspectral imaging, but also in spatio-temporal hyperspectral imaging. As such, the possibility of monitoring bed fluctuations (water depth fluctuation) using spatio-temporal hyperspectral imaging is confirmed.