• Journal of Korea Water Resources Association
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• v.54 no.10
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• pp.807-817
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• 2021

In this study, assessment of vulnerability in the management of spatio-temporal groundwater resources considering the surface waterground water interactions was conducted in administrative districts of mountainous regions in Korea. Mountainous regions were classified into four regions and spatial groundwater resources management vulnerability assessment criteria were selected to consider the surface water-ground water interactions. Paju in the central mountainous region, Gapyeongin the mountains region, Gurye in the southwestern mountainous region, and Yangsan in the southeastern mountainous region were selected as a result of the selection of vulnerable area for groundwater resources management. Assessment of the Monthly vulnerability to groundwater resource management due to changes in groundwater levels and infiltration was carried out in the selected areas. As a result of monthly vulnerability to groundwater resources management, December ~ Feburary was assessed as vulnerable to groundwater resource management. The results of this study are expected to contribute to the more efficient groundwater resource management measures by administrative district

• Korean Journal of Remote Sensing
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• v.37 no.5_3
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• pp.1405-1423
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• 2021

Precipitation is one of the main factors that affect water and energy cycles, and its estimation plays a very important role in securing water resources and timely responding to water disasters. Satellite-based quantitative precipitation estimation (QPE) has the advantage of covering large areas at high spatiotemporal resolution. In this study, machine learning-based rainfall intensity models were developed using Himawari-8 Advanced Himawari Imager (AHI) water vapor channel (6.7 ㎛), infrared channel (10.8 ㎛), and weather radar Column Max (CMAX) composite data based on random forest (RF). The target variables were weather radar reflectivity (dBZ) and rainfall intensity (mm/hr) converted by the Z-R relationship. The results showed that the model which learned CMAX reflectivity produced the Critical Success Index (CSI) of 0.34 and the Mean-Absolute-Error (MAE) of 4.82 mm/hr. When compared to the GeoKompsat-2 and Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN)-Cloud Classification System (CCS) rainfall intensity products, the accuracies improved by 21.73% and 10.81% for CSI, and 31.33% and 23.49% for MAE, respectively. The spatial distribution of the estimated rainfall intensity was much more similar to the radar data than the existing products.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1589-1597
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• 2021

Submarine groundwater discharge (SGD) in coastal areas is gaining importance as a major transport route that bring nutrients and trace metals into the ocean. This paper describes the analysis of the seasonal changes and spatiotemporal characteristicsthrough the modeling monthly SGD for 35 years from 1986 to 2020 for the Nakdong river basin. In this study, we extracted 210 watersheds and SGD estimation points using the SRTM (Shuttle Radar Topography Mission) DEM (Digital Elevation Model). The average annual SGD of the Nakdong River basin was estimated to be 466.7 m²/yr from the FLDAS (Famine Early Warning Systems Network Land Data Assimilation System) recharge data of 10 km which is the highest resolution global model applicable to Korea. There was no significant time-series variation of SGD in the Nakdong river basin, but the concentrated period of SGD was expanded from summer to autumn. In addition, it was confirmed that there is a large amount of SGD regardless of the season in coastal area nearby large rivers, and the trend has slightly increased since the 1980s. The characteristics are considered to be related to the change in the major precipitation period in the study area, and spatially it is due to the high baseflow-groundwater in the vicinity of large rivers. This study is a precedentstudy that presents a modeling technique to explore the characteristics of SGD in Korea, and is expected to be useful as foundational information for coastal management and evaluating the impact of SGD to the ocean.

• Korean Journal of Remote Sensing
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• v.37 no.6_3
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• pp.1931-1942
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• 2021

