• Title/Summary/Keyword: VEGETATION INDEX

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Application of Three-Dimensional Model to Evaluate Stream Discharge Capacity due to Vegetation (식생분포에 따른 하도의 통수능 검토를 위한 3차원 모형의 적용)

  • Noh, Joon Woo;Lee, Jin Young;Ahn, Ki Hong
    • Journal of Environmental Impact Assessment
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    • v.20 no.1
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    • pp.37-48
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    • 2011
  • Recently, the social and environmental functions of nature river are important due to the increase of expectation for river restoration. So it should be considered the effect of vegetation affecting the conveyance capacity and hydraulic resistance. However, it has not yet proposed a objective standard and modeling method to estimate the effect of conveyance capacity according to vegetaion distribution in the watercourse such as water level or velocity. Therefore, this study simulates the variations of water level and velocity using 3-dimensional hydrodynamic model, EFDC, to consider a conveyance capacity in downstream of the Soyang Reservoir. The simulation results were validated using statistical index such as F-test and T-test. As results, the water level rises about 0.01 to 0.47m and velocity difference are about -0.95m/s to 0.23m/s.

Retrieval of emissivity and land surface temperature from MODIS

  • Suh Myoung-Seok;Kang Jeon-Ho;Kim So-Hee;Kwak Chong-Heum
    • Proceedings of the KSRS Conference
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    • 2005.10a
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    • pp.165-168
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    • 2005
  • In this study, emissivity and land surface temperature (LST) were retrieved using the previously developed algorithms and Aqua/MODIS data. And sensitivity of estimated emissivity and LST to the predefined values, such as land cover, normalized difference vegetation index (NOVI) and spectral emissivity were investigated. The methods used for emissivity and LST were vegetation cover method (VCM) and four different split-window algorithms. The spectral emissivity retrieved by VCM was not sensitive to the NOVI error but more sensitive to the land cover error. The comparison of LST showed that the LST was systematically different without regard to the land cover and season. And the LST was very sensitive to the emissivity error excepting the Uliveri et al. This preliminary result indicates that more works are needed for the retrieval of reliable LST from satellite data.

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Development of Vegetation Structure Measurement System using Multi-angle Stereo pair Images

  • DEMIZU Masaki;KAJIWARA Koji;HONDA Yoshiaki
    • Proceedings of the KSRS Conference
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    • 2004.10a
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    • pp.170-173
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    • 2004
  • When the data from the artificial satellite is analyzed, recent years it is perceived to vegetation index using BRF(Bi-directional Reflectance Factor) of the observation target. To make the BRF models, it is important to measure the 3D structure of the observation target actually. In this study, it is proposed to the observation technique by using multi-angle stereo pair image, and shown the observation result in grassland area. Also, our team has been operating the radio controlled helicopter which can fly over the tall forest canopy and it can be equipped the measurement system.

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A Study on the Priority Area Selection for Updating FDB Attributes using MODIS Product (MODIS Product를 활용한 FDB 속성 갱신 대상지역 선정 연구)

  • Park, Wan-Yong;Eo, Yang-Dam;Kim, Yong-Min;Kim, Chang-Jae
    • Journal of the Korea Institute of Military Science and Technology
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    • v.16 no.1
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    • pp.65-73
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    • 2013
  • FDB(Feature DataBase) attributes have been produced by using the resource data prior to the year 2002. Due to this reason, the attributes need to be updated to the up-to-date ones. In this regards, this study focuses on the way of finding areas whose attributes need to be updated. Forest and crop classes were chosen as target classes among FDB features. MODIS Landcover data and FDB are, first, compared to detect the changed forest and crop areas from 2001 to 2008. Then, vegetation vitality changes are analyzed using MODIS annual NDVI data. Based on the change detection and the vegetation vitality analysis, the index of area selection for updating FDB attributes is proposed in this study.

