• Title/Summary/Keyword: Normalized Growth Index

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Monitoring Onion Growth using UAV NDVI and Meteorological Factors

  • Na, Sang-Il;Park, Chan-Won;So, Kyu-Ho;Park, Jae-Moon;Lee, Kyung-Do
    • Korean Journal of Soil Science and Fertilizer
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    • v.50 no.4
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    • pp.306-317
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    • 2017
  • Unmanned aerial vehicles (UAVs) became popular platforms for the collection of remotely sensed data in the last years. This study deals with the monitoring of multi-temporal onion growth with very high resolution by means of low-cost equipment. The concept of the monitoring was estimation of multi-temporal onion growth using normalized difference vegetation index (NDVI) and meteorological factors. For this study, UAV imagery was taken on the Changnyeong, Hapcheon and Muan regions eight times from early February to late June during the onion growing season. In precision agriculture frequent remote sensing on such scales during the vegetation period provided important spatial information on the crop status. Meanwhile, four plant growth parameters, plant height (P.H.), leaf number (L.N.), plant diameter (P.D.) and fresh weight (F.W.) were measured for about three hundred plants (twenty plants per plot) for each field campaign. Three meteorological factors included average temperature, rainfall and irradiation over an entire onion growth period. The multiple linear regression models were suggested by using stepwise regression in the extraction of independent variables. As a result, $NDVI_{UAV}$ and rainfall in the model explain 88% and 68% of the P.H. and F.W. with a root mean square error (RMSE) of 7.29 cm and 59.47 g, respectively. And $NDVI_{UAV}$ in the model explain 43% of the L.N. with a RMSE of 0.96. These lead to the result that the characteristics of variations in onion growth according to $NDVI_{UAV}$ and other meteorological factors were well reflected in the model.

ANALYSIS OF AN SEIQRVS EPIDEMIC DYNAMICS FOR INFECTIOUS VIRAL DISEASE: QUARANTINE AS A CONTROL STRATEGY

  • RAKESH SINGH TOMAR;JOYDIP DHAR;AJAY KUMAR
    • Journal of applied mathematics & informatics
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    • v.41 no.1
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    • pp.107-121
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    • 2023
  • An epidemic infectious disease model consists of six compartments viz. Susceptible, Exposed, Infected, Quarantine, Recovered, and Virus with nonlinear saturation incidence rate is proposed to know the viral disease dynamics. There exist two biological equilibrium points for the model system. The system's local and global stability is done through Lyapunov's direct method about equilibrium points. The sensitivity analysis has been performed for the basic reproduction number and equilibrium points through the normalized forward sensitivity index. Sensitivity analysis shows that virus growth and quarantine rates are more sensitive parameters. In support of mathematical conclusions, numerical experimentation has been shown.

Observation Test of Field Surface Reflectance Using Vertical Rotating Goniometer on Tarp Surface and Grass (수직 축 회전형 측각기 제작 및 야외 지표면 반사도 관측 시험: 타프와 잔디에서)

  • Moon, Hyun-Dong;Jo, Euni;Kim, Hyunki;Cho, Yuna;Kim, Bo-Kyeong;Ahn, Ho-Yong;Ryu, Jae-Hyun;Cho, Jaeil
    • Korean Journal of Remote Sensing
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    • v.38 no.6_1
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    • pp.1207-1217
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    • 2022
  • Vegetation indices using the reflectance of selected wavelength, associating with the monitoring purpose such as identifying the progress of crop growth, on the vegetation canopy surface is widely used in the digital agriculture technology. However, the surface reflectance anisotropy can distort the true value of vegetation index related to the condition of surface, even though the surface property be unchanged. That causes difficulty to observe accurately crop growth on the monitoring system. In this study, a simple type goniometer was designed to measure the reflectance from the anisotropic surface according to various zeniths and azimuths of sun and viewing sensor in the field. On the tarp like as Lambertian surface, the reflectance of Blue, Green, Red, Near-Infrared band was similar to the tarps' reflectance properties. However, the reflectance was slightly overestimated in the cloudy day. The relative difference values of vegetation indices on grass were overestimated for the forward viewing and underestimated for the backward viewing. In addition, enhanced vegetation index (EVI) showed less sensitive according to the positions of sun and sensor viewing. Field observation with a goniometer will be helpful to understand the anisotropy characteristics on the vegetation surface.

