• 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 Korean Institute of Traditional Landscape Architecture
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• v.34 no.3
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• pp.28-37
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• 2016

Through the research and analysis on the hydrological environment and soil environment of habitats through documentary and field studies over 14 habitats of Euryale ferox Salisb. within Jeollabukdo, with the objective of acquiring the basic data for forming an environment based on plantation of reservoirs that are composed with Euryale ferox, the following results were obtained. As a result of analyzing the construction period of the habitats of Euryale ferox from a total of 14 places, the average period of duration after construction of all subject reservoirs appeared to be 71.8 years. Moreover, when examining the relationship between the age of reservoirs and eutrophication, it could be judged that at least the eutrophication of subsoil and water environment is not an obstacle to the growth of Euryale ferox grows in habitats that have a reservoir age of approximately 70 years or more. As a result of analyzing the gardening of soil sediment of the Euryale ferox habitats, the component ingredients appeared to be composed of 80.2% of clay, 16.7% of silt and 3.1% of sand, and the soil class pursuant to such was classified as 'heavy clay'. The organic matter contents of soil sediment appeared to be an average of 36g/kg, and there appeared to be no noticeable difference between the habitats and non-habitats of Euryale ferox. The water quality environment of Euryale ferox habitat appeared to be pH 6.5~7.9, concentration of dissolved oxygen to be $1.8{\sim}8.8mg/{\ell}$, concentration of COD to be $6.8{\sim}74mg/{\ell}$, floating materials to be $2.0{\sim}213mg/{\ell}$, total nitrogen to be $0.422{\sim}10.723mg/{\ell}$, and phosphate to be $0.003{\sim}0.126mg/{\ell}$. The average DO concentration of Aedang Reservoir at Jeongeup, Daejeong Reservoir at Imsil, and Myeongdeokji at Gimje with high vitality and green coverage ratio of Euryale ferox appeared to be $3.5mg/{\ell}$, total nitrogen to be $1.33mg/{\ell}$, and concentration of phosphorus-phosphate to be $0.061mg/{\ell}$. When comparing such with the entire average value, the DO and total nitrogen concentration appeared to be rather low, and the phosphorus-phosphate concentration appeared to be higher by two times or more, thus, an in-depth study on the correlation of the vitality of Euryale ferox Salisb. and concentration of phosphorate-phosphorus will be needed in the future.

• Journal of the Korean Institute of Landscape Architecture
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• v.39 no.5
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• pp.1-11
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• 2011

Many studies which assessed the function of forest are focused on usage of citizen, but studies which focused on natural-ecological function still lack. Hence, the purpose of this study is to select and apply the evaluation indicators on natural-ecological function of forest as a base research for sustainable planing and management. First, the 35 indicators were selected by the review of the internal and external 56 literature. The 12 indicators among those were reselected as natural-ecological indicator by the first survey and 7 indicators such as green area, connectivity etc. were determined through MCB analysis by the second survey. Also, the weights of 7 indicators for the functional evaluation were computed using AHP analysis by the third survey. As aresult of AHP analysis, the naturality was showed the highest indicator by 0.189, while the NDVI was evaluated the lowest indicator by 0.063. According to the result of evaluating the natural-ecological function on forest in Daegu which was selected as suitable study area, the natural-ecological functions around the Mt. Ap and Mt. Chengryong, top of Mt. Biseul had more than 85 scores, so those were assessed as an excellent area. On the other hand, the functions around the western area of Mt. Waryong and Mt. Macheon, the Mt. Daeni of Dalseong-Gun had less than 50 scores, which means that the area had to be controled by sustainable management. Therefore, we will be able to utilize the basic data for the preservation and management at urban and environmental planning through the results of this study.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2002.11b
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• pp.76-76
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• 2002

