• Korean Journal of Ecology and Environment
• /
• v.47 no.4
• /
• pp.319-327
• /
• 2014

Understanding and quantifying of carbon storage in ecosystem is very important factor for predicting change of global carbon cycle under the global climate change. We estimated total ecosystem carbon in Gyeryongsan National Park with naturally well preserved ecosystem in Korea. Vegetation of Gyeryongsan National Park was classified with mainly four communities with Quercus mongolica (1,743.5 ha, 38.0%), Quercus variabilis (1,174.0 ha, 25.6%), Quercus serrata (971.9 ha, 21.2%), Pinus densiflora (695.2 ha, 15.2%). Biomass and soil carbons were calculated from biomass allometric equations based on the DBH and carbon contents of soil and litter collected in quadrat in each community. The tree biomass carbon was in Quercus variabilis ($130.1tCha^{-1}$), Pinus densiflora ($111.1tCha^{-1}$), Quercus mongolica ($76.2tCha^{-1}$), Quercus serrata ($39.0tCha^{-1}$). Soil carbon storage was in Quercus mongolica ($159.7tCha^{-1}$), Quercus serrata ($121.0tCha^{-1}$), Pinus densiflora ($110.5tCha^{-1}$), Quercus variabilis ($90.8tCha^{-1}$). Ecosystem carbon storage was Pinus densiflora ($239.9tCha^{-1}$), Quercus mongolica ($235.9tCha^{-1}$), Quercus variabilis ($226.0tCha^{-1}$), Quercus serrata ($165.9tCha^{-1}$), total amount was $867.7tCha^{-1}$. The area of each vegetation carbon storage was Quercus mongolica ($411,200tCha^{-1}$), Quercus variabilis ($265,300tCha^{-1}$), Pinus densiflora ($166,800tCha^{-1}$), Quercus serrata ($161,200tCha^{-1}$) and the total ecosystem carbon amount estimated $1,045,400tCha^{-1}$ at Gyeryongsan National Park. Theses results indicate that different in naturally well preserved ecosystem.

• Korean Journal of Remote Sensing
• /
• v.38 no.6_1
• /
• pp.1301-1314
• /
• 2022

Normalized Difference Vegetation Index (NDVI) is utilized as an indicator to represent the vegetation condition on the land surface in various applications such as land cover, crop yield, agricultural drought, soil moisture, and forest disaster. However, satellite optical sensors for visible and infrared rays cannot see through the clouds, so the NDVI of the cloud pixel is not a valid value for the land surface. This study proposed a real-time correction of the underestimation noise for GEO-KOMPSAT-2A (GK2A) daily NDVI and made sure its feasibility through the quantitative comparisons with Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI and the qualitative interpretation of time-series changes. The underestimation noise was effectively corrected by the procedures such as the time-series correction considering vegetation phenology, the outlier removal using long-term climatology, and the gap filling using rigorous statistical methods. The correlation with MODIS NDVI was higher, and the difference was lower, showing a 32.7% improvement compared to the original NDVI product. The proposed method has an extensibility for use in other satellite products with some modification.

• Korean Journal of Remote Sensing
• /
• v.20 no.2
• /
• pp.77-89
• /
• 2004

The spatial and temporal variations of aerosol optical depth (AOD) over Northeast Asia regions have special importance in the aerosol research for estimation of aerosol radiative forcing parameters and climate change. Aerosol optical and physical properties (AOD and ${\AA}$ngstrom parameter) have been investigated by using Moderate Resolution Imaging Spectroradiometer (MODIS) and Total Ozone Mapping Spectrometer (TOMS) Aerosol Index (AI) to estimate aerosol characteristics over the study region during 2001. Additionally, aerosol characteristics over the Korean peninsular during Aerosol Characteristic Experiment in Asia (ACE-Asia) Intensive Observation Period (IOP) have been investigated by using satellite observations. The results showed that the daily-observed aerosol data indicate seasonal variations with relatively higher aerosol loading in the spring and very low during the winter. The typical Asian dust case showed higher AOD (>0.7) with lower Angstrom exponent (<0.5) and higher AI (>0.5) that is mainly due to the composition of coarse particles in the springtime. Mean AOD for 2001 at 4 different places showed 0.65$\pm$0.37 at Beijing, 0.31$\pm$0.19 at Gosan, 0.54$\pm$0.26 at Seoul, and 0.38$\pm$0.19 at Kwangju, respectively. An interesting result was found in the present study that polluted aerosol events with small size dominated-aerosol loading around the Korean peninsular are sometimes observed. The origin of these polluted aerosols was thought to East China. Aerosol distribution from satellite images and trajectory results shows the proof of aerosol transport. Therefore, aerosol monitoring using satellite data is very useful.