As the utility of an optical satellite image with a high spatial resolution (i.e., fine-scale) has been emphasized, recently, various studies of the land surface monitoring using those have been widely carried out. However, the usefulness of fine-scale satellite images is limited because those are acquired at a low temporal resolution. To compensate for this limitation, the spatiotemporal data fusion can be applied to generate a synthetic image with a high spatio-temporal resolution by fusing multiple satellite images with different spatial and temporal resolutions. Since the spatio-temporal data fusion models have been developed for mid or low spatial resolution satellite images in the previous studies, it is necessary to evaluate the applicability of the developed models to the satellite images with a high spatial resolution. For this, this study evaluated the applicability of the developed spatio-temporal fusion models for KOMPSAT-3A and Sentinel-2 images. Here, an Enhanced Spatial and Temporal Adaptive Fusion Model (ESTARFM) and Spatial Time-series Geostatistical Deconvolution/Fusion Model (STGDFM), which use the different information for prediction, were applied. As a result of this study, it was found that the prediction performance of STGDFM, which combines temporally continuous reflectance values, was better than that of ESTARFM. Particularly, the prediction performance of STGDFM was significantly improved when it is difficult to simultaneously acquire KOMPSAT and Sentinel-2 images at a same date due to the low temporal resolution of KOMPSAT images. From the results of this study, it was confirmed that STGDFM, which has relatively better prediction performance by combining continuous temporal information, can compensate for the limitation to the low revisit time of fine-scale satellite images.

• Journal of the Korean Institute of Landscape Architecture
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• v.46 no.6
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• pp.97-110
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• 2018

This study examined the value of the old roads and roadscapes as modern assets. Topographic maps of the two years (1916 and 1919, which were produced by the Japanese Government-General of Korea) and the digital topographic map produced in 2017, were analyzed. The total amount of roads that have survived for the past 100 years are located in 108 places and total 26.32km. After examining the remnants of the roads in YeongDo, the type of scenery experienced along the roads were classified into nine kinds. The place where a sequential scenery experience takes place due to the survival of the past, the experience is based on the transition of historical scenery, not the scenery of the present time. A new model that can preserve, manage and plan this scenery is required. Therefore, we propose a new landscape model that elevates the concept of gaze from a spatial concept to a spatiotemporal concept. Based on this model, we propose a conservation criterion of the landscape viewed on the road as a viewpoint. As a modern asset for the next 100 years of YeongDo, it is necessary to understand and preserve the meaning of the landscape and roadside scenery as a transit landscape network. The remnant of roads from 100 years ago suggests that the scenery on the road was has been maintained, and it is the historical landscape of the YeongDo area. Through the landscape conservation plan proposed in this study, it is expected that the historical roads and their landscape will be positioned as a modern asset and an aspect of local heritage, and the future conservation and management of the roads and roadscapes will continue.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.3
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• pp.461-467
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• 2019

Advances in location-aware and IoT (Internet of Things) technology increase the rapid generation of massive movement data. Knowledge discovery from massive movement data helps us to understand the urban flow and traffic management. This paper proposes a method to analyze frequent origin-destination sequence patterns from irregular spatiotemporal taxi pick-up locations. The proposed method starts by conducting cluster analysis and then run a frequent sequence pattern analysis based on identified clusters as a base unit. The experimental data is Seoul taxi trajectory data between 7 a.m. and 9 a.m. during one week. The experimental results present that significant frequent sequence patterns occur within Gangnam. The significant frequent sequence patterns of different regions are identified between Gangnam and Seoul City Hall area. Further, this study uses administrative boundaries as a base unit. The results based on administrative boundaries fails to detect the frequent sequence patterns between different regions. The proposed method can be applied to decrease not only taxis' empty-loaded rate, but also improve urban flow management.

• Journal of Ecology and Environment
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• v.45 no.3
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• pp.143-151
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• 2021

