The importance of geostatistics in pyschical geography<p>Fiziki coğrafyada jeoistatistiğin önemi

Authors

  • Olgu Aydın Ankara University
  • Necla Türkoğlu Ankara University
  • İhsan Çiçek Ankara University

Keywords:

Geography variable, Geographical location, Spatial interaction, Physical geography, Geostatistics, Coğrafi Değişken, Coğrafi Mekân, Mekânsal Etkileşim, Fiziki Coğrafya, Jeoistatistik

Abstract

Geostatistic in geographical science is an important method used to consistently determine the spatial variation of an event. Geostatistics look at where the geographical variables take place, i.e. the location, the spatial interaction and the effects of geographical variables affecting the distribution of variables at the location. In short, geostatistics are interested in the spatial organization of the related research subject. Therefore, it has an important place in the geographical study of events that occured in geographical space with the aid of geostatistical techniques. The aim of this study is to provide a general look at the basic concepts and techniques of geostatistics as a part of applications to physical geography studies using a case study.

 

Özet

Coğrafya biliminde jeoistatistik, bir olayın mekânsal değişkenliğini tutarlı bir şekilde ortaya koyabilmek için kullanılan önemli bir yöntemdir. Jeoistatistik, coğrafi değişkenlerin nerede yer aldığı, yani lokasyonu, değişkenlerin mekânsal etkileşimi ve değişkenlerin bulunduğu alanda dağılımlarını belirleyen diğer coğrafi değişkenlerin etkilerini inceler. Kısaca jeoistatistik, ilgili olduğu konuya ait sistemin mekânsal organizasyonu ile ilgilenmektedir. Bu nedenle coğrafi mekânda meydana gelen olayların jeoistatistik teknikleri yardımıyla araştırılması coğrafya çalışmalarında önemli bir yer tutmaktadır. Bu çalışmanın amacı jeoistatistik tekniklerini fiziki coğrafya uygulamaları açısından kısa bir literatür dâhilinde gözden geçirerek, temel kavram ve teknikler açısından genel bir bakış açısı sağlamaktır.

Downloads

Download data is not yet available.

Metrics

Metrics Loading ...

Author Biographies

Olgu Aydın, Ankara University

Ph.D., Asst. Prof., Ankara University, Faculty of Humanities, Department of Geography

Necla Türkoğlu, Ankara University

Ph.D., Assoc. Prof., Ankara University, Faculty of Humanities, Department of Geography

İhsan Çiçek, Ankara University

Ph.D., Prof., Ankara University, Faculty of Humanities, Department of Geography

References

Agterberg, F. (1974). Geomathematics. Mathematical Background and Geo-Science Applications. Elsevier Scientific Publishing Company, New York.

Antonić, O., Kušan, V., Bakran-Petricioli, T., Alegro, A., Gottstein-Matočec, S., Peterel, H., & Tkalčec, Z. (2005). Mapping the habitats of the republic of Croatia (2000-2004), the project overview (in Croatian). Drypis, Journal for Applied Ecology, 1(1), 40.

Atkinson, P.M., & Lloyd, C.D. (1998). Mapping precipitation in Switzerland with ordinary and indicator kriging. Journal of Geographic Information and Decision Analysis, 2(2), 65-76.

Bailey, T.C., & Gatrell, A.C. (1995). Interactive Spatial Data Analysis. Addison Wesley Longman Limited, Harlow, UK.

Berry, B.J.L., & Marble, D.F. (1968). Spatial Analysis: A Reader in Statistical Geography. Englewood Cliffs (N.J), Prentice Hall.

Bhowmik, A.K., & Costa, A.C. (2012). A geostatistical approach to the seasonal precipitation effect on boro rice production in Bangladesh. International Journal of Geosciences, 3, 443-462.

Bivand, R.S.; Pebesma, E.J. & Gómez-Rubio, V. (2008). Applied Spatial Data Analysis with R (Use R), Springer, New York.

Cannavacciuolo, M., Gellido, A., Cluzeau, D., Gascuel, C., & Trehan, P. (1998). A geostatistical approach to the study of earthworm distribution in grassland. Applied Soil Ecology, 9, 345-349.

Caruso, C., & Quarta, F. (1998). Interpolation methods comparison. Computers and Mathematics with Applications, 35(12), 109-126.

Castrignanò, A., Buondonno, A., Odierna, P., Fiorentino, C., & Coppola, E. (2009). Uncertainty assessment of a soil quality index using geostatistics. Environmetrics, 20, 298-311.