• Korean Journal of Remote Sensing
• /
• v.34 no.3
• /
• pp.553-564
• /
• 2018

Water use efficiency (WUE) is the amount of carbon uptake per unit of water use, which is a key measure of the functions of terrestrial ecosystems, as it is related to both the hydrologic and carbon cycles. Furthermore, it can vary with many factors, such as climate conditions and land cover characteristics, in different regions. In this study, we aim to understand the spatial and temporal variations in WUE on the Korean Peninsula as well as the associated response to drought. The Moderate Resolution Imaging Spectroradiometer (MODIS)-derived gross primary productivity (GPP) and evapotranspiration (ET) datasets and climate data were used to derive a drought index. Based on the monthly WUE, we found that WUE decreased during the monsoon summer in all regions and for all vegetation types. Furthermore, the annual WUE was negatively correlated with the drought index, with increasing correlation coefficients from the northern region to the southern region of the Korean Peninsula.

• Korean Journal of Environment and Ecology
• /
• v.34 no.4
• /
• pp.294-303
• /
• 2020

This study aimed to examine was conducted to the ability of microclimate control in old pine forests by surveying pine forest in Buddhist temples, where the pine forest are stably growing through active protection in the Gyeongnam region, and comparing variation characteristics of microclimate characteristics (temperature and humidity) and distribution of vegetation type. The study sites were pine forests protected well by Buddhist temples (Haein-sa, Beomeo-sa, Tongdo-sa, and Bulguk-sa) in the southeast region of Korea and thus known for stably growing young pine trees. According to the vegetation distribution status analysis, these pine forests did not have a high ratio of pine trees. Except for Tongdo-sa, the ratio of deciduous forest and mixed (deciduous and pine trees) forest had a much larger presence than that of pine forest. Measured data of microclimate showed that the Tongdo-sa area had significantly different characteristics compared to the other three areas. Tongdo-sa area showed a significantly higher diurnal range of temperatures and humidity than the other three areas, in both spring and summer. It is due to the difference in vegetation management. The forests around Tongdo-sa are mostly pine forests, except for the developed areas, while those in the other three areas have a dominant ratio of deciduous brad-leaved forests. Intensive control of pine forest is not effective in mitigating microclimate, i.e., temperature and air humidity. Stress caused by rising temperatures and decreasing air humidity is blamed for the decline of pine forests. Thus, the current active management of pine forests, such as the Tongdo-sa case, has been found to have a greater negative impact on the temperature and humidity stress. Therefore, we believe that a new change in forest management is necessary to increase the effect of mitigating the microclimate of pine forests.

• Korean Journal of Environmental Agriculture
• /
• v.37 no.4
• /
• pp.268-276
• /
• 2018

BACKGROUND: In the month of January 2018, fine dust alerts and warnings were issued 36 times for $PM_{10}$ and 81 times for PM2.5. Air quality is becoming a serious issue nation-wide. Although interest in air-purifying plants is growing due to the controversy over the risk of chemical substances of regular air-purifying solutions, industrial spread of the plants has been limited due to their efficiency in air-conditioning perspective. METHODS AND RESULTS: This study aims to propose a vegetation-based bio-filter system that can assure total indoor air volume for the efficient application of air-purifying plants. In order to evaluate the quantitative performance of the system, time-series analysis was conducted on air-conditioning performance, indoor air quality, and comfort index improvement effects in a lecture room-style laboratory with 16 persons present in the room. The system provided 4.24 ACH ventilation rate and reduced indoor temperature by $1.6^{\circ}C$ and black bulb temperature by $1.0^{\circ}C$. Relative humidity increased by 24.4% and deteriorated comfort index. However, this seemed to be offset by turbulent flow created from the operation of air blowers. While $PM_{10}$ was reduced by 39.5% to $22.11{\mu}g/m^3$, $CO_2$ increased up to 1,329ppm. It is interpreted that released $CO_2$ could not be processed because light compensation point was not reached. As for the indoor comfort index, PMV was reduced by 83.6 % and PPD was reduced by 47.0% on average, indicating that indoor space in a comfort range could be created by operating vegetation-based bio-filters. CONCLUSION: The study confirmed that the vegetation-based bio-filter system is effective in lowering indoor temperature and $PM_{10}$ and has positive effects on creating comfortable indoor space in terms of PMV and PPD.

• Korean Journal of Remote Sensing
• /
• v.39 no.6_1
• /
• pp.1413-1425
• /
• 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 Geographical Society
• /
• v.49 no.2
• /
• pp.221-244
• /
• 2014

We suggested several implications by examining geochemical properties of sediments in Simjeok, Jangdo, and Hwaeomneup mountain wetlands which are natural preservation areas. Geochemical properties of wetland sediments show that all wetlands were included in the type of fens, but their distribution patterns were different from one another. We classified three sub-groups of sediments using the two step cluster analysis on the ratio of exchangeable cations. Wetland sediments can be grouped into Ca-dominated, Mg-dominated, and K-dominated types. Simjeok wetland have Ca-dominated sediments, while the sediments of Jangdo wetland indicate the Mg-dominated and Ca-dominated characteristics. Hwaeomneup wetland is composed of K-dominated sediment mainly. Different properties in the ratio are affected by various environmental factors such as geological, pedological, and vegetational settings. Because these geochemical properties will be affected by climate change and human impacts, these will be environmental indicator in mountain wetlands and be used in wetland management. This scheme can be used for classification of mountain wetlands. Therefore, we should work on geochemical properties of wetland sediments and classification schemes based on geochemical properties not only to widen understanding in geomorphic system or ecosystem of mountain wetlands but to conserve mountain wetlands properly.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2020.06a
• /
• pp.206-206
• /
• 2020