Development of Vegetation Structure after Forest Fire in the East Coastal Region, Korea (동해안 산불 피해지에서 산불 후 경과 년 수에 따른 식생 구조의 발달)

  • 이규송;정연숙;김석철;신승숙;노찬호;박상덕
    • The Korean Journal of Ecology
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    • v.27 no.2
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    • pp.99-106
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    • 2004
  • We developed the estimation model for the vegetation developmental processes on the severely burned slope areas after forest fire in the east coastal region, Korea. And we calculated the vegetation indices as a useful parameter for the development of land management technique in the burned area and suggested the changes of the vegetation indices after forest fire. In order to estimate the woody standing biomass in the burned area, allometric equations of the 17 woody species regenerated by sprouter were investigated. According to the our results, twenty year after forest fire need for the development to the normal forest formed by 4 stratum structure, tree, sub-tree, shrub and herb layer. The height of top vegetation layer, basal area and standing biomass of woody species show a tendency to increase linearly, and the ground vegetation coverage and litter layer show a tendency to increase logarithmically after forest fire. Among vegetation indices, Ive and Ivcd show a tendency to increase logarithmically, and Hcl and Hcdl show a tendency to increase linearly after forest fire. The spatial variation of the most vegetation factors was observed in the developmental stages less than the first 5 years which were estimated secondary disaster by soil erosion after forest fire. Among vegetation indices, Ivc and Ivcd were the good indices for the representation of the spatial heterogeneity in the earlier developmental stages, and Hcl and Hcdl were the useful indices for the long-term estimation of the vegetation development after forest fire.

Forest Type Classification and Ecological Characteristics for Areas of Cheonwangbong, Songnisan (속리산 천왕봉 일대의 산림형 분류와 생태적 특성)

  • Chung, Sang Hoon;Hwang, Kwang Mo;Sung, Joo Han;Kim, Ji Hong
    • Journal of Korean Society of Forest Science
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    • v.104 no.3
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    • pp.375-382
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    • 2015
  • We classified the forest type and figured out the ecological characteristics for each of the types in order to provide the basic informations for being induced ecologically efficient forest practice plan by vegetation units in the natural forest of Songnisan. We established the 250 sample points and collected the vegetation data of vertical distribution for each sample. A variety of multivariate statistical methods were applied to classify the forest types. The species diversity index were analyzed to estimate the stability and maturity for forest vegetation in each the type. The types were divided from two to ten clusters by cluster analysis. The appropriate number of clusters was estimated five clusters by indicator species analysis. It was verified through the multiple discriminant analysis that the estimated number of clusters had been suitable. Based on the species composition for each the type, this study site was classified into five forest types: 1) Quercus serrata and 2) mixed mesophytic forest in the valley area, 3) Q. mongolica forest in the main ridge, 4) Pinus densiflora forest in the sub-ridge extending from the main, and 5) Q. variabilis-P. densiflora forest between the sub-ridge and valley. The species diversity index of the pine forest that had been a simple species composition was the lowest while that of the mixed mesophytic forest of which the composition had been diverse was the highest. As the forest vegetation was more varied, the index showed a tendency to increase.

A study of artificial neural network for in-situ air temperature mapping using satellite data in urban area (위성 정보를 활용한 도심 지역 기온자료 지도화를 위한 인공신경망 적용 연구)

  • Jeon, Hyunho;Jeong, Jaehwan;Cho, Seongkeun;Choi, Minha
    • Journal of Korea Water Resources Association
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    • v.55 no.11
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    • pp.855-863
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    • 2022
  • In this study, the Artificial Neural Network (ANN) was used to mapping air temperature in Seoul. MODerate resolution Imaging Spectroradiomter (MODIS) data was used as auxiliary data for mapping. For the ANN network topology optimizing, scatterplots and statistical analysis were conducted, and input-data was classified and combined that highly correlated data which surface temperature, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), time (satellite observation time, Day of year), location (latitude, hardness), and data quality (cloudness). When machine learning was conducted only with data with a high correlation with air temperature, the average values of correlation coefficient (r) and Root Mean Squared Error (RMSE) were 0.967 and 2.708℃. In addition, the performance improved as other data were added, and when all data were utilized the average values of r and RMSE were 0.9840 and 1.883℃, which showed the best performance. In the Seoul air temperature map by the ANN model, the air temperature was appropriately calculated for each pixels topographic characteristics, and it will be possible to analyze the air temperature distribution in city-level and national-level by expanding research areas and diversifying satellite data.

