• 제목/요약/키워드: normalized difference vegetation index

검색결과 410건 처리시간 0.026초

Application of Highland Kimchi Cabbage Status Map for Growth Monitoring based on Unmanned Aerial Vehicle

  • Na, Sang-Il;Park, Chan-Won;Lee, Kyung-Do
    • 한국토양비료학회지
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    • 제49권5호
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    • pp.469-479
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    • 2016
  • Kimchi cabbage is one of the most important vegetables in Korea and a target crop for market stabilization as well. In particular Kimchi cabbages in a highland area are very sensitive to the fluctuations in supply and demand. Yield variability due to growth conditions dictates the market fluctuations of Kimchi cabbage price. This study was carried out to understand the distribution of the highland Kimchi cabbage growth status in Anbandeok. Anbandeok area in Gangneung, Gangwon-do, Korea is one of the main producing districts of highland Kimchi cabbage. The highland Kimchi cabbage status map of each growth factor was obtained from unmanned aerial vehicle (UAV) imagery and field survey data. Six status maps include UAVRGB image map, normalized difference vegetation index (NDVI) distribution/anomaly map, Crop distribution map, Planting/Harvest distribution map, Growth parameter map and Growth disorder map. As a result, the highland Kimchi cabbage status maps from May 31 to Sep. 6 in 2016 were presented to show spatial variability in the field. The benefits of the highland Kimchi cabbage status map can be summarized as follows: crop growth monitoring, reference for field observations and survey, the relative comparison of the growth condition in field scale, evaluation of growth in comparison of average year, change detection of annual crops or planting areas, abandoned fields monitoring, prediction of harvest season etc.

Response of Soybean (Glycine max L.) to Subsurface Drip Irrigation with Different Dripline Placements at a Sandy-loam Soil

  • Lee, Sanghun;Jung, Ki-Yuol;Chun, Hyen-Chung;Choi, Young-Dae;Kang, Hang-Won
    • 한국토양비료학회지
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    • 제51권2호
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    • pp.79-89
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    • 2018
  • Subsurface drip irrigation (SDI) system is considered one of the most effective methods for water application. A 2-year field study was conducted to investigate the effect of SDI systems with various dripline spacing (0.7 or 1.4 m) and position (under furrow or ridge) on soybean (Glycine max L.) production at a sandy-loam soil in Miryang, South Korea. For 2016-2017, average grain yield in SDI irrigated plots, $3.16Mg\;ha^{-1}$, was statistically greater than rainfed irrigated plot ($2.63Mg\;ha^{-1}$). Soybean grain yield averaged $3.25Mg\;ha^{-1}$ for the 0.7 m dripline spacing and $3.07Mg\;ha^{-1}$ for the 1.4 m spacing for the two-year period compared to a rainfed irrigated average of $2.63Mg\;ha^{-1}$ for the same period. Soybean treated with SDI system had significantly greater values of normalized difference vegetation index and stomatal conductance, indicating that soybean plants in SDI plots had greater photosynthetic and stomatal activity due to the higher water availability in soil. Irrigation water use efficiency (IWUE) was greatest in the plot of 0.7 m spacing installed under ridge position than any other plot across growing season. Average soil water content in plots with 0.7 m dripline spacing was $0.21m^3\;m^{-3}$ at 5 cm depth layer, which was 45% greater compared to the plots with 1.4 m spacing, even though the gross irrigation amounts were greater in 1.4 m spacing plots. It is concluded that wide dripline spacing (1.4 m) is probably the more economical installation design for SDI system compared to 0.7 m spacing in this study soil because the initial cost for dripline may be reduced with wide spacing design, even though the IWUE is greater in the plot of 0.7 m dripline spacing.

