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A comparison of spatial interpolation methods to estimate continuous wind speed surfaces using irregularly distributed data from England and Wales

Published on Jun 15, 2008in International Journal of Climatology 3.10
· DOI :10.1002/joc.1583
W. Luo1
Estimated H-index: 1
(Central Science Laboratory),
M. C. Taylor1
Estimated H-index: 1
(Central Science Laboratory),
S. R. Parker1
Estimated H-index: 1
(Central Science Laboratory)
Abstract
Seven methods of spatial interpolation were compared to determine their suitability for estimating daily mean wind speed surfaces, from data recorded at nearly 190 locations across England and Wales. The eventual purpose of producing such surfaces is to help estimate the daily spread of pathogens causing crop diseases as they move across regions. The interpolation techniques included four deterministic and three geostatistical methods. Quantitative assessment of the continuous surfaces showed that there was a large difference between the accuracy of the seven interpolation methods and that the geostatistical methods were superior to deterministic methods. Further analyses, testing the reliability of the results, showed that measurement accuracy, density, distribution and spatial variability had a substantial influence on the accuracy of the interpolation methods. Independent wind speed data from ten other dates were used to confirm the robustness of the best interpolation methods. © Crown copyright 2007. Reproduced with the permission of Her Majesty's Stationery Office. Published by John Wiley & Sons, Ltd.
  • References (33)
  • Citations (137)
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References33
Newest
Published on May 1, 2004in Geoderma 3.74
T. Hengl21
Estimated H-index: 21
(International Institute of Minnesota),
G.B.M. Heuvelink41
Estimated H-index: 41
(Wageningen University and Research Centre),
A. Stein43
Estimated H-index: 43
(International Institute of Minnesota)
A methodological framework for spatial prediction based on regression-kriging is described and compared with ordinary kriging and plain regression. The data are first transformed using logit transformation for target variables and factor analysis for continuous predictors (auxiliary maps). The target variables are then fitted using step-wise regression and residuals interpolated using kriging. A generic visualisation method is used to simultaneously display predictions and associated uncertainty...
596 Citations Source Cite
Published on Jan 1, 2003in Climate Research 1.86
Sergio M. Vicente-Serrano49
Estimated H-index: 49
,
M. Angel Saz-Sánchez1
Estimated H-index: 1
,
José María Cuadrat7
Estimated H-index: 7
This paper analyzes the validity of various precipitation and temperature maps obtained by means of diverse interpolation methods. The study was carried out in an area where geographic differences and spatial climatic diversity are significant (the middle Ebro Valley in the northeast of Spain). Two variables, annual precipitation and temperature, and several interpolation methods were used in the climate mapping: global interpolators (trend surfaces and regression models), local inter- polators ...
220 Citations Source Cite
Published on Jun 1, 2001in Journal of Applied Meteorology
Claire Jarvis12
Estimated H-index: 12
,
Neil Stuart11
Estimated H-index: 11
Abstract In a comparative experiment, the sequence of daily maximum and minimum temperatures for 1976 was interpolated over England and Wales to a resolution of 1 km using partial thin plate splines, ordinary kriging, trend surface, and an automatic inverse-distance-weighted method of interpolation. A “level playing field” for comparing the estimation accuracies was established through the incorporation of a consistent set of guiding variables in all interpolators. Once variables were included t...
148 Citations Source Cite
Published on Mar 12, 2001
R. Allan Reese7
Estimated H-index: 7
(Centre for Environment, Fisheries and Aquaculture Science)
Preface 1 Introduction 2 Basic Statistics 3 Prediction and Interpolation 4 Characterizing Spatial Processes: The Covariance and Variogram 5 Modelling the Variogram 6 Reliability of the Experimental Variogram and Nested Sampling 7 Spectral Analysis 8 Local Estimation or Prediction: Kriging 9 Kriging in the Presence of Trend and Factorial Kriging 10 Cross-Correlation, Coregionalization and Cokriging 11 Disjunctive Kriging 12 Stochastic Simulation (new file) Appendix A Appendix B References Index
1,947 Citations
Published on Mar 1, 2000in Agricultural and Forest Meteorology 4.04
David T. Price16
Estimated H-index: 16
(Canadian Forest Service),
Daniel W. McKenney33
Estimated H-index: 33
(Canadian Forest Service)
+ 2 AuthorsJennifer Kesteven4
Estimated H-index: 4
(Australian National University)
Two methods for elevation-dependent spatial interpolation of climatic data from sparse weather station networks were compared. Thirty-year monthly mean minimum and maximum temperature and precipitation data from regions in western and eastern Canada were interpolated using thin-plate smoothing splines (ANUSPLIN) and a statistical method termed ‘Gradient plus Inverse-Distance-Squared’ (GIDS). Data were withheld from approximately 50 stations in each region and both methods were then used to predi...
