• Title/Summary/Keyword: Observation Scale

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Lessons from constructing and operating the national ecological observatory network

  • Christopher McKay
    • Journal of Ecology and Environment
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    • v.47 no.4
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    • pp.187-192
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    • 2023
  • The United States (US) National Science Foundation's (NSF's) National Ecological Observatory Network (NEON) is a continental-scale observation facility, constructed and operated by Battelle, that collects long-term ecological data to better understand and forecast how US ecosystems are changing. All data and samples are collected using standardized methods at 81 field sites across the US and are freely and openly available through the NEON data portal, application programming interface (API), and the NEON Biorepository. NSF led a decade-long design process with the research community, including numerous workshops to inform the key features of NEON, culminating in a formal final design review with an expert panel in 2009. The NEON construction phase began in 2012 and was completed in May 2019, when the observatory began the full operations phase. Full operations are defined as all 81 NEON sites completely built and fully operational, with data being collected using instrumented and observational methods. The intent of the NSF is for NEON operations to continue over a 30-year period. Each challenge encountered, problem solved, and risk realized on NEON offers up lessons learned for constructing and operating distributed ecological data collection infrastructure and data networks. NEON's construction phase included offices, labs, towers, aquatic instrumentation, terrestrial sampling plots, permits, development and testing of the instrumentation and associated cyberinfrastructure, and the development of community-supported collection plans. Although colocation of some sites with existing research sites and use of mostly "off the shelf" instrumentation was part of the design, successful completion of the construction phase required the development of new technologies and software for collecting and processing the hundreds of samples and 5.6 billion data records a day produced across NEON. Continued operation of NEON involves reexamining the decisions made in the past and using the input of the scientific community to evolve, upgrade, and improve data collection and resiliency at the field sites. Successes to date include improvements in flexibility and resilience for aquatic infrastructure designs, improved engagement with the scientific community that uses NEON data, and enhanced methods to deal with obsolescence of the instrumentation and infrastructure across the observatory.

Prediction of ocean surface current: Research status, challenges, and opportunities. A review

  • Ittaka Aldini;Adhistya E. Permanasari;Risanuri Hidayat;Andri Ramdhan
    • Ocean Systems Engineering
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    • v.14 no.1
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    • pp.85-99
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    • 2024
  • Ocean surface currents have an essential role in the Earth's climate system and significantly impact the marine ecosystem, weather patterns, and human activities. However, predicting ocean surface currents remains challenging due to the complexity and variability of the oceanic processes involved. This review article provides an overview of the current research status, challenges, and opportunities in the prediction of ocean surface currents. We discuss the various observational and modelling approaches used to study ocean surface currents, including satellite remote sensing, in situ measurements, and numerical models. We also highlight the major challenges facing the prediction of ocean surface currents, such as data assimilation, model-observation integration, and the representation of sub-grid scale processes. In this article, we suggest that future research should focus on developing advanced modeling techniques, such as machine learning, and the integration of multiple observational platforms to improve the accuracy and skill of ocean surface current predictions. We also emphasize the need to address the limitations of observing instruments, such as delays in receiving data, versioning errors, missing data, and undocumented data processing techniques. Improving data availability and quality will be essential for enhancing the accuracy of predictions. The future research should focus on developing methods for effective bias correction, a series of data preprocessing procedures, and utilizing combined models and xAI models to incorporate data from various sources. Advancements in predicting ocean surface currents will benefit various applications such as maritime operations, climate studies, and ecosystem management.

