• The Korean Journal of Ecology
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• 제14권3호
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• pp.231-241
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• 1991

The analyses of correlation, enviromental gradient, continuum and polar ordination methods were used for studing on relationships between forest vegetation and their habitats in Mt. changan, chagsu-gun, korea. influencing correlation of moisture index to the main 41species from the study area they were composed of several groups by leading species of quercus mongoulica, that of carpinus tschonoskii and that of fraxinus mandshurica. On the other hand, it was found three communities in different habitats by environmental gradient i.e. each community of f. mandshurica, mangnolia sieboldii and hydrangea serrata for. acuminata have occurred in moist place, that of c. teschonoskii and q. serrata, in mesic and that of q. mongolica, q.variabilis, rhododendron schlippenbachii, in dry. in addition an occupied distribution area was investigated according to continuum index e.g. cornus controversa,betula costata,q. variabilis, q. serrata and q. mongolica over altitudinal 800m were distributed to a habitat were forming climax by q. mongolica, and/or c. controversa, f. mandshurica, q. serrata and c. tschonoskii under altitudinal 800m were done, by g. tschonoskii. while the forest vegetation of the area was classified into 6 communities such as q. mongolica community, q. variabilis community,q. serrata community, g. tschonoskii community,c. controversa community and f. mandshurica community by means of polar ordination analysis and these have come under the influence of environmental factors.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.415-418
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• 2004

The Studying is on developing precision of the moisture information on a soil. We used the data of AQUA AMSR-E which were obtained by Direct Receiving System in Korea Meteorological Administration(KMA). Although we know the Soil Moisture Information(SMI) helps the numerical weather model to produce the realistic results, we couldn't do it for the problem on a spatial resolution of the data is too low to apply. So we've tried to develop in a spatial resolution by using the AMSR-E data with a Digital Elevation Model(DEM) and Normal Difference Vegetation Index(NDVI) from AQUA MODIS and compared the difference between their information in statics. The result is more precise than the simple algorithm by a polarization ratio, and we could get the better result to use in forecast practically, if it's apply to get more detail in the vegetation temperature.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume I
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• pp.441-444
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• 2006

The MERIS MCI (Maximum Chlorophyll Index), measuring the radiance peak at 709 nm in water-leaving radiance, indicates the presence of a high surface concentration of chlorophyll ${\underline{a}}$ against a scattering background. The index is high in 'red tide' conditions (intense, visible, surface, plankton blooms), and is also raised when aquatic vegetation is present. A bloom search based on MCI has resulted in detection of a variety of events in Canadian, Antarctic and other waters round the world, as well as detection of extensive areas of pelagic vegetation (Sargassum spp.), previously unreported in the scientific literature. Since June 1 2006, global MCI composite images, at a spatial resolution of 5 km, are being produced daily from all MERIS (daylight) passes of Reduced Resolution (RR) data. The global composites significantly increase the area now being searched for events, though the reduced spatial resolution may cause smaller events to be missed. This paper describes the composites and gives examples of plankton bloom events that they have detected. It also shows how the composites show the effect of the South Atlantic Anomaly, where cosmic rays affect the MERIS instrument.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2008년도 학술발표회 논문집
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• pp.1087-1091
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• 2008

Evapotranspiration (ET) is an important factor while simulating daily streamflow in hydrological models. The LAI (Leaf Area Index) value reflecting the conditions of vegetation generally affects considerably in the estimation of ET, for example, when using FAO Penman Monteith equation. Recently in evaluating the vegetation condition as a fixed quantity, the remotely sensed LAIs from MODIS satellite data are avaliable, and the time series values of spatial LAI coupled with land use classes are utilized for ET evaluation. The 4 years (2001-2004) MODIS LAI data were prepared for the evaluation of continuous hydrological model, SLURP (Semi-distributed Land Use-based Runoff Processes). The model was applied for simulating the dam inflow of Chungjudam watershed ($6661.58\;km^2$) located in the upstream of Han river basin of South Korea. From the model results, the FAO Penman Monteith ET was affected by the MODIS LAIs. Especially for the ET of deciduous forest, the Total ET was 33.9 % lager than coniferous forest for the 3.8 % lager of LAI. The watershed average LAI caused a 7.0 % decrease in average soil moisture of the watershed and 14.3 % decrease of ground water recharge.

