• Title/Summary/Keyword: Temporal trends

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Variation and Trends of Irrigation Requirements of Rice Paddies in Korea

  • Nkomozepi, Temba Darlington;Chung, Sang-Ok
    • Current Research on Agriculture and Life Sciences
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    • v.31 no.4
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    • pp.233-239
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    • 2013
  • Understanding the temporal variability of agricultural parameters derived from historical climate data is important for planning in agriculture. Therefore, this study assessed the magnitude and recent trends of the transpiration ratio defined as the crop water use per harvested yield for the period from 1980 to 2010. The crop water use was estimated using the Food and Agriculture Organization's Crop Wat model for eight administrative provinces in Korea. The temporal trends and spatial uncertainty were explored using the Mann-Kendall and Theil Sen's methods. The regional average rice yield was $6.31t\;ha^{-1}$(range 5.9 to $6.9t\;ha^{-1}$). The results showed that the rice yield in Korea increased by $26kg\;ha^{-1}yr^{-1}$. Overall, the regional average transpiration ratio was $1,298m^3t^{-1}$ (range 1,162 to $1,470m^3t^{-1}$). From 1980 to 2010, the transpiration ratio decreased by $8.2m^3t^{-1}$ (range 2.7 to $14.4m^3t^{-1}$), largely as a result of the increasing yield. The statistical approach to historical data used in this study also provides a basis for simulating the future transpiration ratio.

Temporal Trend Analysis of Contamination using Groundwater Quality Monitoring Network Data (지하수 수질측정망 자료를 활용한 시간적 오염도 추이변화 분석)

  • Bang, Sara;Yoo, Keunje;Park, Joonhong
    • Journal of Korean Society on Water Environment
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    • v.27 no.1
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    • pp.120-128
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    • 2011
  • Korea Groundwater Quality Monitoring Network is a database of annual groundwater quality survey results to prevent groundwater pollution. We estimated contamination index (CI) values for each type of land use, and analyzed temporal trends of pollutant concentration data in the Groundwater Quality Monitoring Network from 2001 to 2009. Among the pollutants considered in the database, the concentrations of nitrate and chloride were higher than their standards. In the case of nitrate, recreation parks, golf courses and general waste dumping regions showed increasing trends according to linear regression analysis, whereas industrial complexes and residential regions of urgan and recreation parks showed increasing trends in the chloride concentration data. According to multiple variable linear regression analysis, EC, pH and topography were major factors influencing CI values. These results suggest that groundwater with a high CI value and increasing trend is vulnerable for potential contamination, which requires more careful groundwater pollution control.

Changes of Phenological Cycles in South Korea

  • Park, Gwang-Yong
    • Proceedings of the KGS Conference
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    • 2003.05a
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    • pp.75-78
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    • 2003
  • A recent rise in mean global temperatures suggests a shift in the temporal cycles of natural seasons. The impacts of warming trends can alter the temporal and spatial distribution of flora and fauna. Especially, phenological cycles are very sensitive to the occurrence of alternation of hot and cold seasons. Phenological calendars reflect the natural seasonality. In more detail, phenological cycles affects agriculture and human health (i.e. the amount of fruit production and allergies), as well as tourism industries like flower fairs or festivals. (omitted)

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Projection of Temporal Trends on Drought Characteristics using the Standardized Precipitation Evapotranspiration Index (SPEI) in South Korea (표준강수증발산지수를 활용한 미래 가뭄특성의 시계열 변화전망)

