• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1413-1425
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• 2023

The increasing frequency of wildfires due to climate change is causing extreme loss of life and property. They cause loss of vegetation and affect ecosystem changes depending on their intensity and occurrence. Ecosystem changes, in turn, affect wildfire occurrence, causing secondary damage. Thus, accurate estimation of the areas affected by wildfires is fundamental. Satellite remote sensing is used for forest fire detection because it can rapidly acquire topographic and meteorological information about the affected area after forest fires. In addition, deep learning algorithms such as convolutional neural networks (CNN) and transformer models show high performance for more accurate monitoring of fire-burnt regions. To date, the application of deep learning models has been limited, and there is a scarcity of reports providing quantitative performance evaluations for practical field utilization. Hence, this study emphasizes a comparative analysis, exploring performance enhancements achieved through both model selection and data design. This study examined deep learning models for detecting wildfire-damaged areas using Landsat 8 satellite images in California. Also, we conducted a comprehensive comparison and analysis of the detection performance of multiple models, such as U-Net and High-Resolution Network-Object Contextual Representation (HRNet-OCR). Wildfire-related spectral indices such as normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as input channels for the deep learning models to reflect the degree of vegetation cover and surface moisture content. As a result, the mean intersection over union (mIoU) was 0.831 for U-Net and 0.848 for HRNet-OCR, showing high segmentation performance. The inclusion of spectral indices alongside the base wavelength bands resulted in increased metric values for all combinations, affirming that the augmentation of input data with spectral indices contributes to the refinement of pixels. This study can be applied to other satellite images to build a recovery strategy for fire-burnt areas.

• Journal of the Ergonomics Society of Korea
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• v.35 no.4
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• pp.193-204
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• 2016

Objective: This study carried out base research to build an agricultural safety monitoring system through ICT convergence to reduce safety accidents and enhance welfare in life in the agricultural field. Background: The functions and values of rural villages as the space of living are recognized anew, but occupational accident rate due to farm work accidents is on the rise each year. Therefore, the seriousness of such a problem emerges. The convergence technology combining ICT is recently applied to industries overall, and therefore better services are offered. However, studies on ICT convergence has not yet been applied to the agricultural safety field. Method: This study identified ICT convergence service technology trends and representative serious accident types mainly occurring in agricultural activities. This study defined the major factors of farm work accidents and ICT to solve those accident factors including the sensor technology, wired/wireless communication technology and location information service, and applied them to prototype PCB for the development of an agricultural safety monitoring system. Results: This study proposed an emergency monitoring system for farmers and a harmful environment monitoring system. The ICT technology to prevent farm work accidents can be summarized as sensing technology, ICT and network technology and user interface technology. This study also designed PCB module configuration and situation judgment algorithm as basic research for proposed monitoring system development. Conclusion: The ICT-based agricultural safety monitoring research proposed in this study is expected to become the basis to build a future real time monitoring system, and also is expected to contribute to social safety and welfare service improvement for farmers. Application: The ICT convergence farmer accident prevention system will make contributions to the prevention of serious farm work accidents.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.6
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• pp.121-131
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• 2018

Climate change has caused changes in environmental factors that have a direct impact on agriculture such as temperature and precipitation. The meteorological disaster that has the greatest impact on agriculture is drought, and its forecasts are closely related to agricultural production and water supply. In the case of terrestrial data, the accuracy of the spatial map obtained by interpolating the each point data is lowered because it is based on the point observation. Therefore, acquisition of various meteorological data through satellite imagery can complement this terrestrial based drought monitoring. In this study, Evaporative Stress Index (ESI) was used as satellite data for drought determination. The ESI was developed by NASA and USDA, and is calculated through thermal observations of GOES satellites, MODIS, Landsat 5, 7 and 8. We will identify the difference between ESI and other satellite-based drought assessment indices (Vegetation Health Index, VHI, Leaf Area Index, LAI, Enhanced Vegetation Index, EVI), and use it to analyze the drought in South Korea, and examines the applicability of ESI as a new indicator of agricultural drought monitoring.