• 한국환경복원기술학회지
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• 제16권5호
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• pp.59-69
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• 2013

Global warming also has effects on the phenology. The limitation of phenology study is an acquisition of phenology data. Satellite images analysis can make up limitation of monitering data. This study is to analyze spatial distribution and characteristics of phenology changes using MODIS images. Research data collected images of 16 day intervals of 11 years from year 2001 to 2010. The data analyzed 228 images of 11 years. It can figure out changes of phenology by analyzing enhanced vegetation index of MODIS image. We made a comparison between changes of phenology and flowering of cherry blossoms. As a results, Startup of season spatially was getting late from southern area to north area. Startup of Phenology was foreshortened 13 days during 11 years, and change ratios of cherry blooming was getting more faster from 0.18 dat to 0.22 day per year during that same period.

• Plant Resources
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• 제6권2호
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• pp.114-119
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• 2003

In this study, an on-site survey was conducted around Gasado island at Jodo-myeon, Jindo-gun, Jeonnam during July 2 to 25, 2002. The naturalized plants investigated in the surveyed sites were revealed 15 families and 39 species, including Althaea rosea and Oxalis articulata, which are ornamental plants. Only 10 species appeared in Imjado island among the surveyed sites the surveyed sites and Imjado Island, including Elymus sibiricus, Lolium perenne, Chenopodium album, Oxalis articulata, Oxalis corymbosa, Oenothera odorata, Xanthium strumarium, Bidens frondosa, Ambrosia artemisiaefolia var. elatior, and Taraxacum officinale. 6 species were distributed only in Gasado island, Jindo-gun, which included include Festuca myuros, Chenopodium ambrosioides, Amorpha fruiticosa, Malva neglecta, Calendula arvensis, and Carthamus tinctorius. 18 species were showed in Soheuksan island.; Yeosu area, 29 species; Imja Island in Sinan-gun, 34 species, and Gasado Island in Jindo-gun revealed 39 species. It is believed that the species of naturalized plants have been expanded compared to the other areas because of close location to the inland and large population fastiy. The Urbanization Index(UI) of this area was found to be 19.5. The naturalized plant communites in these surveyed sites were classified into Rumex crispus, Elymus sibiricus, and Lolium perenne community according to the vegetation table. Furthermore, they formed a community around areas that received great artificial influence from human dwellings or roads due to the characteristics of species distribution

• Weed & Turfgrass Science
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• 제4권4호
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• pp.338-347
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• 2015

Reinforcement cells are used to aid grass growth and taken together, this serves to extend greenery beyond the conventional spaces of lawns, tree pits, gardens, and parks, and is advantageous to urban cities since space for greening is often limited. Drought has variable effects on plant life and the resilience of turf to drought resistance also varies with species. Changes in photosynthetic ability were more pronounced for media rather than grass species. The media of sand without organic matter was found to be least suited for drought resistance. Normalized difference vegetation index (NDVI) and digital image analysis (DIA) data were generally in favour of Zoysia species as oppose to A. compressus. In A. compressus, selective traits such as, a more extensive root system and lower specific leaf area (SLA) were not an underlying factor that assisted this grass with enhanced drought resistance. Generally, WUE was found to be strongly related to plant characterises such as overall biomass, photosynthetic features as well as the lushness indexes, and specific leaf area. This study found a strong relationship between WUE and a suite of plant characteristics. These traits should serve as useful selection criteria for species with the ability to resist water stress.