Christakos, G. (2005). Random Field Models in Earth Sciences. Academic Press Inc., San Diego.

Chun, Y., & Griffith, D.A. (2013). Spatial Statistics&Geostatistics. SAGE Publications Ltd., London.

Clark, I. (1979). Practical Geostatistics. Elsevier Science&Technology, London.

Cliff, A.D., & Ord, J.K. (1973). Spatial Autocorrelation. Pion Ltd, London, UK.

Cliff, A.D., & Ord, J.K. (1981). Spatial Process: Models and Applications. Pion Ltd, London, UK.

Courault, D., & Monestiez, P. (1999). Spatial interpolation of air temperature according to atmospheric circulation patterns in Southeast France. Intertational Journal of Climatology, 19, 365-378.

Cressie, N. (1993). Statistics for Spatial Data (Revised Edition). John Wiley&Sons, New York.

David, M. (1977). Geostatistical Ore Reserve Estimation. Elsevier Scientific Publishing Company, New York.

Diodato, N. (2005). The influence of topographic co-variables on the spatial variability of precipitation over small regions of complex terrain. International Journal of Climatology, 25, 351-363.

Di Piazza, A., Conti, F.L., Noto, L.V., Viola, F., & La Loggia, G. (2011). Comparative analysis of different techniques for spatial interpolation of rainfall data to create a serially complete monthly time series of precipitation for Sicily, Italy. International Journal of Applied Earth Observation and Geoinformation, 13, 396-408.

Elith, J., & Leathwick, J.R. (2009). Species distribution models: Ecological explanation and prediction across space and time. Annual Review of Ecology, Evolution, and Systematics, 40, 677-697.

Flipo, N., Nicolas, J., Poulin, M., Even, S., & Ledoux, E. (2007). Assessment of nitrate pollution in the Grand Morin aquifers (France): Combined use of geostatistics and physically based modelling. Environmental Pollution, 146, 241-256.

Fotheringham, A., Brunsdon, C., & Charlton, M. (2000). Quantitative Geography Perspectives on Spatial Data Analysis. SAGE, London.

Gambolati, G., & Volpi, G. (1979). A conceptual deterministic analysis of the kriging technique in hydrology. Water Resources Research, 15(3), 625-629.

Goovaerts, P. (1997). Geostatistics for Natural Resources Evaluation. Oxford University Press, UK.

Goovaerts, P. (2000). Geostatistical approaches for incorporating elevation into the spatial interpolation of rainfall. Journal of Hydrology, 228, 113-129.

Haining, R. (1993). Spatial Data Analysis in the Social and Environmental Sciences. Cambridge, Cambridge University Press, UK.

Hansen, H.S. (1997). Avenue-a powerful environment for developing spatial data analysis tools. 12th ESRI European User Conference, 29 Eylül-1 Ekim 1997, Copenhagen, Denmark.

Hengl, T. (2009). A Practical Guide to Geostatisticstical Mapping. Office for Official Publications of the European Communities, Luxembourg.

Henley, S. (1981). Non-Parametric Geostatistics. Halsted Press, New York.

Hohn, M.E. (1999). Geostatistics and Petroleum Geology. Kluwer Academic Publishers, The Netherlands.

Holawe, F., & Dutter, R. (1999). Geostatistical study of precipitation series in Austria: Time and space. Journal of Hydrology, 219, 70-82.

Hossein, E., Jafar, D., Mohammad, J.R., & Chamheidar, H. (2013). Geostatistical evaluation of graoun water quality distribution with GIS (Case study: Mianab-Shoushtar Plain). Bulletin of Environment, Pharmacology and Life Sciences, 3(1), 78-82.

Im, H.K., Rathouz, P.J., & Frederick, J.E. (2009). Space-time modelling of 20 years of dairly air temperature in the Chicago metropolitan region. Environmetrics, 20, 495-511.

Isaaks, E., & Srivastava, R. (1989). An Introduction to Applied Geostatistics. Oxford University Press, New York.

Jang, C.S., Chen, S.K., & Chieh, L.C. (2008). Using multiple-variable indicator kriging to assess groundwater quality for irrigation in the aquifers of the choushui river alluvial fan. Hydrological Processes, 22, 4477-4489.

Journel, A.G., & Huijbregts, Ch. J. (1978). Mining Geostatistics. San Francisco Academic Press, New York.