• Smart Structures and Systems
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• v.14 no.3
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• pp.469-477
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• 2014

As a kind of intelligent materials, conductive asphalt concrete has a broad application prospect including melting ice and snow on the pavement, closing cracks in asphalt concrete, sensing pavement damage, and so on. Conductive pavement will be suffered from fatigue failure as conventional pavement in the process of service, and this fatigue damage of internal structure can be induced by electrical signal output. The characteristics of electrical signal variation of conductive asphalt concrete in the process of fatigue cracking were researched in this paper. The whole process was clearly divided into three stages according to resistance changes, and the development of fatigue damage wasn't obvious in stage I and stage II, while in stage III, the synchronicity between the resistance and damage began to appear. Thus, fatigue damage variable D and initial damage value $D_0$ represented by the functions of resistance were introduced in stage III. After calculating the initial damage value $D_0$ under different stress levels, it was concluded that the initial damage value $D_0$ had no noticeable change, just ranged between 0.24 and 0.25. This value represented a critical point which could be used to inform the repair time of early fatigue damage in the conductive asphalt pavement.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.22 no.1
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• pp.61-72
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• 2019

With the diversification of research using UAV(Unmanned Aerial Vehicle)s, the possibility of remote sensing research for urban green spaces is increasing. UAVs can be used as an investigation method to monitor the successful construction of the park and the planting of vegetation since its creation. This study was carried out to investigate UAVs utilization of urban green space monitoring in Dosol Square. It was photographed three times on May 21, July 13, and September 16, 2018 using DJI Phantom3 pro, Inspire2, and Parrot Sequoia multispectral camera. Orthographic images were overlaid on the planting plan of the site and the construction results were checked, the change of vitality of the plantation area was analyzed by NDVI(Normalized Difference Vegetation Index) and SAVI(Soil Adjusted Vegetation Index). As a result, it was confirmed that the UAVs are very effective for surveying the view of the urban green space after the construction and recording the results, which can be grasped quantitatively by overlaying the planting plan map. UAVs are more likely to be used in terms of monitoring vegetation vitality. It is interpreted that SAVI is better than NDVI in the green space just after composition. Chionanthus retusus and Pinus strobus were analyzed for their low level of vitality, and partially damaged and their vitality was lowered. In addition, there was difficulty in grass planting area and flower garden due to drainage and summer drought problems. In the future, it is expected that orthoimage and multispectral data using UAVs will be useful in the early vegetation monitoring and management field of urban green spaces.

• Journal of The Geomorphological Association of Korea
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• v.23 no.1
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• pp.117-128
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• 2016

High resolution aerial photographs and digital elevation models for Bangpo beach using UAV were generated in this study to analyze the thematic and geometric characteristics of coastal features. Based on 728 aerial images acquired on September 10, 2016 by the UAV, a image mosaic at 2.2 cm spatial resolution and a digital elevation model at 4.4 cm spatial resolution were developed. This study found out that Bangpo beach consisted of intertidal zone and supratidal zone. The intertidal zone can be subdivided into lower part and upper part with distinctive geomorphological characteristics. While the lower part included sand bars and ripple marks along the coastline, the cusps and sand dunes were the major coastal features of the upper part. Part of the intertidal zone was occupied by shore platform with average slope of 0.9 degree containing various sizes of gravels. The supratidal zone slanted toward ocean with berms on the surface with an interval of 15 m. These coastal features indicated the flow intensity towards to the land and tidal effect. It validated that the UAV application in coastal research was very effective analyzing to examine coastal processes.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.168-168
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• 2023

The frequent occurrence of cyanobacterial harmful algal blooms (CHABs) in inland waters under climate change seriously damages the ecosystem and human health and is becoming a big problem in South Korea. Satellite remote sensing is suggested for effective monitoring CHABs at a larger scale of water bodies since the traditional method based on sparse in-situ networks is limited in space. However, utilizing a standalone variable of satellite reflectances in common CHABs dual-models, which relies on both chlorophyll-a (Chl-a) and phycocyanin or cyanobacteria cells (Cyano-cell), is not fully beneficial because their seasonal variation is highly impacted by surrounding meteorological and bio-environmental factors. Along with the development of Artificial Intelligence (AI), monitoring CHABs from space with analyzing the effects of environmental factors is accessible. This study aimed to investigate the potential application of AI in the dual-model strategy (Chl-a and Cyano-cell are output parameters) for monitoring seasonal dynamics of CHABs from satellites over Korean inland waters. The Sentinel-3 satellite was selected in this study due to the variety of spectral bands and its unique band (620 nm), which is sensitive to cyanobacteria. Via the AI-based feature selection, we analyzed the relationships between two output parameters and major parameters (satellite water-leaving reflectances at different spectral bands), together with auxiliary (meteorological and bio-environmental) parameters, to select the most important ones. Several AI models were then employed for modelling Chl-a and Cyano-cell concentration from those selected important parameters. Performance evaluation of the AI models and their comparison to traditional semi-analytical models were conducted to demonstrate whether AI models (using water-leaving reflectances and environmental variables) outperform traditional models (using water-leaving reflectances only) and which AI models are superior for monitoring CHABs from Sentinel-3 satellite over a Korean inland water body.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1188-1190
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• 2003

