• Korean Journal of Remote Sensing
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• v.34 no.6_4
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• pp.1519-1529
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• 2018

The volcanic ash can spread out over hundreds of kilometers in case of large volcanic eruption. The deposition of volcanic ash may induce damages in urban area and transportation facilities. In order to respond volcanic hazard, it is necessary to estimate efficiently the diffusion area of volcanic ash. The purpose of this study is to compare in-situ volcanic deposition and satellite images of the volcanic eruption case. In this study, we used Near-Infrared (NIR) channels 7 and 8 of Geostationary Ocean Color Imager (GOCI) images for Mt. Aso eruption in 16:40 (UTC) on October 7, 2016. To estimate deposit area clearly, we applied Principal Component Analysis (PCA) and a series of morphology filtering (Eroded, Opening, Dilation, and Closing), respectively. In addition, we compared the field data from the Japan Meteorological Agency (JMA) report about Aso volcano eruption in 2016. From the results, we could extract volcanic ash deposition area of about $380km^2$. In the traditional method, ash deposition area was estimated by human activity such as direct measurement and hearsay evidence, which are inefficient and time consuming effort. Our results inferred that satellite imagery is one of the powerful tools for surface change mapping in case of large volcanic eruption.

• Korean Journal of Remote Sensing
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• v.34 no.6_3
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• pp.1351-1367
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• 2018

Image registration is an essential process for image fusion, change detection and time series analysis using multi-sensor images. For this purpose, we need to detect accurately the difference of scale and rotation between the multi-sensor images with difference spatial resolution. In this paper, we propose a new feature matching method using variable circular template for image registration between multi-resolution images. The proposed method creates a circular template at the center of a feature point in a coarse scale image and also a variable circular template in a fine scale image, respectively. After changing the scale of the variable circular template, we rotate the variable circular template by each predefined angle and compute the mutual information between the two circular templates and then find the scale, the angle of rotation and the center location of the variable circular template, respectively, in fine scale image when the mutual information between the two circular templates is maximum. The proposed method was tested using Kompsat-2, Kompsat-3 and Kompsat-3A images with different spatial resolution. The experimental results showed that the error of scale factor, the error of rotation angle and the localization error of the control point were less than 0.004, $0.3^{\circ}$ and one pixel, respectively.

• Korean Journal of Environmental Biology
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• v.36 no.4
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• pp.626-637
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• 2018

In this study, a series of survey were conducted to identify the distribution patterns of macrobenthos at the Bongam sand tidal flat in Masan Bay. We collected macrobenthos at 9 sampling sites twice in June and September of every year from 2012 to 2017 using a box core sampler (collecting area, $0.025m^2$). There was a total of 50 species with a community density of $6,388ind.m^{-2}$ and a biomass of $313.9g\;wet\;m^{-2}$ during the study period. Polychaetes had the highest number of species and density among the macrofauna, but the mollusks had the largest biomass. The number of species ranged from 10 to 25 during study period but increased to over 20 species in 2014. The density which ranged from $1,508ind.m^{-2}$ to $12,008ind.m^{-2}$ rapidly increased in 2015. The dominant species were all polychaetes such as Heteromastus filiformis, Prionospio japonicus, Hediste diadroma, and Neanthes succinea. The mean diversity index ranged from 1.2 to 1.9, richness index from 1.2 to 2.4, and evenness index from 0.5 to 0.9. From the cluster analysis results, there was a spatial difference in the similarity of faunal composition of macrobenthos and this pattern was maintained throughout the study period, that is, the temporal similarities were higher than the spatial similarities. There was a change in community composition from June 2014 to June 2015 in most of the sampling sites. During this time, the dominant species also changed from H. filiformis and N. succinea to H. filiformis and H. diadroma. The density of opportunistic species such as Capitella capitata and Polydora ligni decreased compared to the early 2000s while the population of H. diadroma increased from 2015. There was little ecological information on H. diadroma such as when and where this species occurred.