Background: Plants are able to optimize defense responses induced by various herbivores, which have different feeding strategies. Local and systemic responses within a plant after herbivory are essential to modulate herbivore-specific plant responses. For instance, leaf-chewing herbivores elicit jasmonic acid signaling, which result in the inductions of toxic chemicals in the attacked leaf (tissue-specific responses) and also in the other unattacked parts of the plant (systemic responses). Root herbivory induces toxic metabolites in the attacked root and alters the levels of transcripts and metabolites in the unattacked shoot. However, we have little knowledge of the local and systemic responses against stem-boring herbivores. In this study, we examined the systemic changes in metabolites in the wild tobacco Nicotiana attenuata, when the stem-boring herbivore Trichobaris mucorea attacks. Results: To investigate the systemic responses of T. mucorea attacks, we measured the levels of jasmonic acid (JA), JA-dependent secondary metabolites, soluble sugars, and free amino acids in 7 distinct tissues of N. attenuata: leaf lamina with epidermis (LLE), leaf midrib (LM), stem epidermis (SE), stem pith (SP), stem vascular bundle (SV), root cortex with epidermis (RCE), and root vascular bundle (RV). The levels of JA were increased in all root tissues and in LM by T. mucorea attacks. The levels of chlorogenic acids (CGAs) and nicotine were increased in all stem tissues by T. mucorea. However, CGA was systematically induced in LM, and nicotine was systematically induced in LM and RCE. We further tested the resource allocation by measuring soluble sugars and free amino acids in plant tissues. T. mucorea attacks increased the level of free amino acids in all tissues except in LLE. The levels of soluble sugars were significantly decreased in SE and SP, but increased in RV. Conclusions: The results reveal that plants have local- and systemic-specific responses in response to attack from a stem-boring herbivore. Interestingly, the level of induced secondary metabolites was not consistent with the systemic inductions of JA. Spatiotemporal resolution of plant defense responses against stem herbivory will be required to understand how a plant copes with attack from herbivores from different feeding guilds.

• Journal of the Society of Disaster Information
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• v.17 no.3
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• pp.655-666
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• 2021

Purpose: This study is to develop a method for measuring dynamic speeding risks using vehicle trajectory big data and to demonstrate the feasibility of the devised speeding index. Method: The speed behaviors of vehicles were analysed in microscopic space and time using individual vehicle trajectories, and then the boundary condition of speeding (i.e., boundary speed) was determined from the standpoint of crash risk. A novel index for measuring the risk exposure of speeding was developed in microscopic space and time with the boundary speed. Result: A validation study was conducted with vehicle-GPS trajectory big data and ground-truth vehicle crash data. As a result of the analysis, it turned out that the index of speeding-risk exposure has a strong explanatory power (R²=0.7) for motorway traffic accidents. This directly indicates that speeding behaviors should be analysed at a microscopic spatiotemporal dimension. Conclusion: The spatial and temporal evolution of vehicle velocity is very variable. It is, hence, expected that the method presented in this study could be efficaciously employed to analyse the causal factors of traffic accidents and the crash risk exposure in microscopic space using mobility trajectory data.

• Atmosphere
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• v.31 no.2
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• pp.241-249
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• 2021

A smart city utilizes data collected from various sensors through the internet of things (IoT) and improves city operations across the urban area. Recently substantial research is underway to examine all aspects of data that requires for the smart city operation. Atmospheric data are an essential component for successful smart city implementation, including Urban Air Mobility (UAM), infrastructure planning, safety and convenience, and traffic management. Unfortunately, the current level of conventional atmospheric data does not meet the needs of the new city concept. New and innovative approaches to developing high spatiotemporal resolution of observational and modeling data, resolving the complex urban structure, are expected to support the future needs. The geographic information system (GIS) integrates the atmospheric data with the urban structure and offers information system enhancement. In this study we proposed the necessity and applicability of the high resolution urban meteorological dataset based on heavy fog cases in the smart city region (e.g., Sejong and Pusan) in Korea.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.627-636
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• 2021

Although many studies on ship detection using synthetic aperture radar (SAR) satellite images are being conducted around the world, there are still very few employing SAR microsatellites, as most of the microsatellites are optical satellites. Recently, the ICEYE and Capella Space have embarked on the development of microsatellites with SAR sensor, and similar projects are being initiated globally in line with the flow of the new space era [e.g., for the ICEYE: 18 satellites (~2021); Capella Space: 36 satellites (~2023); and the Coast Guard SAR: 32 satellites in the early development stage]. In preparation for these new systems, it is important to review the SAR microsatellite system and the recent advances in this technology. Accordingly, in this paper, the current status and characteristics of optical and SAR microsatellite constellation operation are described, and studies using them are investigated. In addition, based on the status and characteristics of the representative SAR microsatellites, specifically the ICEYE and Capella systems, methods for using SAR microsatellite data for ship detection applications are described. Our results confirm that the SAR microsatellites operate as a constellation and have the advantages of short revisit cycles and quick provision of high-resolution images. With this technology, we expect SAR microsatellites to contribute greatly to the monitoring a wide-area target vessel, in which the spatiotemporal resolution of the imagery is especially important.