The Influence of the Early Childhood Teacher's Play Teaching Efficacy and Play Sensitivity on Young Children's Play Flow (유아교사의 놀이교수효능감 및 놀이 민감성이 유아의 놀이몰입에 미치는 영향)

  • In-Sook Choi
    • Journal of the Health Care and Life Science
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    • v.11 no.1
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    • pp.49-57
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    • 2023
  • The purpose of this study is to analyze the relationship between early childhood teachers' play teaching efficacy and play sensitivity and children's play immersion, and to investigate the effect of play teaching efficacy and play sensitivity on children's play immersion. To this end, a survey was conducted targeting 359 early childhood teachers working in kindergartens and daycare centers located in J province. The research tools used in this study were 'Efficacy in Play Teaching' and 'Teacher's Play Sensitivity Scale' targeting teachers and 'Infant Play Immersion Test' targeting infants. As a result of the study, first, the correlation between play teaching efficacy and play sensitivity and young children's play immersion showed that there was a positive correlation between all variables other than the transformation of the sense of time among the teacher's play sensitivity sub-factors and play observation and children's play immersion sub-factors. Second, as a result of examining the effect of teacher's play teaching efficacy and play sensitivity on young children's play immersion, it was found to have a partially statistically significant effect.

Sensitivity of Data Assimilation Configuration in WAVEWATCH III applying Ensemble Optimal Interpolation

  • Hye Min Lim;Kyeong Ok Kim;Hanna Kim;Sang Myeong Oh;Young Ho Kim
    • Journal of the Korean earth science society
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    • v.45 no.4
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    • pp.349-362
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    • 2024
  • We aimed to evaluate the effectiveness of ensemble optimal interpolation (EnOI) in improving the analysis of significant wave height (SWH) within wave models using satellite-derived SWH data. Satellite observations revealed higher SWH in mid-latitude regions (30° to 60° in both hemispheres) due to stronger winds, whereas equatorial and coastal areas exhibited lower wave heights, attributed to calmer winds and land interactions. Root mean square error (RMSE) analysis of the control experiment without data assimilation revealed significant discrepancies in high-latitude areas, underscoring the need for enhanced analysis techniques. Data assimilation experiments demonstrated substantial RMSE reductions, particularly in high-latitude regions, underscoring the effectiveness of the technique in enhancing the quality of analysis fields. Sensitivity experiments with varying ensemble sizes showed modest global improvements in analysis fields with larger ensembles. Sensitivity experiments based on different decorrelation length scales demonstrated significant RMSE improvements at larger scales, particularly in the Southern Ocean and Northwest Pacific. However, some areas exhibited slight RMSE increases, suggesting the need for region-specific tuning of assimilation parameters. Reducing the observation error covariance improved analysis quality in certain regions, including the equator, but generally degraded it in others. Rescaling background error covariance (BEC) resulted in overall improvements in analysis fields, though sensitivity to regional variability persisted. These findings underscore the importance of data assimilation, parameter tuning, and BEC rescaling in enhancing the quality and reliability of wave analysis fields, emphasizing the necessity of region-specific adjustments to optimize assimilation performance. These insights are valuable for understanding ocean dynamics, improving navigation, and supporting coastal management practices.

The Effect of Supportive Nursing Care on Depression, Mood and Satisfaction in Military Patients with Low Back Pain (지지간호가 군 요통환자의 우울ㆍ기분ㆍ만족에 미치는 영향)

