• 한국환경복원기술학회지
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• 제18권2호
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• pp.89-104
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• 2015

In order to effectively manage forested areas in South Korea on a national scale, using remotely sensed data is considered most suitable. In this study, utilizing Land coverage maps and Forest type maps of national geographic information instead of collecting field data was tested for conducting supervised classification on SPOT-5 and KOMPSAT-2 imagery focusing on forested areas. Supervised classification were conducted in two ways: analysing a whole area around the study site and/or only forested areas around the study site, using Support Vector Machine. The overall accuracy for the classification on the whole area ranged from 54.9% to 68.9% with kappa coefficients of over 0.4, which meant the supervised classification was in general considered moderate because of sub-classifying forested areas into three categories (i.e. hardwood, conifer, mixed forests). Compared to this, the overall accuracy for forested areas were better for sub-classification of forested areas probably due to less distraction in the classification. To further improve the overall accuracy, it is needed to gain individual imagery rather than mosaic imagery to use more spetral bands and select more suitable conditions such as seasonal timing. It is also necessary to obtain precise and accurate training data for sub-classifying forested areas. This new approach can be considered as a basis of developing an excellent analysis manner for understanding and managing forest landscape.

• Journal of Forest and Environmental Science
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• 제34권6호
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• pp.429-434
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• 2018

Extractable iron (Fe), manganese (Mn), zinc (Zn) and copper (Cu) contents and their distribution with depths in soils of forested and adjacent deforested areas at Jahazpura, Teknaf, Cox's Bazar of Bangladesh were studied. The soils under forest showed higher levels of DTPA-extractable micronutrients in all three layers of soil in comparison to those of the deforested areas. The differences between forested and deforested sites were, in most cases, significant.. The top soils of forested sites had the higher contents of micronutrient and generally decreased with depth in forested soils, while there was no regular trend of distribution in deforested soils. The study also revealed that contents of extractable Fe, Mn and Cu were sufficient in all depths and sites but Zn was deficient in bottom layer of forested and all three layers of deforested sites. The results suggested that organic matter, clay and soil pH could play important roles in concentrations and distributions of micronutrients in soils of the study areas.

• Perspectives in Nursing Science
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• 제12권1호
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• pp.14-22
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• 2015

Purpose: Forests have positive effects on health due to phytoncide, thus increasing physical activity and stress relief. However, research has not been conducted on the daily health benefits of existing forests. Therefore, this study attempts to compare the health status and behaviors of residents in urban and forested areas. Methods: This cross-sectional study used anthropometric measures, blood tests, heart rate variability, depression, stress, and health behavior self-reports for adults between 35 and 79 years from two regions. Results: Adults living in a forested region had better health consequences-including lower prevalence of osteoarthritis (6.4%) and mean bone mineral density (-0.84) -than those in an urban region (osteoarthritis: 13.7%; bone mineral density: -1.55). The percentage of 'physically active' participants (measured in MET-minutes) differed significantly different between the forested (49.1%) and urban (7.3%) areas. However, health behaviors such as smoking, alcohol consumption, and regular heath check-up rates were worse among residents from the forested, than the urban area. Conclusion: We concluded that more proactive forest therapy programs are needed to prove the health differences.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.244-247
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• 2003

Multi-temporal data is used to determine the rate of deforestation between the years 1976, 1987 and 2000. Three Landsat TM images, for each period, are pre-processed, mosaicked and normalized difference vegetation index (NDVI) values computed. Based on the values, totally non-forested areas are masked out. The forested areas, both partially and wholly, show a very high degree of correlation between all the bands (reflective), thus necessitating application of principal component analysis. The first two principal components and NDVI values (scaled to 0 ? 255) are used in K-means unsupervised classification to distinguish forest from non-forest areas (that appeared as forest at first). Comparison of the resulting thematic maps gives an annual deforestation rate of roughly 15 0000ha. or 2% between any two epochs.

• 한국환경과학회지
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• 제2권2호
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• pp.153-160
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• 1993

산지유역에서 토사공급과 이동에 관한 문제는 동적지형학뿐만 아니 수문학적 순환의 입장에서 매우 중요하다. 토사유출 자연의 개변정도등 지형학적 요인에 크게 지배된다. 본 연구에서는 강우시 자연의 개변정도가 서로 다른 유역에서 유출되는 부류토량을 비교하여 부류토사 유출과정과 메타니즘을 알아 보았다. 강우강도가 유사한 30mm의 비가 내렸을때 채석장이 분포하고 있는 인공개변유역의 부유토사농도는 최고 27,000mg/l인 반면, 백연유역의 부유토사농도는 270mg/l에 불과해 100배 정도의 농도차이가 나타났다. 또 인공개역중에서도 인공개변도에 따라 최대부유토사양도 6,400mg/l에서 27,000mg/l까지 다양하게 관측되었다. 일반적으로 부유토사 공급원은 자연유역의 경우 하상, 하안, 그리고 하도주변하도입이며, 인공개변유역은 사면등의 하도외 지역이다.