Analysis of the Relationship between Urban Permeable/Impermeable Surfaces and Urban Tree Growth Using GeoXAI (GeoXAI를 활용한 도시 투수/불투수면과 도시수목 생육 관계 분석)

  • Seok Jun Kong;Joon Woo Lee;Geun Han Kim
    • Korean Journal of Remote Sensing
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    • v.39 no.6_1
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    • pp.1437-1449
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    • 2023
  • The purpose of this study is to analyze whether pervious and impervious areas in urban areas affect tree growth. In order to determine the differences in the growth of six species of trees planted simultaneously, the effects of pervious and impervious surfaces on tree growth were analyzed using the Normalized Difference Vegetation Index (NDVI) produced using Sentinel-2 and sub-divided land cover map from the Ministry of Environment. For this purpose, the Geospatial eXplainable Artificial Intelligence(GeoXAI) concept was applied. As a result of the analysis, the explanatory power of the model was found to be the best when considering the area of land cover included in the 10m range for Pinus densiflora, the 20 m range for Zelkova Serrata, Metasequoia glyptostroboides, and Ginkgo biloba, the 30 m range for Platanus occidentalis, and the 40 m range for Yoshino cherry trees. In addition, the wider the pervious area, the more active the growth of trees,showing a positive correlation, and the wider the impervious area, such as nearby artificial ground, showed a negative correlation with tree growth. This shows that surrounding pervious and impervious areas affect the growth of trees and that the scope of influence varies depending on the tree species.

A Bibliometric Study on the KCI Listed Theological Journals (KCI 등재 신학 학술지에 대한 계량서지학적 분석)

  • Yoo, Yeong Jun;Lee, Jae Yun
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.31 no.3
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    • pp.5-27
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    • 2020
  • This study aimed at analyzing the keywords and authors of the KCI listed theological journals and finding the official research performance of Korean theology. This study divided the periods in two according to how duplicate the authors are and found hierarchical clusters by analyzing 92 keywords using the McQuitty method. In analyzing them, the Ward linkage method was selected to prevent the authors from gathering into a small number of clusters. Also, to find how influential the journals were to the keywords, the keywords and the percentage of the journals in them were presented together. The authors were analyzed in terms of deciding the positions of them using normalized performance index representing the number of journals and growth index as a growth tendency. Especially, significant researchers were all reformed theologians in a growth index. In the analysis of the keywords of the KCI journals and the authors, the main subject terms of the Korean theology were related to systematic theology and the New Testament. By analyzing the KCI listed journals as the Korean official citation index, this study has made a difference to the advanced articles analyzing the non-KCI listed theological journals.

Study on the Method of Diagnosing the Individuals Crop Growth Using by Multi-Spectral Images

  • Dongwon Kwon;Jaekyeong Baek;Wangyu Sang;Sungyul Chang;Jung-Il Cho;Ho-young Ban;HyeokJin Bak
    • Proceedings of the Korean Society of Crop Science Conference
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    • 2022.10a
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    • pp.108-108
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    • 2022
  • In this study, multispectral images of wheat according to soil water state were collected, compared, and analyzed to measure the physiological response of crops to environmental stress at the individual level. CMS-V multi-spectral camera(Silios Technologies) was used for image acquisition. The camera lens consists of eight spectral bands between 550nm and 830nm. Light Reflective information collected in each band sensor and stored in digital values, and it is converted into a reflectance for calculating the vegetation index and used. According to the camera manual, the NDVI(Normalized Difference vegetation index) value was calculated using 628 nm and 752 nm bands. Image measurement was conducted under natural light conditions, and reflectance standards(Labsphere) were captured with plants for reflectance calculation. The wheat variety used Gosomil, and the wheat grown in the field was transplanted into a pot after heading date and measured. Three treatments were performed so that the soil volumetric water content of the pot was 13~17%, 20~23%, and 25%, and the growth response of wheat according to each treatment was compared using the NDVI value. In the first measurement after port transplantation, the difference in NDVI value according to treatment was not significant, but in the subsequent measurement, the NDVI value of the treatment with a water content of 13 to 17% was lowest and was the highest at 20 to 23%. The NDVI values decreased compared to the first measurement in all treatment, and the decrease was the largest at 13-17% water content and the smallest at 20-23%. Although the difference in NDVI values could be confirmed, it would be difficult to directly relate it to the water stress of plants, and further research on the response of crops to environmental stress and the analysis of multi-spectral image will be needed.