  • 김정아
    • Journal of Korean Academy of Nursing
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    • v.20 no.3
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    • pp.324-340
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    • 1990
  • Support has always been considered an important nursing concept. However, there is no agreement among nurse researchers as to a conceptual definition of supportive nursing or meaningful supportive behaviors. Clarification of the concept, support in nursing, is necessary to promote communication among nurses on nursing behaviors that are effective in providing support and on understanding the relevant properties and charcteristics of the concept, supportive nursing care. The objectives of the study were : 1. to analyse the concept, support in nursing, in order to provide a definition of supportive nursing care, and 2. to operationalize the definition of supportive nursing care and use it as an experimental nursing intervention for patients with low back pain. The first part of the study used the concept analysis approach developed by Walker and Avant(1983) to define the concept of supportive nursing care. The properties of supportive nursing care, defined by this analysis, included perception of supportive need, reciprocal interaction(Transaction), listening, providing empathy and information related to health, and confirmation of the patient's verbal and non - verbal response. The second part, the experimental part of the study, was done using King's(1970) Interpersonal Theory for Nursing. The concept, supportive nursing care, as defined in the concept analysis was operationalized and used as the experimental intervention. The experiment tested the effectiveness of the independent variable, supportive nursing care on the dependent variables, depression, mood and patient satisfaction, in the patients with low back pain in army hospitals. The instruments used to measure the dependent variables were Zung's(1965) Self- Rating Depression Scale, Ryman and Colleagues'(1974) Mood Questionnaire and LaMonica and Colleagues'(1986) Patient Satisfaction Scale. The experimental design used for this study was a Solomon 4 group experimental design. This design has the strength of allowing for observation of the main effects of supportive nursing care and pretesting, and for observation of the interaction effects of pretesting and supportive nursing care. The design includes one experimental group and three control groups. The Subjects of this study were 150 young male patients with low back pain on Neuro - Surgical Wards in three general army hospitals. There were 35 in the experimental group, 39 in the pre - posttest control group, 36 in the treatment - posttest control group and 40 in the posttest only control group. Supportive nursing care, as operationalized by the researcher according to the concept analysis, was given to the patients in the experimental group and the treatment -posttest control group, individually for 30 minute sessions, every other day for 5 days. Data collection was done using a questionnaire. The data were collected in a pretest one week before the supportive nursing care sessions, a posttest immediately after the sessions and follow- up test one week later. Hypotheses testing was done using 2×2 factorial analysis of variance and Meta analysis(Stouffer's Z method). The results of this study are summarized as follows : 1. Hypothesis Ⅰ, “There will be a difference on depression level between the patients with low back pain who receive supportive nursing care and those who do not receive supportive nursing care”, was supported (F=8.49, p<.05). 2. Hypothesis Ⅱ, “There will be a difference on mood level between the patients with low back pain who receive supportive nursing care and those who to not receive supportive nursing care”, was supported (Z meta=2.17, p<.05). 3. Hypothesis Ⅲ, “There will be a difference on satisfaction level between the patients with low back pain who receive supportive nursing care and those who do not receive supportive nursing care”, was supported (F=13.67, p<.05). 4. ANOVA, done to examine the interaction effect of history and maturation, showed no significant difference on the dependent variables between the observations of the pretest scores of the experimental group, the pretest scores of the pre- posttest control group and the posttest score of the posttest only control group. 5. To test for continuing effect of supportive nursing care, paired t-test was done to compare the scores for the dependent variables at the posttest and at the one week later follow-up test. No significant difference on the scores for the dependent variables was found between the posttest scores and the follow-up test scores for the two groups that received supportive nursing care, the experimental group and the treatment-posttest control group. In conclusion, it was found that in the case of young soldiers with low back pain in army hospitals, their depression level was decreased, their mood state was changed positively and their satisfaction level was increased by receiving supportive nursing care. Further, the effectiveness of the supportive nursing care lasted for at least one week in this study. The significance of this study to nursing is in the analysis of the concept of supportive nursing care and the demonstration of the effectiveness of supportive nursing care as an intervention within the limits of the study.

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A basic research for evaluation of a Home Care Nursing Delivery System (가정간호 서비스 질 평가를 위한 도구개발연구)

