• Journal of Korea Water Resources Association
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• v.54 no.9
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• pp.681-692
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• 2021

Vegetation processes have a significant impact on rainfall runoff processes through evapotranspiration control, but are rarely considered in the conceptual lumped hydrological model. This study evaluated the model performance of the Hapcheon Dam watershed by integrating the ecological module expressing the leaf area index data sensed remotely from the satellite into the hydrological partition module. The proposed eco-hydrological model has three main features to better represent the eco-hydrological process in humid regions. 1) The growth rate of vegetation is constrained by water shortage stress in the watershed. 2) The maximum growth of vegetation is limited by the energy of the watershed climate. 3) The interaction of vegetation and aquifers is reflected. The proposed model simultaneously simulates hydrologic components and vegetation dynamics of watershed scale. The following findings were found from the validation results using the model parameters estimated by the SCEM algorithm. 1) Estimating the parameters of the eco-hydrological model using the leaf area index and streamflow data can predict the streamflow with similar accuracy and robustness to the hydrological model without the ecological module. 2) Using the remotely sensed leaf area index without filtering as input data is not helpful in estimating streamflow. 3) The integrated eco-hydrological model can provide an excellent estimate of the seasonal variability of the leaf area index.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1089-1098
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• 2020

In this study, we propose a method to detect red tide Cochlodinium Polykrikoide using by machine learning and geostationary marine satellite images. To learn the machine learning model, GOCI Level 2 data were used, and the red tide location data of the National Fisheries Research and Development Institute was used. The machine learning model used logistic regression model, decision tree model, and random forest model. As a result of the performance evaluation, compared to the traditional GOCI image-based red tide detection algorithm without machine learning (Son et al., 2012) (75%), it was confirmed that the accuracy was improved by about 13~22%p (88~98%). In addition, as a result of comparing and analyzing the detection performance between machine learning models, the random forest model (98%) showed the highest detection accuracy.It is believed that this machine learning-based red tide detection algorithm can be used to detect red tide early in the future and track and monitor its movement and spread.

• Journal of Space Technology and Applications
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• v.1 no.1
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• pp.64-75
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• 2021

On the moon as well as the earth, one of the easiest ways to understand geological formation history of any region is to observe the stratigraphy if it is available, the order in which the strata build up. By analyzing stratigraphy, it is possible to infer what geological events have occurred in the past. Mare Nubium also has an unique normal fault called Rupes Recta that shows stratigraphy. However, a rover moving with wheels is incompetent to explore the cliff since the Rupes Recta has an inclination of 10° - 30°. Therefore, a quadruped walking robot must be employed for stable expedition. To exploration a fault with a four-legged walking robot, it is necessary to design an expedition route by taking account of whether the stratigraphy is well displayed, whether the slope of the terrain is moderate, and whether there are obstacles and rough texture in the terrain based on the remote sensing data from the previous lunar missions. For the payloads required for fault surface exploration we propose an optical camera to grasp the actual appearance, a spectrometer to analyze the composition, and a drill to obtain samples that are not exposed outward.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.6
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• pp.1249-1258
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• 2022

Marine debris is defined as a substance that is intentionally or inadvertently left on the shore or is introduced or discharged into the ocean, which has or is likely to have a harmful effect on the marine environments. In this study, the detection of marine debris and the analysis of the amount of change on marine debris were performed using the object detection method for an efficient method of identifying the quantity of marine debris and analyzing the amount of change. The study area is Yuho Mongdol Beach in the northeastern part of Geoje Island, and the amount of change was analyzed through images collected at 15-minute intervals for 32 days from September 12 to October 14, 2022. Marine debris detection using YOLOv5x, a one-stage object detection model, derived the performance of plastic bottles mAP 0.869 and styrofoam buoys mAP 0.862. As a result, marine debris showed a large decrease at 8-day intervals, and it was found that the quantity of Styrofoam buoys was about three times larger and the range of change was also larger.

