• Journal of Environmental Science International
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• v.29 no.5
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• pp.519-529
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• 2020

The purpose of this study was to provide basic health care data for the climate aspects of park re-cultivation by evaluating air ions according to the type of vegetation in the valley and upper slopes of the mountain park. Simple negative or positive air ions were expected to show the same tendencies, so they were analyzed in terms of correcting the air ion index. By analyzing the air ions according to the topography, it was found that valley > slope in terms of the air ion index. When analyzing air ions according to tree species, we found that evergreen conifers in the valley > the deciduous broad-leaved trees in the valley > the evergreen conifers in the slope = the deciduous broad-leaved trees in the slope. For DBH(Diameter at breast height), the valley large pole > slope large pole > slope medium hard wood, while crown density was analyzed as valley dense > slope dense> valley proper > slope proper. Layered structure analysis showed that the multi-layer structure of the valley > multi-layer structure of the slope = the single-layer structure of the valley > the single-layer structure of the slope. The correlation coefficient was determined according to vegetation type and air ion index in the order of DBH > crown density > layer structure > geomorphic structure. In this study, limits exist except for ridge line, valley, and slopes in urban mountain parks. Therefore, analysis should be made considering both topographical structure and various vegetation types in future studies of air ions.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.9-18
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• 2024

Small streams, despite their rich ecosystems, face challenges in vegetation assessment due to the limitations of traditional, time-consuming methods. This study presents a groundbreaking approach, combining unmanned aerial vehicles(UAVs), convolutional neural networks(CNNs), and the vegetation differential vegetation index (VDVI), to revolutionize both assessment and management of stream vegetation. Focusing on Idong Stream in South Korea (2.7 km long, 2.34 km² basin area)with eight diverse revetment methods, we leveraged high-resolution RGB images captured by UAVs across five dates (July-December). These images trained a ResNeXt101 CNN model, achieving an impressive 89% accuracy in classifying vegetation cover(soil,water, and vegetation). This enabled detailed spatial and temporal analysis of vegetation distribution. Further, VDVI calculations on classified vegetation areas allowed assessment of vegetation vitality. Our key findings showcase the power of this approach:(a) TheCNN model generated highly accurate cover maps, facilitating precise monitoring of vegetation changes overtime and space. (b) August displayed the highest average VDVI(0.24), indicating peak vegetation growth crucial for stabilizing streambanks and resisting flow. (c) Different revetment methods impacted vegetation vitality. Fieldstone sections exhibited initial high vitality followed by decline due to leaf browning. Block-type sections and the control group showed a gradual decline after peak growth. Interestingly, the "H environment block" exhibited minimal change, suggesting potential benefits for specific ecological functions.(d) Despite initial differences, all sections converged in vegetation distribution trends after 15 years due to the influence of surrounding vegetation. This study demonstrates the immense potential of UAV-based remote sensing and CNNs for revolutionizing small-stream vegetation assessment and management. By providing high-resolution, temporally detailed data, this approach offers distinct advantages over traditional methods, ultimately benefiting both the environment and surrounding communities through informed decision-making for improved stream health and ecological conservation.

• Journal of Environmental Science International
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• v.25 no.12
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• pp.1653-1660
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• 2016

Drought is a reoccurring worldwide natural hazard that affects not only food production but also economics, health, and infrastructure. Drought monitoring is usually performed with precipitation-based indices without consideration of the actual state and amount of the land surface properties. A drought index based on the actual evapotranspiration can overcome these shortcomings. The severity of a drought can be quantified by making a spatial map. The procedure for estimating actual evapotranspiration is costly and complicated, and requires land surface information. The possibility of utilizing drone-driven remotely sensed data for actual evapotranspiration estimation was analyzed in this study. A drone collected data was used to calculate the normalized difference vegetation index (NDVI) and soil-adjusted vegetation index (SAVI). The spatial resolution was 10 m with a grid of $404{\times}395$. The collected data were applied and parameterized to an actual evapotranspiration estimation. The result shows that drone-based data is useful for estimating actual evapotranspiration and the corresponding drought indices.