Spatial analysis of Shoreline change in Northwest coast of Taean Peninsula

  • Yun, MyungHyun;Choi, ChulUong
    • 대한원격탐사학회지
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    • 제31권1호
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    • pp.29-38
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    • 2015
  • The coastline influenced naturally and artificially changes dynamically. While the long-term change is influenced by the rise in the surface of the sea and the changes in water level of the rivers, the short-term change is influenced by the tide, earthquake and storm. Also, man-made thoughtless development such as construction of embankment and reclaimed land not considering erosion and deformation of coast has been causes for breaking functions of coast and damages on natural environment. In order to manage coastal environment and resources effectively, In this study is intended to analyze and predict erosion in coastal environment and changes in sedimentation quantitatively by detecting changes in coastal line from data collection for satellite images and aerial LiDAR data. The coastal line in 2007 and 2012 was extracted by manufacturing Digital Surface Model (DSM) with Aviation LiDAR materials. For the coastal line in 2009 and 2010, Normalized Difference Vegetation Index (NDVI) method was used to extract the KOMPSAT-2 image selected after considering tide level and wave height. The change rate of the coastal line is varied in line with the forms of the observation target but most of topography shows a tendency of being eroded as time goes by. Compared to the relatively monotonous beach of Taean, the gravel and rock has very complex form. Therefore, there are more errors in extraction of coastlines and the combination of transect and shoreline, which affect overall changes. Thus, we think the correction of the anomalies caused by these properties is required in the future research.

NDVI 시계열 시리즈에 의한 한반도 지표면 변화 추적

  • 이상훈
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2009년도 춘계학술대회 논문집
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    • pp.97-100
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    • 2009
  • 육상의 지표면 파라미터는 기후와 주로 연관되어 있으므로 육상 관측 위성 영상에 나타나는 많은 물리적 과정은 계절 주기에 따른 시간적 변화를 보인다. 본 연구에서는 계절에 따라 변하는 물리적 과정을 포함하는 시계일 원격 탐사 영상 시리즈를 어댑티브 피드백 시스템에 의해 복원한다. 이 시스템에서는 계절적 변화를 추적하기 위하여 하모닉 모델을 사용하고 수치 영상 모형의 공간적 의존성을 나타내기 위해 깁슨 랜덤 필드를 사용한다. 복원과정을 통하여 구성된 하모닉 모델과 어댑티브 계수에 의해 지표면 연속적 변화를 감시할 수 있다. 본 연구에서는 1996년부터 2000년까지 한반도로부터 관측된 AVHRR 영상 시리즈를 일주일 간격으로 정적 합성하여 NOVI 시리즈를 구하고 하모닉 모델을 사용하는 어댑티브 복원 시스템을 이 NDVI 시리즈를 적용하여 한반도 지표면 변화를 추적하였다. 연구 결과는 하모닉 어댑티브 복원시스템이 거의 실시간으로 지표면 변화를 감시하는데 매우 효과적인 수단이 될 것이라는 잠재성을 보여준다.

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MODIS 이미지를 이용한 지표특성에 따른 토양수분의 시·공간적 분포 특성 (Characteristics of Soil Moisture Distributions at the Spatio-Temporal Scales Based on the Land Surface Features Using MODIS Images)

  • 김상우;신용철;이태화;이상호;최경숙;박윤식;임경재;김종건
    • 한국농공학회논문집
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    • 제59권6호
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    • pp.29-37
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    • 2017
  • In this study, we analyzed the impacts of land surface characteristics on spatially and temporally distributed soil moisture values at the Yongdam and Soyang-river dam watersheds in 2014 and 2015. The soil moisture, NDVI (Normalized Difference Vegetation Index) and temperature values at the spatio-temporal scales were estimated using satellite-based MODIS (MODerate Resolution Imaging Spectroradiometer) products. Then the Pearson correlations between soil moisture and land surface characteristics (NDVI, temperature and DEM-digital elevation model) were estimated and analyzed, respectively. Overall, the monthly soil moisture values at the time step were highly influenced by the precipitation amounts. Also, the results showed that the soil moisture has the strong correlation with DEM while the temperature was inversely correlated with the soil moisture. However the monthly correlations between NDVI and soil moisture were highly varied along the time step. These findings indicated that water loss near the land surface are highly occurred by soil and plant activities as evapotranspiration and infiltration during the no/less precipitation period. But the high precipitation amounts reduce the impacts of land surface characteristics because of saturated condition of land surface. Thus these results demonstrated that soil moisture values are highly correlated with land surface characteristics. Our findings can be useful for water resources/environmental management, agricultural drought, etc.