• Economic and Environmental Geology
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• v.56 no.6
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• pp.817-830
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• 2023

This study investigates the age of the surficial rocks in the Arunta region using Uranium-Lead (U-Pb) geochronological dating. Rock samples were collected at four locations, Cattle-Water Pass (CP 1610), Gough Dam (GD 1622 and GD 1610), and London-Eye (LE 1601), within the Strangways Metamorphic Complex and crushed by selFragging. Subsequently, the zircon grains were imaged using Cathodoluminescence (CL) analysis and the U-Pb (uranium and lead) isotope ratios and the chrono-stratigraphy were measured. The imaged zircon revealed an anomalous heterogeneous crystal structure. Ellipses of the samples at locations GD1601, CP1610, and GD1622 fall below the intercept indicating the ages produced discordant patterns, whereas LE1601 intersects the Concordia curve at two points, implying the occurrence of an event of significant impact. For the rock sample at CP1610, the estimated mean age is 1742.2 ± 9.2 Ma with mean squared weighted deviation (MSWD) = 0.49 and probability of equivalence of 0.90; 1748 ± 15 Ma - MSWD = 1.02 and probability of equivalence of 0.40 for GD1622; and 1784.4 ± 9.1 Ma with MSWD of 1.09 and probability of equivalence of 0.37 for LE1601. But for samples at GD1601, two different age groups with different means occurred: 1) below the global mean (1792.2 ± 32 Ma) estimated at 1738.2 ± 14 Ma with MSWD of 0.109 and probability of equivalence of 0.95 and 2) above it with mean of 1838.22 ± 14 Ma, MSWD of 1.6 and probability of equivalence of 0.95. Analysis of the zircon grains has shown a discrepancy in the age range between 1700 Ma and 1800 Ma compared to the ASO dated to have occurred between 440 and 300 Ma. Moreover, apparent similarity in age of the core and rim means that the mineral crystallized relatively quickly without significant interruptions and effect on the isotopic system. This may have constraint the timing and extent of geological events that might have affected the mineral, such as metamorphism or hydrothermal alteration.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.3
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• pp.182-196
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• 2023

Accurate and timely estimation of crop yields is crucial for various purposes, including global food security planning and agricultural policy development. Remote sensing techniques, particularly using vegetation indices (VIs), have show n promise in monitoring and predicting crop conditions. However, traditional VIs such as the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) have limitations in capturing rapid changes in vegetation photosynthesis and may not accurately represent crop productivity. An alternative vegetation index, the near-infrared reflectance of vegetation (NIRv), has been proposed as a better predictor of crop yield due to its strong correlation with gross primary productivity (GPP) and its ability to untangle confounding effects in canopies. In this study, we investigated the potential of NIRv in estimating crop yield, specifically for corn and soybean crops in major crop-producing regions in 14 states of the United States. Our results demonstrated a significant correlation between the peak value of NIRv and crop yield/area for both corn and soybean. The correlation w as slightly stronger for soybean than for corn. Moreover, most of the target states exhibited a notable relationship between NIRv peak and yield, with consistent slopes across different states. Furthermore, we observed a distinct pattern in the yearly data, where most values were closely clustered together. However, the year 2012 stood out as an outlier in several states, suggesting unique crop conditions during that period. Based on the established relationships between NIRv peak and yield, we predicted crop yield data for 2022 and evaluated the accuracy of the predictions using the Root Mean Square Percentage Error (RMSPE). Our findings indicate the potential of NIRv peak in estimating crop yield at the county level, with varying accuracy across different counties.

• Korean Journal of Remote Sensing
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• v.36 no.5_2
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• pp.867-879
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• 2020

As the era of space technology utilization is approaching, the launch of CAS (Compact Advanced Satellite) 500-1/2 satellites is scheduled during 2021 for acquisition of high-resolution images. Accordingly, the increase of image usability and processing efficiency has been emphasized as key design concepts of the CAS 500-1/2 ground station. In this regard, "CAS 500-1/2 Image Acquisition and Utilization Technology Development" project has been carried out to develop core technologies and processing systems for CAS 500-1/2 data collecting, processing, managing and distributing. In this paper, we introduce the results of the above project. We developed an operation system to generate precision images automatically with GCP (Ground Control Point) chip DB (Database) and DEM (Digital Elevation Model) DB over the entire Korean peninsula. We also developed the system to produce ortho-rectified images indexed to 1:5,000 map grids, and hence set a foundation for ARD (Analysis Ready Data)system. In addition, we linked various application software to the operation system and systematically produce mosaic images, DSM (Digital Surface Model)/DTM (Digital Terrain Model), spatial feature thematic map, and change detection thematic map. The major contribution of the developed system and technologies includes that precision images are to be automatically generated using GCP chip DB for the first time in Korea and the various utilization product technologies incorporated into the operation system of a satellite ground station. The developed operation system has been installed on Korea Land Observation Satellite Information Center of the NGII (National Geographic Information Institute). We expect the system to contribute greatly to the center's work and provide a standard for future ground station systems of earth observation satellites.