  • Nam, Won-Ho;Hayes, Michael J.;Wilhite, Donald A.;Svoboda, Mark D.
    • Journal of The Korean Society of Agricultural Engineers
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    • v.57 no.1
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    • pp.37-45
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    • 2015
  • Recent droughts in South Korea have had large economic and environmental impacts across the country. Changes in rainfall and hydrologic patterns due to climate change can potentially increase the occurrence of extreme droughts and affect the future availability of water resources. Therefore, it is necessary to evaluate drought vulnerability for water resources planning and management, and identify the appropriate mitigation actions to conduct a drought risk analysis in the context of climate change. The objective of this study is changes in the temporal trends of drought characteristics in South Korea to examine drought impacts under climate change. First, the changes of drought occurrence were analyzed by applying the Standardized Precipitation Evapotranspiration Index (SPEI) for meteorological data on 54 meteorological stations, and were analyzed for the past 30 years (1981-2010), and Representative Concentration Pathways (RCP) climate change scenarios (2011-2100). Second, the changes on the temporal trends of drought characteristics were performed using run theory, which was used to compare drought duration, severity, and magnitude to allow for quantitative evaluations under past and future climate conditions. These results show the high influence of climate change on drought phenomenon, and will contribute to water resources management and drought countermeasures to climate change.

Temporal Data Mining Framework (시간 데이타마이닝 프레임워크)

  • Lee, Jun-Uk;Lee, Yong-Jun;Ryu, Geun-Ho
    • The KIPS Transactions:PartD
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    • v.9D no.3
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    • pp.365-380
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    • 2002
  • Temporal data mining, the incorporation of temporal semantics to existing data mining techniques, refers to a set of techniques for discovering implicit and useful temporal knowledge from large quantities of temporal data. Temporal knowledge, expressible in the form of rules, is knowledge with temporal semantics and relationships, such as cyclic pattern, calendric pattern, trends, etc. There are many examples of temporal data, including patient histories, purchaser histories, and web log that it can discover useful temporal knowledge from. Many studies on data mining have been pursued and some of them have involved issues of temporal data mining for discovering temporal knowledge from temporal data, such as sequential pattern, similar time sequence, cyclic and temporal association rules, etc. However, all of the works treated data in database at best as data series in chronological order and did not consider temporal semantics and temporal relationships containing data. In order to solve this problem, we propose a theoretical framework for temporal data mining. This paper surveys the work to date and explores the issues involved in temporal data mining. We then define a model for temporal data mining and suggest SQL-like mining language with ability to express the task of temporal mining and show architecture of temporal mining system.

A Hierarchical Bayesian Modeling of Temporal Trends in Return Levels for Extreme Precipitations (한국지역 집중호우에 대한 반환주기의 베이지안 모형 분석)

  • Kim, Yongku
    • The Korean Journal of Applied Statistics
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    • v.28 no.2
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    • pp.137-149
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    • 2015
  • Flood planning needs to recognize trends for extreme precipitation events. Especially, the r-year return level is a common measure for extreme events. In this paper, we present a nonstationary temporal model for precipitation return levels using a hierarchical Bayesian modeling. For intensity, we model annual maximum daily precipitation measured in Korea with a generalized extreme value (GEV). The temporal dependence among the return levels is incorporated to the model for GEV model parameters and a linear model with autoregressive error terms. We apply the proposed model to precipitation data collected from various stations in Korea from 1973 to 2011.

Exploring preventive factors against insufficient antibody positivity rate for foot-and-mouth disease in pig farms in South Korea: a preliminary ecological study

  • Dongwoon Han;Byeongwoo Ahn;Kyung-Duk Min
    • Journal of Veterinary Science
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    • v.25 no.1
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    • pp.13.1-13.9
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    • 2024
  • Background: Foot-and-mouth disease (FMD) is a highly contagious viral disease in livestock that has tremendous economic impact nationally. After multiple FMD outbreaks, the South Korean government implemented a vaccination policy for efficient disease control. However, during active surveillance by quarantine authorities, pig farms have reported an insufficient antibody positivity rate to FMD. Objective: In this study, the spatial and temporal trends of insufficiency among pig farms were analyzed, and the effect of the number of government veterinary officers was explored as a potential preventive factor. Methods: Various data were acquired, including national-level surveillance data for antibody insufficiency from the Korea Animal Health Integrated System, the number of veterinary officers, and the number of local pig farms. Temporal and geographical descriptive analyses were conducted to overview spatial and temporal trends. Additionally, logistic regression models were employed to investigate the association between the number of officers per pig farm with antibody insufficiency. Spatial cluster analysis was conducted to detect spatial clusters. Results: The results showed that the incidence of insufficiency tended to decrease in recent years (odds ratio [OR], 0.803; 95% confidence interval [95% CIs], 0.721-0.893), and regions with a higher density of governmental veterinary officers (OR, 0.942; 95% CIs, 0.918-0.965) were associated with a lower incidence. Conclusions: This study implies that previously conducted national interventions would be effective, and the quality of government-provided veterinary care could play an important role in addressing the insufficient positivity rate of antibodies.