위성영상자료를 이용한 서울시 도시녹지의 평가기법 연구: 북한산 국립공원 주연부 탐지 (A Study on the Evaluation Method of Urban Open Spaces of Seoul with Remote Sensing: Detection of the Ecotone of the Mt. Pukhansan National Park)

  • 박종화
    • 대한원격탐사학회지
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    • 제11권3호
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    • pp.71-81
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    • 1995
  • 본 연구의 목적은 북한산 국립공원 경계선 일대의 추이대를 탐지하는 기법을 개발하여 추이대의 폭을 조사하고, 시간경과에 따른 추이대의 폭의 변화여부를 조사하여 과도한 이용자의 집중과 주변부의 환경오염에 의한 추이대 식생의 피해 여부를 규명하는 것이다. 이를 위해서 1985, 1987, 1993년 5월 중순에 수신된 TM영상을 이용하여 계산한 정규식생지수(NDVI)를 도출하 고, 버퍼링작업에 의하여 경계선으로 부터의 거리별 NDVI를 산출하여 추이대를 조사하는 방법을 제시하였다. 연구 결과 본 연구대상지의 추이대의 식생은 생물계절(phenology), 인접지역의 토지 이용의 영향을 받는 것이 확인되었으며, 1993년에는 1985년에 비해서 추이대의 폭이 약 2배로 증 대되어 탐방객의 과도한 이용 등으로 인하여 공원경계부 인접한 식생 피해지역의 범위가 확대되 고 있는 것으로 판명되었다.

Terra MODIS NDVI 및 LST 자료와 RNN-LSTM을 활용한 토양수분 산정 (RNN-LSTM Based Soil Moisture Estimation Using Terra MODIS NDVI and LST)

  • 장원진;이용관;이지완;김성준
    • 한국농공학회논문집
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    • 제61권6호
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    • pp.123-132
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    • 2019
  • This study is to estimate the spatial soil moisture using Terra MODIS (Moderate Resolution Imaging Spectroradiometer) satellite data and machine learning technique. Using the 3 years (2015~2017) data of MODIS 16 days composite NDVI (Normalized Difference Vegetation Index) and daily Land Surface Temperature (LST), ground measured precipitation and sunshine hour of KMA (Korea Meteorological Administration), the RDA (Rural Development Administration) 10 cm~30 cm average TDR (Time Domain Reflectometry) measured soil moisture at 78 locations was tested. For daily analysis, the missing values of MODIS LST by clouds were interpolated by conditional merging method using KMA surface temperature observation data, and the 16 days NDVI was linearly interpolated to 1 day interval. By applying the RNN-LSTM (Recurrent Neural Network-Long Short Term Memory) artificial neural network model, 70% of the total period was trained and the rest 30% period was verified. The results showed that the coefficient of determination ($R^2$), Root Mean Square Error (RMSE), and Nash-Sutcliffe Efficiency were 0.78, 2.76%, and 0.75 respectively. In average, the clay soil moisture was estimated well comparing with the other soil types of silt, loam, and sand. This is because the clay has the intrinsic physical property for having narrow range of soil moisture variation between field capacity and wilting point.

위성 데이터 및 기계 학습 기법을 활용한 한반도 임진강 미계측 지역 유출량 예측: MODIS, ASCAT, SDS 데이터를 활용하여 (River Flow Forecasting using Satellite-based Products and Machine Learning Technique over the Ungauged River Flow in Korean Peninsula, Imjin River: Using MODIS, ASCAT, and SDS dataset)

  • 최민하;김형록;;전경수
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2016년도 학술발표회
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    • pp.159-159
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    • 2016
  • 북한 지역에서 시작되어 한반도의 금문댐까지 연결되는 임진강은 북한지역의 유출량 미계측으로 인해 유출량 산출에 많은 어려움이 있어왔다. 본 연구에서는 위성 데이터를 활용하여 미계측 유역의 유출량을 추정 할 수 있는 기법을 제시하였다. Satellite-derived Flow Signal (SDF)는 위성 기반 특정 지역의 유출 정보를 제공하며, JAXA의 GCOM-W1 위성에 탑재된 Advanced Microwave Scanning Radiometer 2(AMSR2) 센서에서 산출된다. 본 연구에서는 SDS 뿐 아니라 유출에 크게 관련이 있는 지표 토양수분 데이터와 식생인자를 임진강 유출 값을 예측하기 위한 입력 값으로 활용하였다. 토양수분 데이터는 Metop-A 위성에 탑재된 Advanced Scatterometer(ASCAT) 센서에서 산출되는 데이터를 활용하였으며, 식생데이터는 Aqua 위성에 탑재된 Moderate Resolution Imaging Spectroradiometer(MODIS) 센서에서 측정되는 Normalized Difference Vegetation Index(NDVI) 데이터를 활용하였다. 추가적으로 SDS, 토양수분, NDVI 데이터는 다양한 lag time으로 약 150여개의 입력데이터로 세분화되었다. 150개의 방대한 입력인자는 Partial Mutual Information(PMI) 방법을 통해 소수 중요 인자들로 간추려져 기계 학습 입력인자로 활용되었다. 기계학습에 있어서는 Support Vector Machine(SVM), Artificial Neural Network (ANN) 기법을 활용하였다. SVM, ANN을 통해 모델화된 유출데이터는 금문댐 유출데이터와 비교/분석되었다. SVM 기법 기반의 유출량은 실제 유출량과 0.73의 상관계수를 보여주었고, ANN 기법 기반의 유출량은 0.66의 상관계수를 결과를 나타내었다. 하지만 SVM 기반 유출데이터는 과소 산정 되는 경향을 보였으며, ANN 기법 기반의 유출량은 과대산정되는 결과가 산출되는 한계점이 있음을 파악할 수 있었다.