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Method of Monitoring Forest Vegetation Change based on Change of MODIS NDVI Time Series Pattern (MODIS NDVI 시계열 패턴 변화를 이용한 산림식생변화 모니터링 방법론)

  • Jung, Myung-Hee;Lee, Sang-Hoon;Chang, Eun-Mi;Hong, Sung-Wook
    • Spatial Information Research
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    • v.20 no.4
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    • pp.47-55
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    • 2012
  • Normalized Difference Vegetation Index (NDVI) has been used to measure and monitor plant growth, vegetation cover, and biomass from multispectral satellite data. It is also a valuable index in forest applications, providing forest resource information. In this research, an approach for monitoring forest change using MODIS NDVI time series data is explored. NDVI difference-based approaches for a specific point in time have possible accuracy problems and are lacking in monitoring long-term forest cover change. It means that a multi-time NDVI pattern change needs to be considered. In this study, an efficient methodology to consider long-term NDVI pattern is suggested using a harmonic model. The suggested method reconstructs MODIS NDVI time series data through application of the harmonic model, which corrects missing and erroneous data. Then NDVI pattern is analyzed based on estimated values of the harmonic model. The suggested method was applied to 49 NDVI time series data from Aug. 21, 2009 to Sep. 6, 2011 and its usefulness was shown through an experiment.

Drone Image based Time Series Analysis for the Range of Eradication of Clover in Lawn (드론 영상기반 잔디밭 내 클로버의 퇴치 범위에 대한 시계열 분석)

  • Lee, Yong Chang;Kang, Joon Oh;Oh, Seong Jong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.39 no.4
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    • pp.211-221
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    • 2021
  • The Rabbit grass(Trifolium Repens, call it 'Clover') is a representative harmful plant of lawn, and it starts growing earlier than lawn, forming a water pipe on top of the lawn and hindering the photosynthesis and growth of the lawn. As a result, in competition between lawn and clover, clover territory spreads, but lawn is damaged and dried up. Damage to the affected lawn area will accelerate during the rainy season as well as during the plant's rear stage, spreading the area where soil is exposed. Therefore, the restoration of damaged lawn is causing psychological stress and a lot of economic burden. The purpose of this study is to distinguish clover which is a representative harmful plant on lawn, to identify the distribution of damaged areas due to the spread of clover, and to review of changes in vegetation before and after the eradication of clover. For this purpose, a time series analysis of three vegetation indices calculated based on images of convergence Drone with RGB(Red Green Blue) and BG-NIR(Near Infra Red)sensors was reviewed to identify the separation between lawn and clover for selective eradication, and the distribution of damaged lawn for recovery plan. In particular, examined timeseries changes in the ecology of clover before and after the weed-whacking by manual and brush cutter. And also, the method of distinguishing lawn from clover was explored during the mid-year period of growth of the two plants. This study shows that the time series analysis of the MGRVI(Modified Green-Red Vegetation Index), NDVI(Normalized Difference Vegetation Index), and MSAVI(Modified Soil Adjusted Vegetation Index) indices of drone-based RGB and BG-NIR images according to the growth characteristics between lawn and clover can confirm the availability of change trends after lawn damage and clover eradication.