무주나무(Lasianthus japonicus Miquel)는 일본, 대만, 중국 등에 분포하고 열대 및 아열대의 상록활엽수림에서만 자라는 것으로 알려져 있으며, 우리나라에는 제주도 남쪽계곡에만 분포하는 희귀식물이다. 무주나무는 현재 환경부 지정 보호야생식물로 보호되고 있으나 개체특성 및 자생지에 대한 정확한 조사가 이루어진 바 없다. 본 연구는 무주나무의 자생지 현황과 생육특성을 파악하고자 실시하였다. 무주나무의 자생지는 제주도 남제주군 남원읍 하례리 해발 250m의 계곡 동사면과 서귀포시 돈네코 계곡의 해발 350 m 계곡의 서사면 등 2개소로 확인되었다. 자생지별 개체수는 남원읍 하례리 4개체, 서귀포시 돈네코계곡 5개체 등 총 9개체에 불과하였다. 자생지는 계곡의 상록수림 하부에 바위 위 부엽토나, 습한 계곡 사면이었으며, 교목층에는 구실잣밤나무, 비쭈기나무, 황칠나무, 동백나무 등이 우점하고, 관목층에는 사스레피나무, 백량금, 산호수 등이 우점하는 상록활엽수림이었다. 분포 개체의 수고는 최소 0.4 m, 최대 1.55 m로 평균 1.5 m 였다. 생장특성을 조사한 결과 줄기는 어릴 때는 사각형이지만 점차 원형으로 되며, 일정한 마디가 있고 털이 없으며, 잎은 대생하고, 혁질이며, 중륵과 측맥이 뚜렷한 특성을 갖고 있었다. 열매는 장과형으로 성숙 시에는 남색이며 털이 없으며, 직경 약 6-7 mm, 4-5개의 종자가 들어 있었다. 종자는 반달형이며, 3개의 홈이 지는 특성을 갖고 있었다. 현재의 자생지는 자연적인 요인으로서 토양유실이 심하게 일어나고 있는 지역이었으며, 교목 또는 다른 관목에 의한 피압으로 무주나무의 생장에 부적절한 환경으로 판단되었다. 따라서 자생지의 적절한 식생관리와 지속적인 자생지 조사 및 자생지외 보존에 관한 연구가 이루어져야할 것으로 생각된다.$I_{NO}$ 가 죽절초를 제외한 3종에서 여름철 낮시간에 증가하였다. 겨울철의 O-J-I-P곡선은 모든 종에서 낮시간에 다소 낮아지지만 큰 변화는 없었다. 그리고, 문주란, 박달목서, 파초일엽에서 $\psi$o/(1-$\psi$o)가 낮시간에 다소 증가하였다. 이로부터 P $I_{NO}$ , SF $I_{NO}$ , $\psi$o/(1-$\psi$o)등의 변수는 식물의 활력도를 검정하는 지표로 활용될 가능성이 높다고 할 수 있다.irc}C$) 까지 동시에 냉각된 사실을 지시한다. 각섬석 편암내의 각섬석들은 복잡한 40Ar/39Ar 연대를 보여주며 일부가 평형연대를 보여주지만 특별한 의미 부여가 힘들다.해예방행동을 촉구하는 등의 효과도 높은 것으로 예방의학적인 유용성이 크다고 볼 수 있다. 미침을 알 수 있었다. 대두 단백질로 코팅된 golden delicious는 상온에서60일 동안 보관하였을 경우, 사과표피의 색도 변화를 현저히 지연시킴을 확인하였다. 또한 control과 비교하여 성공적으로 사과에 코팅하였으며, 상온에서 보관하여을 때 사과의 품질을 30일 이상 연장하는 효과를 관찰하였다. 이들 결과로부터 대두단백질 필름이 과일 등의 포장제로서 이용할 가능성을 확인하였다.로 [-wh] 겹의문사는 복수 의미를 지닐 수 없 다. 그러면 단수 의미는 어떻게 생성되는가\ulcorner 본 논문에서는 표면적 형태에도 불구하고 [-wh]의미의 겹의문사는 병렬적 관계의 합성어가 아니라 내부구조를 지니지 않은 단순한 단어(minimal $X^{0}$ elements)로 가정한다. 즉, [+wh] 의미의 겹의문사는 동일한 구성

• Korean Journal of Environment and Ecology
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• v.18 no.1
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• pp.53-60
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• 2004