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Analysis of Growth Characteristics Using Plant Height and NDVI of Four Waxy Corn Varieties Based on UAV Imagery

  • Jeong, Chan-Hee;Park, Jong-Hwa
    • 대한원격탐사학회지
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    • 제37권4호
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    • pp.733-745
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    • 2021
  • Although waxy corn varieties developed after the 1980s show differences depending on development stages and conditions, studies on the characteristics of waxy corn during the growth stage are rare. The subject of this study was a field survey and unmanned aerial vehicle (UAV) image acquisition of four waxy corn varieties cultivated in Idam-ri, Gammul-myeon, Goesan-gun, Korea. The study was conducted in four stages at intervals of two weeks after planting in 2019. The growth characteristics of each of the four varieties were analyzed using growth curves obtained based on field survey and UAV imagery data. The characteristics of each growth stage of the four varieties of corn, as assessed using normalized difference vegetation index (NDVI) and plant height (P.H.) values, were as follows. The growth model was identified as a model in which three-parameter logistic (3PL) curves reflect the growth characteristics of corn well. In particular, it was found that the variations in growth rate shown by P.H. and NDVI values clearly explain the differences between corn varieties. Among the four cultivars, growth and development first occurred at the early vegetative stage in Daehakchal, followed by Mibaek 2, Miheukchal, and finally Hwanggeummatchal. The variationsin P.H. and NDVI were achieved quickly and earlier in Daehakchal, followed by Mibaek 2, Hwanggeummatchal, and Miheukchal. It was confirmed that these results reflected the characteristics of the fast white-type varieties, while the black-type varieties were delayed, as in a previous study. These results reflect the resistance to lodging that affects the cultivation environment and the response characteristics to nutrients and moisture. It was confirmed that UAV accurately provides growth information that is very useful for analyzing the growth characteristics of each corn variety.

Statistical Analyses of the Flowering Dates of Cherry Blossom and the Peak Dates of Maple Leaves in South Korea Using ASOS and MODIS Data

  • Kim, Geunah;Kang, Jonggu;Youn, Youjeong;Chun, Junghwa;Jang, Keunchang;Won, Myoungsoo;Lee, Yangwon
    • 대한원격탐사학회지
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    • 제38권1호
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    • pp.57-72
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    • 2022
  • In this paper, we aimed to examine the flowering dates of cherry blossom and the peak dates of maple leaves in South Korea, by the combination of temperature observation data from ASOS (Automated Surface Observing System) and NDVI (Normalized Difference Vegetation Index) from MODIS (Moderate Resolution Imaging Spectroradiometer). The more recent years, the faster the flowering dates and the slower the peak dates. This is because of the impacts of climate change with the increase of air temperature in South Korea. By reflecting the climate change, our statistical models could reasonably predict the plant phenology with the CC (Correlation Coefficient) of 0.870 and the MAE (Mean Absolute Error) of 3.3 days for the flowering dates of cherry blossom, and the CC of 0.805 and the MAE of 3.8 for the peak dates of maple leaves. We could suppose a linear relationship between the plant phenology DOY (day of year) and the environmental factors like temperature and NDVI, which should be inspected in more detail. We found that the flowering date of cherry blossom was closely related to the monthly mean temperature of February and March, and the peak date of maple leaves was much associated with the accumulated temperature. Amore sophisticated future work will be required to examine the plant phenology using higher-resolution satellite images and additional meteorological variables like the diurnal temperature range sensitive to plant phenology. Using meteorological grid can help produce the spatially continuous raster maps for plant phenology.