The multi-temporal characteristics of spectral vegetation indices for agricultural land use on RapidEye satellite imagery (농촌지역 토지이용유형별 RapidEye 위성영상의 분광식생지수 시계열 특성)

  • Kim, Hyun-Ok;Yeom, Jong-Min;Kim, Youn-Soo
    • Aerospace Engineering and Technology
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    • v.10 no.1
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    • pp.149-155
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    • 2011
  • A fast-changing agriculture environment induced by global warming and abnormal climate conditions demands scientific systems for monitoring and predicting crop conditions as well as crop yields at national level. Remote sensing opens up a new application field for precision agriculture with the help of commercial use of high resolution optical as well as radar satellite data. In this study, we investigated the multi-temporal spectral characteristics relative to different agricultural land use types in Korea using RapidEye satellite imagery. There were explicit differences between vegetation and non-vegetation land use types. Also, within the vegetation group spectral vegetation indices represented differences in temporal changing trends as to plant species and paddy types.

Urban Spatial Analysis using Multi-temporal KOMPSAT-1 EOC Imagery

  • Kim Youn-Soo;Jeun Gab-Ho;Lee Kwang-Jae;Kim Byung-Kyo
    • Proceedings of the KSRS Conference
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    • 2004.10a
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    • pp.515-517
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    • 2004
  • Although sustainable development of a city should in theory be based on updated spatial information like land cover/use changes, in practice there are no effective tools to get such information. However the development of satellite and sensor technologies has increased the supply of high resolution satellite data, allowing cost-effective, multi-temporal monitoring. Especially KOMPSAT-1(KOrea Multi-Purpose SATellite) acquired a large number of images of the whole Korean peninsula and covering some large cities a number of times. In this study land-use patterns and trends of Daejeon from the year 2000 to the year 2003 will be considered using land use maps which are generated by manual interpretation of multi-temporal KOMPSAT EOC imagery and to show the possibility of using high resolution satellite remote sensing data for urban analysis.

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Trends of Breast Cancer Incidence in Iran During 2004-2008: A Bayesian Space-time Model

  • Jafari-Koshki, Tohid;Schmid, Volker Johann;Mahaki, Behzad
    • Asian Pacific Journal of Cancer Prevention
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    • v.15 no.4
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    • pp.1557-1561
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    • 2014
  • Background: Breast cancer is the most frequently diagnosed cancer in women and estimating its relative risks and trends of incidence at the area-level is helpful for health policy makers. However, traditional methods of estimation which do not take spatial heterogeneity into account suffer from drawbacks and their results may be misleading, as the estimated maps of incidence vary dramatically in neighboring areas. Spatial methods have been proposed to overcome drawbacks of traditional methods by including spatial sources of variation in the model to produce smoother maps. Materials and Methods: In this study we analyzed the breast cancer data in Iran during 2004-2008. We used a method proposed to cover spatial and temporal effects simultaneously and their interactions to study trends of breast cancer incidence in Iran. Results: The results agree with previous studies but provide new information about two main issues regarding the trend of breast cancer in provinces of Iran. First, this model discovered provinces with high relative risks of breast cancer during the 5 years of the study. Second, new information was provided with respect to overall trend trends o. East-Azerbaijan, Golestan, North-Khorasan, and Khorasan-Razavi had the highest increases in rates of breast cancer incidence whilst Tehran, Isfahan, and Yazd had the highest incidence rates during 2004-2008. Conclusions: Using spatial methods can provide more accurate and detailed information about the incidence or prevalence of a disease. These models can specify provinces with different health priorities in terms of needs for therapy and drugs or demands for efficient education, screening, and preventive policy into action.