This study was carried out to investigate the effect of green area in apartment complexes to variation of temperature. The inside temperature of each site was estimated by analyzing Landsat ETM＋ image data. The factors on variation of temperature were landcover type, building density, and Normalised Difference Vegetation Index(NDVI). The results of correlation between inside temperature of apartment complex and land cover type showed that the green area ratio had negative(－) correlation and impermeable pavement ratio had positive(＋) correlation. Building-to-land ratio was not significant with inside temperature. A coefficient of correlation between the temperature value and the value of permeable pavement ratio added up green area ratio was higher than a coefficient of correlation between the temperature value and the value of permeable pavement ratio added up impermeable pavement ratio. Thus we may define that permeable pavement area decrease urban temperature with green area in apartment complex. Floor area ratio had no significant correlation with inside temperature. Inside temperature was decreased as the NDVI was increased. To establish the temperature distribution model in a development apartment complex, As the result of regression analysis between inside temperature as dependent variable and permeable pave ratio+green area ratio, green area ratio, building-to-land ratio and NDIT as independent variables, only permeable pavement ratio added up green area ratio of the independent variables was accepted fur regression equation in both two seasons and adjusted coefficient of determination was 41.4 on September, 2000 and 40.4 on June,2001.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.253-265
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• 2020

As the risk of landslide is recently increasing due to the typhoons and localized heavy rains, effective techniques for the landslide damage detection are required to support the establishment of the recovery planning. This study describes the analysis of landslide-damaged areas using ISODATA(Iterative Self-Organizing Data Analysis Technique Algorithm) with Sentinel-2 image, regarding the case of Gokseong in August 7, 2020. A total of 4.75 ha of landslide-damaged areas was detected from the Sentinel-2 image using spectral characteristics of red, NIR(Near Infrared), and SWIR(Shortwave Infrared) bands. We made sure that the satellite remote sensing is an effective method to detect the landslide-damaged areas and support the establishment of the recovery planning, followed by the field surveys that require a lot of manpower and time. Also, this study can be used as a reference for the landslide management for the CAS500-1/2(Compact Advanced Satellite) scheduled to launch in 2021 and the Korean Medium Satellite for Agriculture and Forestry scheduled to launch in 2024.

• Journal of Korea Water Resources Association
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• v.42 no.1
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• pp.33-50
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• 2009

The impact on hydrologic components considering future potential climate, land use change and vegetation cover information was assessed using SLURP (Semi-distributed Land-Use Runoff Process) continuous hydrologic model. The model was calibrated (1999 - 2000) and validated (2001 - 2002) for the upstream watershed ($260.4\;km^2$) of Gyeongancheon water level gauging station with the coefficient of determination and Nash-Sutcliffe efficiency ranging from 0.77 to 0.60 and 0.79 to 0.60, respectively. Two GCMs (MIROC3.2hires, ECHAM5-OM) future weather data of high (A2), middle (A1B) and low (B1) emission scenarios of the IPCC (Intergovernmental Panel on Climate Change) were adopted and the data was corrected by 20C3M (20th Century Climate Coupled Model) and downscaled by Change Factor (CF) method using 30 years (1977 - 2006, baseline period) weather data. Three periods data of 2010 - 2039 (2020s), 2040 - 2069 (2050s), 2070 - 2099 (2080s) were prepared. To reduce the uncertainty of land surface conditions, future land use and vegetation canopy prediction were tried by CA-Markov technique and NOAA NDVI-Temperature relationship respectively. MIROC3.2 hires and ECHAM5-OM showed increase tendency in annual streamflow up to 21.4 % for 2080 A1B and 8.9 % for 2050 A1B scenario respectively. The portion of future predicted ET about precipitation increased up to 3 % in MIROC3.2 hires and 16 % in ECHAM5-OM respectively. The future soil moisture content slightly increased compared to 2002 soil moisture.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1109-1123
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• 2020

In South Korea with forest as a major land cover class (over 60% of the country), many wildfires occur every year. Wildfires weaken the shear strength of the soil, forming a layer of soil that is vulnerable to landslides. It is important to identify the severity of a wildfire as well as the burned area to sustainably manage the forest. Although satellite remote sensing has been widely used to map wildfire severity, it is often difficult to determine the severity using only the temporal change of satellite-derived indices such as Normalized Difference Vegetation Index (NDVI) and Normalized Burn Ratio (NBR). In this study, we proposed an approach for determining wildfire severity based on machine learning through the synergistic use of Sentinel-1A Synthetic Aperture Radar-C data and Sentinel-2A Multi Spectral Instrument data. Three wildfire cases-Samcheok in May 2017, Gangreung·Donghae in April 2019, and Gosung·Sokcho in April 2019-were used for developing wildfire severity mapping models with three machine learning algorithms (i.e., Random Forest, Logistic Regression, and Support Vector Machine). The results showed that the random forest model yielded the best performance, resulting in an overall accuracy of 82.3%. The cross-site validation to examine the spatiotemporal transferability of the machine learning models showed that the models were highly sensitive to temporal differences between the training and validation sites, especially in the early growing season. This implies that a more robust model with high spatiotemporal transferability can be developed when more wildfire cases with different seasons and areas are added in the future.