토지이용의 고도화에 따라 비점오염원 부하는 증가하는 추세이며 기후변화에 따른 강우강도 증가 등으로 지표면에 축적된 고농도의 비점오염물질이 하천으로 유출, 수질오염을 가중시키고 있어 비점오염원 관리가 필요하다. 환경부에서 효율적인 비점오염원 관리를 위하여 2004년부터 현재까지 3단계에 걸쳐 비점오염원 관리 종합대책을 수행하고 있으며, 2008년부터 비점국고보조사업을 추진하여 비점오염저감시설 설치를 통한 수질개선 및 수생태계 건강성 확보에 기여하고자 하였다. 이에 본 연구는 비점국고보고사업을 통해 구축된 비점오염저감시설을 대상으로 시설 설치 및 운영 현황과 강우시 비점오염저감 효과 분석을 통한 시설의 평가를 수행하고자 한다. 연구대상시설은 시범시설 및 국고보조시설 총 70개소로 2005~2017년에 준공되었으며, 2016년부터 현재까지 총 4년동안 진행된 모니터링을 바탕으로 연구를 수행하였다. 시설의 용량은 34~97,000㎥의 범위로 SA/CA 1.2~6.6%의 범위이다. 강우시 모니터링은 선행무강우일수 3일이상을 고려하여 수행하였으며 도시지역의 경우 5mm 이상, 농촌지역 10mm 이상시 모니터링을 진행하였다. 시설의 유입과 유출부에서 수질 및 유량 모니터링을 진행하였으며, 수질오염공정시험법에 준하여 BOD, COD, SS, T-N 및 T-P 항목에 대해 분석을 수행하였다. 모니터링 결과, 국내 비점오염저감시설의 평균 부하량은 SS 250.4 kg/day, BOD 89.2 kg/day, COD 136.2 kg/day, TN 51.4 kg/day, TP 7.1 kg/day 로 분석되었으며, 유출부 의 경우 SS 83.8 kg/day, BOD 37.2 kg/day, COD 51.0 kg/day, TN 15.4 kg/day, TP 2.0 kg/day로 나타났다. 또한, 은 오염물질 유입 및 유출 부하량의 상관관계 분석결과 SS, BOD, COD의 유입 및 유출 부하량의 상관성은 높게 나타났으며 특히 유기물질(BOD, COD)의 상관성은 0.8이상으로 분석되었다(p<0.005). 이는 비점오염저감시설에 적용된 식생, 미생물, 여재 등을 통하여 물리학적 및 생태학적 처리를 통해 저감되기 때문으로 판단된다. 하지만, TN은 인위적 요인과 자연적 요인이 복합적으로 작용으로 배출 특성으로 상관성은 매우 낮은 것으로 분석되었다.

• Korean Journal of Remote Sensing
• /
• v.36 no.6_1
• /
• pp.1421-1434
• /
• 2020

The frequency and intensity of heatwaves have been increasing due to climate change. Since urban areas are more severely damaged by heatwaves as they act in combination with the urban heat island phenomenon, every possible preparation for such heat threats is required. Many overseas local governments build heat maps using a variety of spatial information to prepare for and counteract heatwaves, and prepare heatwave measures suitable for each region with different spatial characteristics within a relevant city. Building a heat map is a first and important step to prepare for heatwaves. The cases of heat map construction and thermal environment analysis involve various area distributions from urban units with a large area to local units with a small area. The method of constructing a heat map varies from a method utilizing remote sensing to a method using simulation, but there is no standard for using differentiated spatial information according to spatial scale, so each researcher constructs a heat map and analyzes the thermal environment based on different methods. For the above reason, spatial information standards required for building a heat map according to the analysis scale should be established. To this end, this study examined spatial information, analysis methodology, and final findings related to Korean and oversea analysis studies of heatwaves and urban thermal environments to suggest ways to improve the utilization efficiency of spatial information used to build urban heat maps. As a result of the analysis, it was found that spatial, temporal, and spectral resolutions, as basic resolutions, are necessary to construct a heat map using remote sensing in the use of spatial information. In the use of simulations, it was found that the type of weather data and spatial resolution, which are input condition information for simulation implementation, differ according to the size of analysis target areas. Therefore, when constructing a heat map using remote sensing, spatial, spectral, and temporal resolution should be considered; and in the case of using simulations, the spatial resolution, which is an input condition for simulation implementation, and the conditions of weather information to be inputted, should be considered in advance. As a result of understanding the types of monitoring elements for heatwave analysis, 19 types of elements were identified such as land cover, urban spatial characteristics, buildings, topography, vegetation, and shadows, and it was found that there are differences in the types of the elements by spatial scale. This study is expected to help give direction to relevant studies in terms of the use of spatial information suitable for the size of target areas, and setting monitoring elements, when analyzing heatwaves.