  • Kim, Mo-Im;Cho, Won-Jung;Kim, Eui-Sook;Kim, Sung-Kyu;Chang, Soon-Bok;Ryu, Ho-Sihn
    • Journal of Home Health Care Nursing
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    • v.6
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    • pp.33-45
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    • 1999
  • The purpose of this study was to develop a basic framework and criteria for evaluation of quality care provided to patients with the attributes of disease in the home care nursing field, and to provide measurement tools for home health care in the future. The study design was a developmental study for evaluation of hospital-based HCN(home care nursing) in Korea. The study process was as follows: a home care nursing study team of College of Nursing. Yonsei University reviewed the nursing records of 47 patients who were enrolled at Yonsei University Medical Center Home Care Center in March, 1995. Twenty-five patients were insured at that time, were selected from 47 patients receiving home care service for study feasibility with six disease groups; Caesarean Section (C/S), simple nephrectomy, Liver cirrhosis(LC), chronic obstructive pulmonary disease(COPD), Lung cancer or cerebrovascular accident(CVA). In this study, the following items were selected : First step : Preliminary study 1. Criteria and items were selected on the basis of related literature on each disease area. 2. Items were identified by home care nurses. 3. A physician in charge reviewed the criteria and content of selected items. 4. Items were revised through preliminary study offered to both HCN patients and discharged patients from the home care center. Second step : Pretest 1. To verify the content of the items, a pretest was conducted with 18 patients of which there were three patients in each of the six selected disease groups. Third step : Test of reliability and validity of tools 1. Using the collected data from 25 patients with either cis, Simple nephrectomy, LC, COPD, Lung cancer, or CVA. the final items were revised through a panel discussion among experts in medical care who were researchers, doctors, or nurses. 2. Reliability and validity of the completed tool were verified with both inpatients and HCN patients in each of field for researches. The study results are as follows: 1. Standard for discharge with HCN referral The referral standard for home care, which included criteria for discharge with HCN referral and criteria leaving the hospital were established. These were developed through content analysis from the results of an open-ended questionnaire to related doctors concerning characteristic for discharge with HCN referral for each of the disease groups. The final criteria was decided by discussion among the researchers. 2. Instrument for measurement of health statusPatient health status was measured pre and post home care by direct observation and interview with an open-ended questionnaire which consisted of 61 items based on Gorden's nursing diagnosis classification. These included seven items on health knowledge and health management, eight items on nutrition and metabolism, three items on elimination, five items on activity and exercise, seven items on perception and cognition, three items on sleep and rest, three items on self-perception, three items on role and interpersonal relations, five items on sexuality and reproduction, five items on coping and stress, four items on value and religion, three items on family. and three items on facilities and environment. 3. Instrument for measurement of self-care The instrument for self-care measurement was classified with scales according to the attributes of the disease. Each scale measured understanding level and practice level by a Yes or No scale. Understanding level was measured by interview but practice level was measured by both observation and interview. Items for self-care measurement included 14 for patients with a CVA, five for women who had a cis, ten for patients with lung cancer, 12 for patients with COPD, five for patients with a simple nephrectomy, and 11 for patients with LC. 4. Record for follow-up management This included (1) OPD visit sheet, (2) ER visit form, (3) complications problem form, (4) readmission sheet. and (5) visit note for others medical centers which included visit date, reason for visit, patient name, caregivers, sex, age, time and cost required for visit, and traffic expenses, that is, there were open-end items that investigated OPD visits, emergency room visits, the problem and solution of complications, readmissions and visits to other medical institution to measure health problems and expenditures during the follow up period. 5. Instrument to measure patients satisfaction The satisfaction measurement instrument by Reisseer(1975) was referred to for the development of a tool to measure patient home care satisfaction. The instrument was an open-ended questionnaire which consisted of 11 domains; treatment, nursing care, information, time consumption, accessibility, rapidity, treatment skill, service relevance, attitude, satisfaction factors, dissatisfaction factors, overall satisfaction about nursing care, and others. In conclusion, Five evaluation instruments were developed for home care nursing. These were (1)standard for discharge with HCN referral. (2)instrument for measurement of health status, (3)instrument for measurement of self-care. (4)record for follow-up management, and (5)instrument to measure patient satisfaction. Also, the five instruments can be used to evaluate the effectiveness of the service to assure quality. Further research is needed to increase the reliability and validity of instrument through a community-based HCN evaluation.