Evaluation of the Amount of Nitrogen Top Dressing Based on Ground-based Remote Sensing for Leaf Perilla (Perilla frutescens) under the Polytunnel House

  • Kang, Seong-Soo;Sung, Jwa-Kyung;Gong, Hyo-Young;Jung, Hyung-Jin;Kim, Yoo-Hak;Hong, Soon-Dal
    • Korean Journal of Soil Science and Fertilizer
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    • v.49 no.5
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    • pp.598-607
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    • 2016
  • This study was conducted to evaluate the amount of nitrogen (N) top dressing based on the normalized difference vegetation indices (NDVI) by ground based sensors for leaf perilla under the polyethylene house. Experimental design was the randomized complete block design for five N fertilization levels and conventional fertilization with 3 and 4 replications in Gumsan-gun and Milyang-si field, respectively. Dry weight (DW), concentration of N, and amount of N uptake by leaf perilla as well as NDVIs from sensors were measured monthly. Difference of growth characteristics among treatments in Gumsan field was wider than Milyang. SPAD-502 chlorophyll meter reading explained 43.4% of the variability in N content of leaves in Gumsan field at $150^{th}$ day after seedling (DAS) and 45.9% in Milyang at $239^{th}$ DAS. Indexes of red sensor (RNDVI) and amber sensor (ANDVI) at $172^{th}$ day after seedling (DAS) in Gumsan explained 50% and 57% of the variability in N content of leaves. RNDVI and ANDVI at $31^{th}$ DAS in Milyang explained 60% and 65% of the variability in DW of leaves. Based on the relationship between ANDVI and N application rate, ANDVI at $172^{th}$ DAS in Gumsan explained 57% of the variability in N application rate but non significant relationship in Milyang field. Average sufficiency index (SI) calculated from ratio of each measurement index per maximum index of ANDVI at $172^{th}$ DAS in Gumsan explained 73% of the variability in N application rate. Although the relationship between NDVIs and growth characteristics was various upon growing season, SI by NDVIs of ground based remote sensors at top dressing season was thought to be useful index for recommendation of N top dressing rate of leaf perilla.

Prediction of stress intensity factor range for API 5L grade X65 steel by using GPR and MPMR

  • Murthy, A. Ramachandra;Vishnuvardhan, S.;Saravanan, M.;Gandhi, P.
    • Structural Engineering and Mechanics
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    • v.81 no.5
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    • pp.565-574
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    • 2022
  • The infrastructures such as offshore, bridges, power plant, oil and gas piping and aircraft operate in a harsh environment during their service life. Structural integrity of engineering components used in these industries is paramount for the reliability and economics of operation. Two regression models based on the concept of Gaussian process regression (GPR) and Minimax probability machine regression (MPMR) were developed to predict stress intensity factor range (𝚫K). Both GPR and MPMR are in the frame work of probability distribution. Models were developed by using the fatigue crack growth data in MATLAB by appropriately modifying the tools. Fatigue crack growth experiments were carried out on Eccentrically-loaded Single Edge notch Tension (ESE(T)) specimens made of API 5L X65 Grade steel in inert and corrosive environments (2.0% and 3.5% NaCl). The experiments were carried out under constant amplitude cyclic loading with a stress ratio of 0.1 and 5.0 Hz frequency (inert environment), 0.5 Hz frequency (corrosive environment). Crack growth rate (da/dN) and stress intensity factor range (𝚫K) values were evaluated at incremental values of loading cycle and crack length. About 70 to 75% of the data has been used for training and the remaining for validation of the models. It is observed that the predicted SIF range is in good agreement with the corresponding experimental observations. Further, the performance of the models was assessed with several statistical parameters, namely, Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Coefficient of Efficiency (E), Root Mean Square Error to Observation's Standard Deviation Ratio (RSR), Normalized Mean Bias Error (NMBE), Performance Index (ρ) and Variance Account Factor (VAF).