• 대한원격탐사학회지
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• 제16권4호
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• pp.327-338
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• 2000

The forest conditions of North Korea has been a great concern since it was known to be closely related to many environmental problems of the disastrous flooding, soil erosion, and food shortage. To assess the long-term changes of forest area as well as the canopy conditions, several sources of multitemporal satellite data were applied to the study area near Kaesung. KOMPSAT-1 EOC data were overlaid with 1981 topographic map showing the boundaries of forest to assess the deforestation area. Delineation of the cleared forest was performed by both visual interpretation and unsupervised classification. For analyzing the change of forest canopy condition, multiple scenes of Landsat and SPOT data were selected. After preprocessing of the multitemporal satellite data, such as image registration and normalization, the normalized difference vegetation index (NDVI) was derived as a representation of forest canopy conditions. Although the panchromatic EOC data had radiometric limitation to classify diverse cover types, they can be effectively used t detect and delineate the deforested area. The results showed that a large portion of forest land has been cleared for the urban and agricultural uses during the last twenty years. It was also found that the canopy condition of remaining forests has not been improved for the last twenty years. It was also found that the canopy condition of remaining forests has not been improved for the last twenty years. Possible causes of the deforestation and the temporal pattern of canopy conditions are discussed.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.230-230
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• 2023

딥러닝 알고리즘 중 과거의 정보를 저장하는 문제(장기종속성 문제)가 있는 단순 RNN(Simple Recurrent Neural Network)의 단점을 해결한 LSTM(Long short-term memory)이 등장하면서 특정한 유역의 강우-유출 모형을 구축하는 연구가 증가하고 있다. 그러나 하나의 모형으로 모든 유역에 대한 유출을 예측하는 지역화 강우-유출 모형은 서로 다른 유역의 식생, 지형 등의 차이에서 발생하는 수문학적 행동의 차이를 학습해야 하므로 모형 구축에 어려움이 있다. 따라서, 본 연구에서는 국내 12개의 유역에 대하여 LSTM 기반 분포형 지역화 강우-유출 모형을 구축한 이후 강우 이외의 보조 자료에 따른 정확도를 살펴보았다. 국내 12개 유역의 7년 (2012.01.01-2018.12.31) 동안의 49개 격자(4km²)에 대한 10분 간격 레이더 강우, MODIS 위성 이미지 영상을 활용한 식생지수 (Normalized Difference Vegetation Index), 10분 간격 기온, 유역 평균 경사, 단순 하천 경사를 입력자료로 활용하였으며 10분 간격 유량 자료를 출력 자료로 사용하여 LSTM 기반 분포형 지역화 강우-유출 모형을 구축하였다. 이후 구축된 모형의 성능을 검증하기 위해 학습에 사용되지 않은 3개의 유역에 대한 자료를 활용하여 Nash-Sutcliffe Model Efficiency Coefficient (NSE)를 확인하였다. 식생지수를 보조 자료를 활용하였을 경우 제안한 모형은 3개의 검증 유역에 대하여 하천 흐름을 높은 정확도로 예측하였으며 딥러닝 모형이 위성 자료를 통하여 식생에 의한 차단 및 토양 침투와 같은 동적 요소의 학습이 가능함을 나타낸다.

• Journal of Animal Science and Technology
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• 제65권6호
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• pp.1254-1269
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• 2023

This study aims to predict the change in corn share according to the grazing of 20 gestational sows in a mature corn field by taking images with a camera-equipped unmanned air vehicle (UAV). Deep learning based on convolutional neural networks (CNNs) has been verified for its performance in various areas. It has also demonstrated high recognition accuracy and detection time in agricultural applications such as pest and disease diagnosis and prediction. A large amount of data is required to train CNNs effectively. Still, since UAVs capture only a limited number of images, we propose a data augmentation method that can effectively increase data. And most occupancy prediction predicts occupancy by designing a CNN-based object detector for an image and counting the number of recognized objects or calculating the number of pixels occupied by an object. These methods require complex occupancy rate calculations; the accuracy depends on whether the object features of interest are visible in the image. However, in this study, CNN is not approached as a corn object detection and classification problem but as a function approximation and regression problem so that the occupancy rate of corn objects in an image can be represented as the CNN output. The proposed method effectively estimates occupancy for a limited number of cornfield photos, shows excellent prediction accuracy, and confirms the potential and scalability of deep learning.