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Case study on flood water level prediction accuracy of LSTM model according to condition of reference hydrological station combination (참조 수문관측소 구성 조건에 따른 LSTM 모형 홍수위예측 정확도 검토 사례 연구)

  • Lee, Seungho;Kim, Sooyoung;Jung, Jaewon;Yoon, Kwang Seok
    • Journal of Korea Water Resources Association
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    • v.56 no.12
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    • pp.981-992
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    • 2023
  • Due to recent global climate change, the scale of flood damage is increasing as rainfall is concentrated and its intensity increases. Rain on a scale that has not been observed in the past may fall, and long-term rainy seasons that have not been recorded may occur. These damages are also concentrated in ASEAN countries, and many people in ASEAN countries are affected, along with frequent occurrences of flooding due to typhoons and torrential rains. In particular, the Bandung region which is located in the Upper Chitarum River basin in Indonesia has topographical characteristics in the form of a basin, making it very vulnerable to flooding. Accordingly, through the Official Development Assistance (ODA), a flood forecasting and warning system was established for the Upper Citarium River basin in 2017 and is currently in operation. Nevertheless, the Upper Citarium River basin is still exposed to the risk of human and property damage in the event of a flood, so efforts to reduce damage through fast and accurate flood forecasting are continuously needed. Therefore, in this study an artificial intelligence-based river flood water level forecasting model for Dayeu Kolot as a target station was developed by using 10-minute hydrological data from 4 rainfall stations and 1 water level station. Using 10-minute hydrological observation data from 6 stations from January 2017 to January 2021, learning, verification, and testing were performed for lead time such as 0.5, 1, 2, 3, 4, 5 and 6 hour and LSTM was applied as an artificial intelligence algorithm. As a result of the study, good results were shown in model fit and error for all lead times, and as a result of reviewing the prediction accuracy according to the learning dataset conditions, it is expected to be used to build an efficient artificial intelligence-based model as it secures prediction accuracy similar to that of using all observation stations even when there are few reference stations.

Development of KD- Propeller Series using a New Blade Section (새로운 날개단면을 이용한 KD-프로펠러 씨리즈 개발)

  • J.T. Lee;M.C. Kim;J.W. Ahn;H.C. Kim
    • Journal of the Society of Naval Architects of Korea
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    • v.28 no.2
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    • pp.52-68
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    • 1991
  • A new propeller series is developed using the newly developed blade section(KH18 section) which behaves better cavitation characteristics and higher lift-drag ratio at wide range of angle-of-attack. The pitch and camber distributions are disigned in order to have the same radial and chordwise loading distribution with the selected circumferentially averaged wake input. Since the geometries of the series propeller, such as chord length, thickness, skew and rate distribations, are selected by regression of the recent full scale propeller geometric data, the performance prediction of a propeller at preliminary design stage can be mure realistic. Number of blades of the series propellers is 4 and the expanded blade area ratios are 0.3, 0.45, 0.6 and 0.75. Mean pitch ratios are selected as 0.5, 0.65, 0.8, 0.75 and 1.1 for each expanded area ratio. The new propeller series is composed of 20 propellers and is named as KD(KRISO-DAEWOO) propeller series. Propeller open water tests are performed at the experimental towing tank, and the cavitation observation tests and fluctuating pressure measurements are carried out at the cavitation tunnel of KRISO. $B_{P}-\delta$ curves, which can be used to select the optimum propeller diameter at the preliminary design stage, are derived from a regression analysis of the propeller often water test results. The KD-cavitation chart is derived from the cavitation observation test results by choosing the local maximum lift coefficient and the local cavitation number as parameters. The caviy extent of a propeller can be predicted more accurately by using the KD-cavitation chart at a preliminary design stage, since it is derived from the results of the cavitation observation tests in the selected ship's wake, whereas the existing cavitation charts, such as the Burrill's cavitation chart, are derived from the test results in uniform flow.

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An Analysis on the Episodes of Large-scale Transport of Natural Airborne Particles and Anthropogenically Affected Particles from Different Sources in the East Asian Continent in 2008 (2008년 동아시아 대륙으로부터 기원이 다른 먼지와 인위적 오염 입자의 광역적 이동 사례에 대한 분석)