• Journal of Aerospace System Engineering
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• v.18 no.4
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• pp.27-33
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• 2024

This study deals with the demonstration of precision agriculture technology that can predict the health status of crops by analyzing the vegetation index (NDVI) using a drone equipped with a multi-spectral camera and an EO/IR camera. The multi-spectral camera measures crop reflectance to determine the vegetation index, while the EO/IR camera detects temperature changes in crops to evaluate water stress and health status. Data from this study can improve agricultural productivity and optimize the use of chemical fertilizers and pesticides. Moreover, integrating object recognition technology in the future could turn precision agriculture into a vital alternative for enhancing the sustainability of agriculture.

• 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.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.365-365
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• 2019

가뭄은 전 세계적으로 농업을 비롯한 사회, 경제적으로 큰 피해를 주는 자연 재해이며, 향후 피해 저감을 위해 가뭄의 경향을 파악하고 지역별 가뭄 특성을 파악할 필요가 있다. 위성영상을 활용한 가뭄 판단은 광역적 범위를 대상으로 다양한 밴드를 활용한 데이터를 주기적이고 일정한 수준으로 취득 가능하다는 장점이 있다. 농업 가뭄 분야의 위성영상 활용은 미계측 지역에 대한 정확한 데이터 취득이 어려운 지점데이터의 단점을 보완할 수 있다. 위성영상을 활용한 가뭄 지수로는 Leaf Area Index (LAI), Vegetation Health Index (VHI), Enhanced Vegetation Index (EVI) 등 다양한 지수들이 있으며, 본 연구에서는 단기 가뭄 판단에 활용되고 있는 Evaporative Stress Index (ESI)를 활용하였다. 국내 행정구역 기반의 가뭄 판단을 위해 Moderate Resolution Imaging Spectramadiometer (MODIS)위성의 MOD16A2 영상을 사용하였다. MOD16A2는 land surface temperature (LST)과 LAI의 계산을 통한 실제 증발산량과 FAO-56 Penman-Monteith 공식을 사용한 잠재증발산량을 포함한 다양한 데이터를 8일 주기의 500m 해상도로 제공하고 있다. 2001년부터 2018년까지 500m 해상도의 ESI를 산정하였으며, 국내의 과거 가뭄 경향 분석과 지역별 특성 파악을 위한 표준화를 수행하였다. 그 결과 과거 극심한 가뭄이 있었던 해 (2000-2001년, 2015-2017년 등)에 대한 농업 가뭄 경향 분석이 가능하였으며, 지역별 특성을 파악한 결과 상습가뭄 지역에서 가뭄 경향을 확인하였다. 농업 가뭄 분야에서 ESI의 활용은 가뭄 조기 경보 시스템 개발 및 위성영상 기반 가뭄 모니터링 기술 개발 등에 활용 가능할 것으로 기대된다.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.45-56
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• 2024

Faced with aging populations, declining resources, and limited agricultural productivity, rural areas in South Korea require innovative solutions. This study investigated the potential of drone-based vegetation indices (VIs) to analyze soybean growth patterns in open-field smart agriculture in Goesan-gun, Chungbuk Province, South Korea. We monitored multi-seasonal normalized difference vegetation index (NDVI) and the normalized difference red edge (NDRE) data for three soybean lots with different irrigation methods (subsurface drainage, conventional, subsurface drip irrigation) using drone remote sensing. Combining NDVI (photosynthetically active biomass, PAB) and NDRE (chlorophyll) offered a comprehensive analysis of soybean growth, capturing both overall health and stress responses. Our analysis revealed distinct growth patterns for each lot. LotA(subsurface drainage) displayed early vigor and efficient resource utilization (peaking at NDVI 0.971 and NDRE 0.686), likely due to the drainage system. Lot B (conventional cultivation) showed slower growth and potential limitations (peaking at NDVI 0.963 and NDRE 0.681), suggesting resource constraints or stress. Lot C (subsurface drip irrigation) exhibited rapid initial growth but faced later resource limitations(peaking at NDVI 0.970 and NDRE 0.695). By monitoring NDVI and NDRE variations, farmers can gain valuable insights to optimize resource allocation (reducing costs and environmental impact), improve crop yield and quality (maximizing yield potential), and address rural challenges in South Korea. This study demonstrates the promise of drone-based VIs for revitalizing open-field agriculture, boosting farm income, and attracting young talent, ultimately contributing to a more sustainable and prosperous future for rural communities. Further research integrating additional data and investigating physiological mechanisms can lead to even more effective management strategies and a deeper understanding of VI variations for optimized crop performance.