• 한국환경생태학회지
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• 제21권1호
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• pp.30-37
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• 2007

한국중부 지역에 서식하는 수리부엉이(Bubo bubo)의 먹이를 확인하고 서식 환경에 따른 먹이습성을 파악하기 위하여 사냥흔적 및 먹이 잔존물 82개, 소화되지 않은 먹이 덩어리인 펠릿(pellet) 55개를 각각 분석하였다. 그 결과 조류, 포유류 및 곤충으로 구성된 총 150개체의 먹이가 확인되었으며, 그 중 조류의 이용 빈도(56.67%) 및 생물량(78.04%)이 가장 높았다. 집쥐류(Rattus spp.), 꿩(Phasianus colchicus), 등줄쥐(Apodemus agrarius)를 흔히 이용하였으나, 생물량 측면에서 꿩이 가장 중요한 먹이로 나타났다. 척추동물을 기준으로 한 수리부엉이 먹이의 평균 생물량은 503.3g으로서 비교적 다양한 크기의 먹이를 포식하였으나, 개활지 보다 산림지역에서 더 크고 다양한 먹이를 이용하였다. 산림지역에서는 꿩과 원앙(Aix galericulata) 등의 조류를 많이 포식하였으나, 특정 분류군을 선호하기 보다 적정 크기의 먹이를 선호하는 양상을 보였다. 반면 개활지에서는 소형의 특정 포유류(설치류)에 의존하면서 큰 생물량을 가진 꿩 등의 조류를 일부 이용하는 기회주의적인 먹이습성을 보였다.

• 한국지형학회지
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• 제24권1호
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• pp.1-12
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• 2017

Planting trees is a very common practice in the coastal dunefields of South Korea as a way to stabilize dune landscapes and protect inland residential areas from strong winds and blown sands. On the other hand, disturbing the original foredune environment may deteriorate the ability of coastal landsto recover from coastal erosion after storms, causing a retreat of coastline. However, there is little information of this sort on the surface of forested dunefields. Airborne LiDAR or drone-based mapping is not easily applicable in such areas. In this study, we developed a digital terrain model of Dasari dunefields, Chungnam Province, based on direct topographic surveys with real-time kinematic GPS and total stations. We also analyzed previous two aerial photographs taken in 1947 and 1966, in order to detect an older landforms of the dunefields. Results suggested that there have been little changes in geomorphology of the Dasari dunefields for the last 50 years, despite continued tree plantings. Today, there are remains of U-shaped structures such as blowouts and parabolic dunes in the dunefields.

• 한국농공학회논문집
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• 제60권3호
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• pp.37-50
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• 2018

Local climate characteristics for both urban and rural areas can be attributed to multiple factors. Two factors affecting these characteristics include: 1) greenhouse gases related to global warming, and 2) urban heat island (UHI) effects caused by changes in surface land use and energy balances related to rapid urbanization. Because of the unique hydrological and climatological characteristics of cities compared with rural and forested areas, distinguishing the impacts of global warming urbanization is important. In this study, we analyzed anthropogenic climatic changes caused by rapid urbanization. Weather elements (maximum temperature, minimum temperature, and precipitation) over the last 60 years (1955-2016) are compared in urban areas (Seoul, Incheon, Pohang, Daegu, Jeonju, Ulsan, Gwangju, Busan) and rural/forested areas (Gangneung, Chupungnyeong, Mokpo, and Yeosu). Temperature differences between these areas reveal the effects of urbanization and global warming. The findings of this study can be used to analyze and forecast the impacts of climate change and urbanization in other urban and non-urban areas.

• Asian Journal of Atmospheric Environment
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• 제12권1호
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• pp.67-77
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• 2018

To investigate the effects of forest and the surrounding natural and anthropogenic sources on the bulk depositions on forested land, this study examined differences in ion concentrations between wet-only and bulk samples at two forested sites in Japan. The surrounding natural and anthropogenic sources at each site were different; Shirasaka is in a rural area and Tanashi is an urban environment. The volume weighted (vw) mean concentrations of $K^+$ and $Ca^{2+}$ in the bulk samples were significantly (p<0.05) higher than those in the wet-only samples at both sites. The forest canopy and a nearby incineration plant were hypothesized to be the main sources of $K^+$ contaminants at Shirasaka and Tanashi, respectively. The transport of sea salt and urban dust may explain the presence of enriched $Ca^{2+}$ concentrations in the bulk samples at Shirasaka and Tanashi, respectively. The $NH_4{^+}$ concentrations in the Shirasaka bulk samples were significantly (p<0.05) lower than those in the wet-only samples. The vw mean $SO{_4}^{2-}$ and $NO_3{^-}$ concentrations in both sample types were not significantly different at either site. This study demonstrated that the ion concentration differences between wet-only and bulk samples were affected by nearby natural and anthropogenic sources even at forest sites, similar to previous findings for non-forested locations. However, the $K^+$ concentration differences between wet-only and bulk samples may be higher owing to forest sources, even in the absence of anthropogenic sources.

• 지질공학
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• 제34권1호
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• pp.107-115
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• 2024

This study assesses forest fire susceptibility in Gangwon-do, South Korea, which hosts the largest forested area in the nation and constitutes ~21% of the country's forested land. With 81% of its terrain forested, Gangwon-do is particularly susceptible to wildfires, as evidenced by the fact that seven out of the ten most extensive wildfires in Korea have occurred in this region, with significant ecological and economic implications. Here, we analyze 480 historical wildfire occurrences in Gangwon-do between 2003 and 2019 using 17 predictor variables of wildfire occurrence. We utilized three machine learning algorithms—random forest, logistic regression, and support vector machine—to construct wildfire susceptibility prediction models and identify the best-performing model for Gangwon-do. Forest and soil map data were integrated as important indicators of wildfire susceptibility and enhanced the precision of the three models in identifying areas at high risk of wildfires. Of the three models examined, the random forest model showed the best predictive performance, with an area-under-the-curve value of 0.936. The findings of this study, especially the maps generated by the models, are expected to offer important guidance to local governments in formulating effective management and conservation strategies. These strategies aim to ensure the sustainable preservation of forest resources and to enhance the well-being of communities situated in areas adjacent to forests. Furthermore, the outcomes of this study are anticipated to contribute to the safeguarding of forest resources and biodiversity and to the development of comprehensive plans for forest resource protection, biodiversity conservation, and environmental management.