• Journal of the Korean earth science society
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• v.27 no.4
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• pp.450-463
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• 2006

Seasonal threshold values for fog detection over the ten airport areas within the Korean Peninsula have been derived from the data of polar-orbit Aqua/Terra MODIS and geostationary GOES-9 during a two years. The values are obtained from reflectance at $0.65{\mu}m\;(R_{0.65})$ and the difference in brightness temperature between $3.7{\mu}m\;and\;11{\mu}m\;(T_{3.7-11})$. In order to examine the discrepancy between the threshold values of two kinds of satellites, the following four parameters have been analyzed under the condition of daytime/nighttime and fog/clear-sky, utilizing their simultaneous observations over the Seoul metropolitan area: brightness temperature at $3.7{\mu}m$, the temperature at $11{\mu}m,\;the\;T_{3.7-11}$ for day and night, and the $R_{0.65}$ for daytime. The parameters show significant correlations (r<0.5) in spatial distribution between the two kinds of satellites. The discrepancy between their infrared thresholds is mainly due to the disagreement in their spatial resolutions and spectral bands, particularly at $3.7{\mu}m$. Fog detection from GOES-9 over the nine airport areas except the Cheongju airport has revealed accuracy of 60% in the daytime and 70% in the nighttime, based on statistical verification. The accuracy decreases in foggy cases with twilight, precipitation, short persistence, or the higher cloud above fog. The sensitivity of radiance and reflectance with wavelength has been analyzed in numerical experiments with respect to various meteorological conditions to investigate optical characteristics of the three channels.

• Journal of the Korean earth science society
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• v.39 no.3
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• pp.228-240
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• 2018

Solar energy is calculated using meteorological (14 station), ceilometer (2 station) and microwave radiometer (MWR, 7 station)) data observed from the Weather Information Service Engine (WISE) on the Seoul metropolitan area. The cloud optical thickness and the cloud fraction are calculated using the back-scattering coefficient (BSC) of the ceilometer and liquid water path of the MWR. The solar energy on the surface is calculated using solar radiation model with cloud fraction from the ceilometer and the MWR. The estimated solar energy is underestimated compared to observations both at Jungnang and Gwanghwamun stations. In linear regression analysis, the slope is less than 0.8 and the bias is negative which is less than $-20W/m^2$. The estimated solar energy using MWR is more improved (i.e., deterministic coefficient (average $R^2=0.8$) and Root Mean Square Error (average $RMSE=110W/m^2$)) than when using ceilometer. The monthly cloud fraction and solar energy calculated by ceilometer is greater than 0.09 and lower than $50W/m^2$ compared to MWR. While there is a difference depending on the locations, RMSE of estimated solar radiation is large over $50W/m^2$ in July and September compared to other months. As a result, the estimation of a daily accumulated solar radiation shows the highest correlation at Gwanghwamun ($R^2=0.80$, RMSE=2.87 MJ/day) station and the lowest correlation at Gooro ($R^2=0.63$, RMSE=4.77 MJ/day) station.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.1
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• pp.101-116
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• 2018

Sustainability science is an emerging transdisciplinary research which necessitates not only the communication and collaboration of scientists, practitioners and stakeholders from different disciplines and interests, but also the paradigm shift from deterministic and reductionist approaches to the old basic. Ecological-societal systems (ESS) are co-evolving complex systems having many interacting parts (or agents) whose random interactions at local scale give rise to spontaneous emerging order at global scale (i.e., self-organization). Here, the flows of energy, matter and information between the systems and their surroundings play a key role. We introduce a conceptual framework for such continually morphing dynamical systems, i.e. self-organizing hierarchical open systems (SOHOs). To understand the structure and functionality of SOHOs, we revisit the two fundamental laws of physics. Re-interpretation of these principles helps understand the destiny and better path toward sustainability, and how to reconcile ecosystem integrity with societal vision and value. We then integrate the so-called visioneering (V) framework with that of SOHOs as feedback/feedforward loops so that 'a nudged self-organization' may guide systems' agents to work together toward sustainable ESS. Finally, example is given with newly endorsed Sustainable Development Goals (SDG) Lab (i.e., 'Rural systems visioneering') by Future Earth, which is now underway in rural villages in Tanzania.