Taipei Watershed Management Bureau (WRATB) is a government agency entitled for water resources protection at two major watersheds in order to provide drinking water for about four millions population in Taipei on a sustainable basis. At WRATB, there are two major public sewage treatment facilities which can convert sewage in each watershed into an acceptable state before they were discharged into rivers. More than 82% of household wastewater have been collected and treated by the two public sewage systems. However, households at remote area still need more effective sewage management prescriptions. The objective of this paper is to implement geographic information systems in order to provide more effective approaches that sewage management can be easier and cost effective. ArcIMS was implemented for Internet browsing and map server of those sewage facilities on personal computers, laptop computers. In the open field, ArcPAD was implemented with personal digital assistant (PDA) such that compact flash type's global positioning systems (GPS) and digital camera can be utilized with PDA. All sewage facilities digital files were convert into ArcMap format files. MapObjects and visual BASIC were used to create sewage application modules to meet every single technician personal flavor. ASP.NET was implemented for Internet database manipulations of all sewage databases. Mobile GIS was the key component of GIS applications in the open field for sewage management on a basis of house by house. Houses at remote area, which can not cover by the two public sewage systems, were managed by PDA and laptop computers with GPS and digital camera. Sewage management at Taipei Watershed Management Bureau is easier both in the open field and in the office. Integration of GPS, GIS, and PDA makes sewage management in the open field much easier. ArcIMS, MapObjects, ASP.NET and visual BASIC make sewage management can be done in the office and over Internet.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.355-362
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• 1999

With the ready access to the high resolution satellite image data, users of and areas covered by satellite image data are constantly on the rise world-wide. Korea will also be able to take full advantage of the satellite data once the KOMPSAT is successfully launched. Harmonizing satellite data production and application technology and users' needs, along with the guiding policy is essential for promoting satellite data use. Up to now, the Korean government has mainly concentrated on developing production technology for the satellite units. However, the imminent task of independent satellite data production demands a promotion policy for satellite data use. In this context, the policy is defined as an important medium for identifying the role and status of satellite image information at the national level and also Preparing the legal as well as systematic foundation for producing, building, distributing, and packaging satellite data. For example, in the countries with the advanced satellite technology, such as the United States, the United Kingdom, and Australia, digital ortho image and digital elevation model (DEM) are mandatorily included in the National Geographic Framework Data through policy measures. In addition, in order for the efficient provision of the satellite data, separate organization or agency is being in operation for the exclusive production and distribution of the satellite data. The present paper aims to examine the role and status of the satellite data as well as their current status and problems in Korea in reference to the National Spatial Data Infrastructure, and finally to provide the policy directions to promote the satellite data use in public sector on the basis of the preceding analyses.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.2
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• pp.39-52
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• 2020

A high quality, long-term, high-resolution precipitation dataset is an essential in climate analyses and global water cycles. Rainfall data from station observations are inadequate over many parts of the world, especially North Korea, due to non-existent observation networks, or limited reporting of gauge observations. As a result, satellite-based rainfall estimates have been used as an alternative as a supplement to station observations. The Climate Hazards Group Infrared Precipitation (CHIRP) and CHIRP combined with station observations (CHIRPS) are recently produced satellite-based rainfall products with relatively high spatial and temporal resolutions and global coverage. CHIRPS is a global precipitation product and is made available at daily to seasonal time scales with a spatial resolution of 0.05° and a 1981 to near real-time period of record. In this study, we analyze the applicability of CHIRPS data on the Korean Peninsula by supplementing the lack of precipitation data of North Korea. We compared the daily precipitation estimates from CHIRPS with 81 rain gauges across Korea using several statistical metrics in the long-term period of 1981-2017. To summarize the results, the CHIRPS product for the Korean Peninsula was shown an acceptable performance when it is used for hydrological applications based on monthly rainfall amounts. Overall, this study concludes that CHIRPS can be a valuable complement to gauge precipitation data for estimating precipitation and climate, hydrological application, for example, drought monitoring in this region.