• Fire Science and Engineering
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• v.33 no.1
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• pp.76-84
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• 2019

Experimental studies using an open cone calorimeter were conducted to provide information on the CO and soot yields of wood combustibles required for a kitchen fire simulation of PBD. A total of eight specimens were examined for medium density fiberboard (MDF) and particle board (PB), which are used widely in kitchen furniture production, depending on the water content, surface processing method, and surface color. The thermal penetration time related to the fire spread rate in the depth direction differed significantly according to the surface processing treatment method, even for a specimen of identical thickness. The CO yield ($y_{CO}$) of the MDF and PB series did not change significantly according to the combustion mode and surface treatment process in flaming mode. On the other hand, $y_{CO}$ was approximately 10 times higher in smoldering mode than in flaming mode. The soot yield ($y_{soot}$), however, varied considerably depending on the combustion mode and surface treatment process. In particular, a higher $y_{soot}$ was found in flaming mode and in the surface-treated specimens. Finally, the $y_{CO}$ and $y_{soot}$ of MDF and PB measured for the kitchen fire simulation of PBD were applied.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.7
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• pp.528-534
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• 2019

This study analyzes the factors affecting China's carbon emissions from 1985 to 2016. In recent years, the whole industries of China are in the midst of industrialization and have several problems. Now, the low-carbon economy has become the main task of China's economic development. This study analyzes the factors affecting China 's carbon emissions by selecting relevant data onto the Chinese yearbook and using a time series model. The analysis shows that related industries continue to innovate and increase the use of green energy such as electricity, but coal is still the largest share of the energy consumed. As energy use efficiency increases and industrial R&D investment increases year by year, carbon emissions are increasing every year. In addition, there is a stereotype that industry is the biggest factor affecting carbon emissions. The research found that the impact of the industry on China's carbon emissions is declining gradually. While controlling industrial carbon emissions, keeping continue to improve technology development and focusing on carbon emissions from other industries are critical to reduce overall carbon emissions. Based on the empirical results, if we can change stereotypes starting from the nature of the data, we will quickly reach a low carbon sustainable development economy.

• Korean Journal of Environmental Biology
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• v.40 no.1
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• pp.99-111
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• 2022

Vegetation is the basis for biodiversity conservation and sustainable development. In the Environmental Impact Assessment (EIA), which is the most direct and efficient policy measure to prevent degradation of nature, vegetation-related assessment has limitations as it is not based on quantitative and scientific methods. In addition, it focuses on the presence of protected species; hence, it does not take into account the role of vegetation as a habitat on a wide-area scale. As a way to overcome these limitations, this study aims to contribute to the quantification and advancement of future EIA on vegetation. Through the review of previous studies, core areas, connectivity, and vegetation condition were derived as the items to be dealt within the macroscopic aspect of vegetation impact assessment. Each item was spatially constructed using land cover maps and satellite imageries, and time series change analysis was performed. As a result, it was found that vegetation has been continuously deteriorating due to development in all aspects, and in particular, development adversely affects not only the inside of the project site but also the surrounding area. Although this study suggested the direction for improvement of the EIA in the vegetation sector based on data analysis, a more specific methodology needs to be established in order to apply it to the actual EIA process. By actively utilizing various environmental spatial data, the impact of the development on the natural ecosystem can be minimized.

• Journal of Korean Society of Forest Science
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• v.112 no.4
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• pp.530-543
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• 2023