Deep Learning-based Forest Fire Classification Evaluation for Application of CAS500-4 (농림위성 활용을 위한 산불 피해지 분류 딥러닝 알고리즘 평가)

  • Cha, Sungeun;Won, Myoungsoo;Jang, Keunchang;Kim, Kyoungmin;Kim, Wonkook;Baek, Seungil;Lim, Joongbin
    • Korean Journal of Remote Sensing
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    • v.38 no.6_1
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    • pp.1273-1283
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    • 2022
  • Recently, forest fires have frequently occurred due to climate change, leading to human and property damage every year. The forest fire monitoring technique using remote sensing can obtain quick and large-scale information of fire-damaged areas. In this study, the Gangneung and Donghae forest fires that occurred in March 2022 were analyzed using the spectral band of Sentinel-2, the normalized difference vegetation index (NDVI), and the normalized difference water index (NDWI) to classify the affected areas of forest fires. The U-net based convolutional neural networks (CNNs) model was simulated for the fire-damaged areas. The accuracy of forest fire classification in Donghae and Gangneung classification was high at 97.3% (f1=0.486, IoU=0.946). The same model used in Donghae and Gangneung was applied to Uljin and Samcheok areas to get rid of the possibility of overfitting often happen in machine learning. As a result, the portion of overlap with the forest fire damage area reported by the National Institute of Forest Science (NIFoS) was 74.4%, confirming a high level of accuracy even considering the uncertainty of the model. This study suggests that it is possible to quantitatively evaluate the classification of forest fire-damaged area using a spectral band and indices similar to that of the Compact Advanced Satellite 500 (CAS500-4) in the Sentinel-2.

Classification of Forest Cover Types in the Baekdudaegan, South Korea

  • Chung, Sang Hoon;Lee, Sang Tae
    • Journal of Forest and Environmental Science
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    • v.37 no.4
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    • pp.269-279
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    • 2021
  • This study was carried out to introduce the forest cover types of the Baekdudaegan inhabiting the number of native tree species. In order to understand the vegetation distribution characteristics of the Baekdudaegan, a vegetation survey was conducted on the major 20 mountains of the Baekdudaegan. The vegetation data were collected from 3,959 sample points by the point-centered quarter method. Each mountain was classified into 4-7 forests by using various multivariate statistical methods such as cluster analysis, indicator species analysis, multiple discriminant analysis, and species composition analysis. The forests were classified mainly according to the relative abundance of Quercus mongolica. There was a total of 111 classified forests and these forests were integrated into the following nine forest cover types using the percentage similarity index and by clustering according to vegetation type: 1) Mongolian oak, 2) Mongolian oak and other deciduous, 3) Oaks (Mixed Quercus spp.), 4) Korean red pine, 5) Korean red pine and oaks, 6) ash, 7) mixed mesophytic, 8) subalpine zone coniferous, and 9) miscellaneous forest. Forests grouped within the subalpine zone coniferous and miscellaneous classifications were characterized by similar environmental conditions and those forests that did not fit in any other category, respectively.

A Comparison of the Plant Community Structures in the Burned and Unburned Areas of Mt Kumo-san (금오산에서 산회지와 비산화지의 식물군집구조 비교)

  • Kim, Woen;Sung, Kyung-Hee
    • The Korean Journal of Ecology
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    • v.19 no.1
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    • pp.55-64
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    • 1996
  • This is a report on the recovery of vegetation and secondary succession in the burned area studied from April, 1990 to April. 1991. The forest fire occurred in a part of Mt. $K\v{u}mo-san$ on April, 1986 and the pine forest and its understory vegetation were burned out completely. The floristic compositions of burned (B) and unburned (U) areas were composed of sixty eight and thirty one species (vascular plants), respectively. These species were divided into invaders (47 species), increasers (15 species), deceasers (3 species), neutrals (3 species), and retreaters (10 species) on the basis of summed dominance ratio ($SDR_3$). Biological spectra showed the $H-D_1-R_5-e$ type in both the burned and unburned areas. The species of Lespedeza ($SDR_3$=94.7), Miscanthus (91.95), Festuca (68.33), and Spodiopogon (52.06) were dominant in the burned areas, while the species of Pinus (76.67), Robinia (56.25), Quercus (52.08), and Carex (40.25)were dominant in the unburned area. Dominance index (C) in burned and unburned areas was 0.15 and 0.25, respectively. the index of similarity (CCs) was 0.42. The degree of succession (DS) and species diversity (H) in burned and unburned areas were 675.8, 884.2 and 4.07, 2.05, respectively. The degree of succession in the burned area graduall increased and the burned area was recovered to be simmilar to the unburned area. Evenness index in burned and unburned areas was 0.965 and 0.595, respectively.

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