245 Citations Source Cite
Published on Feb 1, 2000in Journal of Hydrology 3.73
Pierre Goovaerts40
Estimated H-index: 40
(University of Michigan)
This paper presents three multivariate geostatistical algorithms for incorporating a digital elevation model into the spatial prediction of rainfall: simple kriging with varying local means; kriging with an external drift; and colocated cokriging. The techniques are illustrated using annual and monthly rainfall observations measured at 36 climatic stations in a 5000 km 2 region of Portugal. Cross validation is used to compare the prediction performances of the three geostatistical interpolation ...
953 Citations Source Cite
Published on Nov 1, 1999in Phytopathology 3.04
S. J. Fleischer24
Estimated H-index: 24
,
Paul E. Blom5
Estimated H-index: 5
,
Randy Weisz13
Estimated H-index: 13
ABSTRACT Measuring and understanding spatial variation of pests is a fundamental component of population dynamics. The resulting maps can drive spatially variable pest management, which we define as precision integrated pest management (IPM). Precision IPM has the potential to reduce insecticide use and slow the rate of resistance development because of the creation of temporally dynamic refuges. This approach to IPM requires sampling in which the objective is to measure spatial variation and ma...
73 Citations Source Cite
Published on Jan 1, 1998
Peter A. Burrough26
Estimated H-index: 26
,
Rachael McDonnell12
Estimated H-index: 12
Keywords: information handling ; geostatistics ; fuzzy logic Reference Record created on 2005-06-20, modified on 2016-08-08
2,550 Citations
Published on Jan 1, 1997
Timothy C. Coburn10
Estimated H-index: 10
(Abilene Christian University)
1. Exploratory Data Analysis 2. The Random Functions Model 3. Inference and Modeling 4. Local Estimation: Accounting for a Single Attribute 5. Local Estimation: Accounting for Secondary Information 6. Assessment of Local Uncertainty 7. Assessment of Spatial Uncertainty 8. Summary
3,634 Citations
Published on Dec 1, 1995in Journal of Economic Entomology 1.94
Randall Weisz14
Estimated H-index: 14
,
S. J. Fleischer24
Estimated H-index: 24
,
Zane Smilowitz18
Estimated H-index: 18
We describe a sampling program using sample units that might be feasible for mapping Colorado potato beetle, Leptinotarsa decemlineata (Say), densities for site-specific integrated pest management (IPM), an approach that varies the spatial placement of interventions in relation to the variation in pest density within a field. The influence of 5 interpolation methods (kriging, 4 inverse distance weighted functions, and thin plate spline with tension) on 3 estimators of the error associated with e...
39 Citations Source Cite
Cited By137
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Published on Jul 1, 2019in Computers & Structures 2.89
Jun Shi1
Estimated H-index: 1
,
Kaikai Zheng1
Estimated H-index: 1
+ 2 AuthorsGuangchun Zhou1
Estimated H-index: 1
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Published on Apr 1, 2019in Environmental Science and Pollution Research 2.80
Xiao Han1
Estimated H-index: 1
(Lanzhou University),
Yanlong Guo (Chinese Academy of Sciences)+ 5 AuthorsXiaoxuan Mao6
Estimated H-index: 6
(Lanzhou University)
Lung cancer as one of the major causes of cancer mortality has been demonstrated to be closely related to the ambient atmospheric environment, but little has been done in the synthetic evaluation of the linkage between cancer mortality and combined impact of ambient air pollution and meteorological conditions. The present study determined the environmental suitability for female lung cancer mortality associated with air contaminants and meteorological variables. A novel fuzzy matter–element meth...