Societal value of the benefits forests provide has grown significantly, given their pivotal role in mitigating climate change and fostering the shift toward a carbon-neutral society. Due to the economic and public value of forests, which extends far beyond landowners and foresters, the forestry sector mutually interacts with society as a whole. Thus, understanding public perceptions and preferences concerning forests and forest policies from the societal viewpoint is vital for shaping future forest policy decisions. This research delved into evolving perceptions over the past 32 years, using a time-series analysis of data gathered from the 'Public awareness survey on forests'. This survey, conducted seven times between 1991 and 2023 by opinion poll agents, provides insights into changing sentiments. The findings reveal a notable increase in public satisfaction with overall forest policies. Specifically, positive sentiments were observed regarding forest rehabilitation, forest trails, education initiatives, and the establishment and functioning of forest recreation facilities. Conversely, the study highlights areas where public satisfaction remained relatively low, notably in matters concerning the use and conversion of mountainous regions, forest disaster prevention, and international forest cooperation. Additionally, the respondents emphasized the need for heightened attention to forest management, the development of forest roads, and increased efforts in overseas afforestation compared to current initiatives.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.5
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• pp.1-14
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• 2023

Soybeans are one of the world's top five staple crops and a major source of plant-based protein. Due to their susceptibility to climate change, which can significantly impact grain production, the National Agricultural Science Institute is conducting research on crop phenotypes through growth analysis of various soybean varieties. While the process of capturing growth progression photos of soybeans is automated, the verification, recording, and analysis of growth stages are currently done manually. In this paper, we designed and trained a YOLOv5s model to detect soybean leaf objects from image data of soybean plants and a Convolution Neural Network (CNN) model to judgement the unfolding status of the detected soybean leaves. We combined these two models and implemented an algorithm that distinguishes layers based on the coordinates of detected soybean leaves. As a result, we developed a program that takes time-series data of soybeans as input and performs growth analysis. The program can accurately determine the growth stages of soybeans up to the second or third compound leaves.

• Korean Journal of Remote Sensing
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• v.40 no.2
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• pp.191-202
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• 2024

Global warming is causing abnormal climates worldwide due to the increase in greenhouse gas concentrations in the atmosphere, negatively affecting ecosystems and humanity. In response, various countries are attempting to reduce greenhouse gas emissions in numerous ways, and interest in blue carbon, carbon absorbed by coastal ecosystems, is increasing. Known to absorb carbon up to 50 times faster than green carbon, blue carbon plays a vital role in responding to climate change. Particularly, the tidal flats of South Korea, one of the world's five largest tidal flats, are valued for their rich biodiversity and exceptional carbon absorption capabilities. While previous studies on blue carbon have focused on the carbon storage and annual carbon absorption rates of tidal flats, there is a lack of research linking tidal flat area changes detected using satellite data to carbon storage. This study applied the direct difference water index to high-resolution satellite data from PlanetScope and RapidEye to analyze the area and changes of the Nakdong River estuary tidal flats over six periods between 2013 and 2023, estimating the carbon storage for each period. The analysis showed that excluding the period in 2013 with a different tidal condition, the tidal flat area changed by up to approximately 5.4% annually, ranging from about 9.38 km² (in 2022) to about 9.89 km² (in 2021), with carbon storage estimated between approximately 30,230.0 Mg C and 31,893.7 Mg C.

• Journal of the Korean Regional Science Association
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• v.40 no.2
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• pp.107-130
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• 2024

Urban land surface temperature (LST) change is a major environmental factor that affects the thermal comfort, energy consumption, and health of urban residents. Most studies that explored the relationship between LST and urban built-environment form analyzed only midday LST. This study explores the diurnal variation of summertime LST in Seoul using ECOSTRESS data, which observes LST at various times of the day and analyzes whether the LST variation differs by built environment type. Launched in 2018, ECOSTRESS operates in a non-sun-synchronous orbit, observing LST with a high resolution of 70 meters. This study collected data from early morning (6:25) to evening (17:26) from 2019 to 2022 to build time-series LST. Based on greenery, water bodies, and building form data, eight types of Seoul's built environment were derived by hierarchical clustering, and the LST fluctuation characteristics of each cluster were compared. The results showed that the spatial disparity in LST increased after dawn, peaked at noon, and decreased again, highlighting areas with rapid versus stable LST changes. Low-rise and high-rise compact districts experienced fast, high temperature increases and high variability, while low-density apartments experienced moderate LST increases and low variability. These results suggest urban forms that can mitigate rapid daytime heating.