• Journal of Environmental Impact Assessment
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• v.29 no.6
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• pp.430-440
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• 2020

The application contents, process, and its limitations are discussed for the setting of Korean legal guides & criteria for water cycle and ecological condition in development project of land use by thorough comparison and examination of prerequisites and credits of water cycle and soil+vegetation by USA's SITES (Sustainable Sites Initiative). In the case of SITES, due to the implementation procedure operated as a non-governmental independent assessment system by Green Business Certification, Inc, the natural condition of water cycle and soil-vegetation items-the key element of ecosystem services can be quantitatively assessed, well along with its legal and institutional guidelines and regulations. On the other hand, in the case of Korea, as a part of the national certification procedure for green building, the ecological area ratio system still have very limited role as an only amenity resource in the creation of artificial green spaces and insufficiency of management system for rain water. In conclusion, it was understood as an urgent situation in necessary for prompt establishment of site's sustainability certification system at the national level, based on management of water circulation and natural soil & vegetation in developed area with consideration of various land uses and types of development projects.

• Korean Journal of Environment and Ecology
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• v.36 no.5
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• pp.445-459
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• 2022

In this study, we investigated current vegetation and assessed the health of vegetation through the KERVI (Korea Estuary Riparian Vegetation Index) to monitor vegetation changes near estuaries due to the opening of the Nakdong River estuary. As the first investigation of the long-term monitoring, six areas near the Nakdong River estuary were surveyed twice in July and October 2021, and vegetation monitoring and a survey of species composition and distribution density of aquatic, riparian, and land plants were carried out. The survey identified 262 taxa, 82 families, 192 genera, 196 species, 3 subspecies, 26 varieties, and 1 form of vascular plants in the surveyed area. The results of the vegetation health assessment through KREVI showed that sites 1 and 6 were rated "Very good" in both surveys, sites 2 and 4 were rated "Very good" in the first survey and then "Good"in the second survey, and site 3 and 5 were rated one grade higher in the second survey than the first survey. The assessment showed that the health grades of most species in the survey area were generally high. Most of the potential natural vegetation after the opening of estuary gates to create a brackish water area is expected to consist of reed (Phragmites communisTrin.) communities. The area of the willow (Salix koreensisAndersson) community adjacent to the water area may be somewhat narrower, but the community will be maintained. In the case of freshwater areas in inland areas with very low salinity, reeds (Phragmites communisTrin.) are expected to occupy most of them, and some communities such as amur silver-grass (Miscanthus sacchariflorusBenth.) and cattails (Typha orientalisC. Presl) are expected to be distributed. We suggest establishing measures such as estuary gate operation to create healthy brackish water regions through long-term monitoring.

• Environmental Analysis Health and Toxicology
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• v.30
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• pp.10.1-10.14
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• 2015

Recent cohort studies have relied on exposure prediction models to estimate individual-level air pollution concentrations because individual air pollution measurements are not available for cohort locations. For such prediction models, geographic variables related to pollution sources are important inputs. We demonstrated the computation process of geographic variables mostly recorded in 2010 at regulatory air pollution monitoring sites in South Korea. On the basis of previous studies, we finalized a list of 313 geographic variables related to air pollution sources in eight categories including traffic, demographic characteristics, land use, transportation facilities, physical geography, emissions, vegetation, and altitude. We then obtained data from different sources such as the Statistics Geographic Information Service and Korean Transport Database. After integrating all available data to a single database by matching coordinate systems and converting non-spatial data to spatial data, we computed geographic variables at 294 regulatory monitoring sites in South Korea. The data integration and variable computation were performed by using ArcGIS version 10.2 (ESRI Inc., Redlands, CA, USA). For traffic, we computed the distances to the nearest roads and the sums of road lengths within different sizes of circular buffers. In addition, we calculated the numbers of residents, households, housing buildings, companies, and employees within the buffers. The percentages of areas for different types of land use compared to total areas were calculated within the buffers. For transportation facilities and physical geography, we computed the distances to the closest public transportation depots and the boundary lines. The vegetation index and altitude were estimated at a given location by using satellite data. The summary statistics of geographic variables in Seoul across monitoring sites showed different patterns between urban background and urban roadside sites. This study provided practical knowledge on the computation process of geographic variables in South Korea, which will improve air pollution prediction models and contribute to subsequent health analyses.