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Published on Apr 1, 2019in Energy Conversion and Management 6.38
Antonio Zapata-Sierra6
Estimated H-index: 6
(University of Almería),
Alejandro Cama-Pinto1
Estimated H-index: 1
+ 2 AuthorsFrancisco Manzano-Agugliaro18
Estimated H-index: 18
(University of Almería)
Abstract Long time series of wind data can have data gaps that may lead to errors in the subsequent analyses of the time series. This study proposes using the wavelet transform as a system to verify that a data completion technique is correct and that the data series behaves correctly, enabling the user to infer the expected results. Wind speed data from three weather stations located in southern Europe were used to test the proposed method. The series consist of data measured every 10 min for 1...
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Published on Apr 1, 2019in Renewable & Sustainable Energy Reviews 9.18
Jay Rovisham Singh Doorga2
Estimated H-index: 2
(University of Mauritius),
Kumar R. Dhurmea2
Estimated H-index: 2
+ 1 AuthorsRavindra Boojhawon5
Estimated H-index: 5
(University of Mauritius)
Abstract A new hybrid forecasting tool is developed in this study which makes use of satellite remote sensing data of surface solar irradiation coupled to a Double Exponential Smoothing time series model. The prediction capabilities of the Double Exponential Smoothing model are reported to be higher than the ARMA and NAR-Neural Network. The mean absolute percentage error of this hybrid system is revealed to be the lowest (4.89%) on average for 5 consecutive days-ahead forecasts over the years 20...
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Published on Mar 30, 2019in Hydrological Processes 3.18
Zhihua Zhang1
Estimated H-index: 1
(Northwest University (United States)),
Shifan Deng (Northwest University (United States))+ 2 AuthorsXiaowen Zhang5
Estimated H-index: 5
(Northwest University (United States))
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Published on Feb 20, 2019in Water 2.07
In Colombia, daily maximum multiannual series are one of the main inputs for design streamflow calculation, which requires performing a rainfall frequency analysis that involves several prior steps: (a) requesting the datasets, (b) waiting for the information, (c) reviewing the datasets received for missing or data different from the requested variable, and (d) requesting the information once again if it is not correct. To tackle these setbacks, 318 rain gauges located in the Colombian Caribbean...
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Published on Jan 1, 2019in Global and Planetary Change 3.98
Xiaoyan Wang10
Estimated H-index: 10
(Hohai University),
Tao Yang21
Estimated H-index: 21
(Hohai University)
+ 2 AuthorsPengfei Shi8
Estimated H-index: 8
(Hohai University)
Abstract Rivers originating from the Tianshan Mountains, known collectively as the “water tower of Central Asia”, are a key source of fresh water to the densely populated lowlands. Despite of the significance of water resources, our knowledge on the discharge regime in the alpine regions is limited, due to the paucity of in situ measurements and the complexity of contributing sources including rainfall, snowmelt and glacier-melt. In this study, the streamflow regime for the headwater catchment o...
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Published on Dec 1, 2018in BMC Public Health 2.42
Sebsibe Tadesse6
Estimated H-index: 6
(University of Gondar),
Fikre Enqueselassie1
Estimated H-index: 1
(College of Health Sciences, Bahrain),
Seifu Hagos Gebreyesus4
Estimated H-index: 4
(College of Health Sciences, Bahrain)
Background In low-income countries it is difficult to obtain complete data that show spatial heterogeneity in the risk of tuberculosis within-and-between smaller administrative units. This may contribute to the partial effectiveness of tuberculosis control programs. The aim of this study was to estimate the spatial risk of tuberculosis distribution in Gurage Zone, Southern Ethiopia using limited spatial datasets.
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Published on Nov 1, 2018in Climate Dynamics 3.77
Katja Reinhardt (University of Bayreuth), Cyrus Samimi14
Estimated H-index: 14
(University of Bayreuth)
While climatological data of high spatial resolution are largely available in most developed countries, the network of climatological stations in many other regions of the world still constitutes large gaps. Especially for those regions, interpolation methods are important tools to fill these gaps and to improve the data base indispensible for climatological research. Over the last years, new hybrid methods of machine learning and geostatistics have been developed which provide innovative prospe...
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