• Journal of the Korean Institute of Landscape Architecture
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• v.48 no.4
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• pp.19-28
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• 2020

The Urban Heat Island (UHI) Effect has intensified due to urbanization and heat management at the urban level is treated as an important issue. Green space improvement projects and environmental policies are being implemented as a way to alleviate Urban Heat Islands. Several studies have been conducted to analyze the correlation between urban green areas and heat with linear regression models. However, linear regression models have limitations explaining the correlation between heat and the multitude of variables as heat is a result of a combination of non-linear factors. This study evaluated the Heat Island alleviating effects in Seoul during the summer by using a deep neural network model methodology, which has strengths in areas where it is difficult to analyze data with existing statistical analysis methods due to variable factors and a large amount of data. Wide-area data was acquired using Landsat 8. Seoul was divided into a grid (30m × 30m) and the heat island reduction variables were enter in each grid space to create a data structure that is needed for the construction of a deep neural network using ArcGIS 10.7 and Python3.7 with Keras. This deep neural network was used to analyze the correlation between land surface temperature and the variables. We confirmed that the deep neural network model has high explanatory accuracy. It was found that the cooling effect by NDVI was the greatest, and cooling effects due to the park size and green space proximity were also shown. Previous studies showed that the cooling effects related to park size was 2℃-3℃, and the proximity effect was found to lower the temperature 0.3℃-2.3℃. There is a possibility of overestimation of the results of previous studies. The results of this study can provide objective information for the justification and more effective formation of new urban green areas to alleviate the Urban Heat Island phenomenon in the future.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.36 no.3
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• pp.115-127
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• 2018

This study was attempted to find out the value of cultural assets through the clear diagnosis and prescription of the dead and weakness factors of the Population of Retusa Fringe Trees in Pyeongji-ri, Jinan(Natural Monument No. 214), The results are as follows. First, Since the designation of 13 natural monuments in 1968, since 1973, many years have passed since then. In particular, despite the removal of some of the buried soil during the maintenance process, such as retreating from the fence of the primary school after 2010, Second, The first and third surviving tree of the designated trees also have many branches that are dead, the leaves are dull, and the amount of leaves is small. vitality of tree is 'extremely bad', and the first branch has already been faded by a large number of branches, and the amount of leaves is considerably low this year, so that only two flowers are bloomed. The second is also in a 'bad'state, with small leaves, low leaf density, and deformed water. The largest number 1 in the world is added to the concern that the s coverd oil is assumed to be paddy soils. Third, It is found that the composition ratio of silt is high because it is known as '[silty loam(SiL)]'. In addition, the pH of the northern soil at pH 1 was 6.6, which was significantly different from that of the other soil. In addition, the organic matter content was higher than the appropriate range, which is considered to reflect the result of continuous application for protection management. Fourth, It is considered that the root cause of failure and growth of Jinan pyeongji-ri Population of Retusa Fringe Trees group is chronic syndrome of serious menstrual deterioration due to covered soil. This can also be attributed to the newly planted succession and to some of the deaths. Fifthly, It is urgent to gradually remove the subsoil part, which is estimated to be the cause of the initial damage. Above all, it is almost impossible to remove the coverd soil after grasping the details of the soil, such as clayey soil, which is buried in the rootstock. After removal of the coverd soil, a pestle is installed to improve the respiration of the roots and the ground with Masato. And the dead 4th dead wood and the 5th and 6th dead wood are the best, and the lower layer vegetation is mown. The viable neck should be removed from the upper surface, and the bark defect should undergo surgery and induce the development of blindness by vestibule below the growth point. Sixth, The underground roots should be identified to prepare a method to improve the decompression of the root and the respiration of the soil. It is induced by the shortening of rotten roots by tracing the first half of the rootstock to induce the generation of new roots. Seventh, We try mulching to suppress weed occurrence, trampling pressure, and soil moisturizing effect. In addition, consideration should be given to the fertilization of the foliar fertilizer, the injection of the nutrients, and the soil management of the inorganic fertilizer for the continuous nutrition supply. Future monitoring and forecasting plans should be developed to check for changes continuously.