  • Kim, Hak-Sung;Yoon, Ma-Byong;Sohn, Jung-Joo
    • Journal of the Korean earth science society
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    • v.31 no.6
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    • pp.600-607
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    • 2010
  • In 2008, multiple episodes of large-scale transport of natural airborne particles and anthropogenically affected particles from different sources in the East Asian continent were identified in the National Oceanic and Atmospheric Administration (NOAA) satellite RGB-composite images and the mass concentrations of ground level particulate matters. To analyze the aerosol size distribution during the large-scale transport of atmospheric aerosols, both aerosol optical depth (AOD; proportional to the aerosol total loading in the vertical column) and fine aerosol weighting (FW; fractional contribution of fine aerosol to the total AOD) of Moderate resolution Imaging Spectroradiometer (MODIS) aerosol products were used over the East Asian region. The six episodes of massive natural airborne particles were observed at Cheongwon, originating from sandstorms in northern China, Mongolia and the loess plateau of China. The $PM_{10}$ and $PM_{2.5}$ stood at 70% and 16% of the total mass concentration of TSP, respectively. However, the mass concentration of $PM_{2.5}$ among TSP increased as high as 23% in the episode in which they were flowing in by way f the industrial area in east China. In the other five episodes of anthropogenically affected particles that flowed into the Korean Peninsula from east China, the mass concentrations of $PM_{10}$ and $PM_{2.5}$ among TSP reached 82% and 65%, respectively. The average AOD for the large-scale transport of anthropogenically affected particle episodes in the East Asian region was measured at $0.42{\pm}0.17$ compared with AOD ($0.36{\pm}0.13$) for the natural airborne particle episodes. Particularly, the regions covering east China, the Yellow Sea, the Korean Peninsula, and the east Korean sea were characterized by high levels of AOD. The average FW values observed during the event of anthropogenically affected aerosols ($0.63{\pm}0.16$) were moderately higher than those of natural airborne particles ($0.52{\pm}0.13$). This observation suggests that anthropogenically affected particles contribute greatly to the atmospheric aerosols in East Asia.

On Using Near-surface Remote Sensing Observation for Evaluation Gross Primary Productivity and Net Ecosystem CO2 Partitioning (근거리 원격탐사 기법을 이용한 총일차생산량 추정 및 순생태계 CO2 교환량 배분의 정확도 평가에 관하여)

  • Park, Juhan;Kang, Minseok;Cho, Sungsik;Sohn, Seungwon;Kim, Jongho;Kim, Su-Jin;Lim, Jong-Hwan;Kang, Mingu;Shim, Kyo-Moon
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.23 no.4
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    • pp.251-267
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    • 2021
  • Remotely sensed vegetation indices (VIs) are empirically related with gross primary productivity (GPP) in various spatio-temporal scales. The uncertainties in GPP-VI relationship increase with temporal resolution. Uncertainty also exists in the eddy covariance (EC)-based estimation of GPP, arising from the partitioning of the measured net ecosystem CO2 exchange (NEE) into GPP and ecosystem respiration (RE). For two forests and two agricultural sites, we correlated the EC-derived GPP in various time scales with three different near-surface remotely sensed VIs: (1) normalized difference vegetation index (NDVI), (2) enhanced vegetation index (EVI), and (3) near infrared reflectance from vegetation (NIRv) along with NIRvP (i.e., NIRv multiplied by photosynthetically active radiation, PAR). Among the compared VIs, NIRvP showed highest correlation with half-hourly and monthly GPP at all sites. The NIRvP was used to test the reliability of GPP derived by two different NEE partitioning methods: (1) original KoFlux methods (GPPOri) and (2) machine-learning based method (GPPANN). GPPANN showed higher correlation with NIRvP at half-hourly time scale, but there was no difference at daily time scale. The NIRvP-GPP correlation was lower under clear sky conditions due to co-limitation of GPP by other environmental conditions such as air temperature, vapor pressure deficit and soil moisture. However, under cloudy conditions when photosynthesis is mainly limited by radiation, the use of NIRvP was more promising to test the credibility of NEE partitioning methods. Despite the necessity of further analyses, the results suggest that NIRvP can be used as the proxy of GPP at high temporal-scale. However, for the VIs-based GPP estimation with high temporal resolution to be meaningful, complex systems-based analysis methods (related to systems thinking and self-organization that goes beyond the empirical VIs-GPP relationship) should be developed.