Journel, A.G. (1983). Non-Parametric estimation of spatial distribution. Mathematical Geology, 15(3), 445-468.

Journel, A.G. (1987). Non-Parametric Geostatistics for Risk and Additional Sampling Assessment. In: Keith, L.H. (ed.), ACS Symposium Series: Principles of Environmental Sampling, (pp. 45-72).

Kalkhan, M.A. (2011). Spatial Statistics: GeoSpatial Information Modelling and Thematic Mapping. CRC Press, USA.

Latimer, A.M., Wu, S., Gelfand, A.E., & Silander, Jr., J.A. (2004). Building statistical models to analyze species distributions. Ecological Applications, 16(1), 33-50.

Leathwick, J.R., Rowe, D., Richardson, J., Elith, J., & Hastiie, T. (2005). Using multivariate adaptive regression splines to predict the distributions of New Zealand’s freshwater diadromous fish. Freshwater Biology, 50, 2034-2052.

Leathwick, J.R., Elith, J., Francis, M.P., Hastie, T., & Taylor, P. (2006). Variation in demersal fish species richness in the oceans surrounding New Zealand: An analysis using boosted regression trees. Marine Ecology Progress Series, 321, 267-281.

Linchtenstern, A. (2013). Kriging Methods in Spatial Statistics. Bachelor’s Thesis, Technische Universität München, Department of Mathematics, Germany.

Lloyd, C.D. (2005). Assessing the effect of integrating elevation data into the estimation of monthly precipitation in Great Britain. Journal of Hydrology, 308, 128-150.

Machiwal, D., & Jha, M.K. (2014). Characterizing rainfall-grandwater dynamics in a hard-rock aquifer system using time series, geographic information system and geostatistical modelling. Hydrological Processes, 28, 2825-2843.

Martínez-Cob, A. (1996). Multivariate geostatistical analysis of evapotranspiration and precipitation in mountainous terrain. Journal of Hydrology, 174(1-2), 19-35.

Maynou, F.X., Sarda, F., & Conan, G.Y. (1998). Assessment of the spatial structure and biomass evaluation of Nephrops norvegicus (L.) populations in the northwestern Mediterranean by geostatistics. ICES Journal of Marine Science, 55, 102-120.

Moral, F.J. (2010). Comparison of different geostatistical approaches to map climate variables: Application to precipitation. International Journal of Climatology, 30(4), 620-631.

Myers, D. (1982). Matrix formulation of co-kriging. Mathematical Geology, 14(3), 249-257.

Myers, D., Begovich, C., Butz, T., & Kane, V. (1982). Variogram models for regional groundwater geochemical data. Mathematical Geology, 14(6), 629-644.

Myers, D. (1983). Estimation of linear combinations and co-kriging. Mathematical Geology, 15(5), 633-637.

Olea, R.A. (1975). Optimum Mapping Techniques Using Regionalized Variable Theory. Kansas Geological Survey, Series on Spatial Analysis, 2, Lawrence, Kansas.

Olea, R.A. (1977). Measuring Spatial Dependence with Semivariograms. Kansas Geological Survey, Series on Spatial Analysis, 3, Lawrence, Kansas.

Olea, R.A. (1982). Optimization of the High Plains Aquifer Observation Network. Kansas, Kansas Geological Survey, Groundwater Series, 7, Kansas.

Olea, R.A. (1994). Fundementals of semivariogram estimation, modeling, and usage: In Yarus, J. M., Chambers, R. L. (eds), Stochastic Modelling and Geostatistics: Principles, Methods, and Case Studies. The American Association of Petroleum Geologist, Computer Applications in Geology. 3, 27-35.

Oliver, M.A., & Webster, R. (2014). A tutorial guide to geostatistics: computing and modeling variograms and kriging. Catena, 113, 56-69.

Pebesma, E.J. (2004). Multivariable geostatistics in S: the gstat package. Computers & Geosciences, 30(7), 683-691.

Petitgas, P. (2001). Geostatistics in fisheries survey design and stock assessment: models, variances and applications. Fish and Fisheries, 2, 231-249.

P´erez-Casta˜neda, R., & Defeo, O. (2004). Spatial distribution and structure along ecological gradients: Penaeid shrimps in a tropical estuarine habitat of Mexico. Marine Ecology Progress Series, 273, 173-185.

Phillips, D.L., Dolph, J., & Marks, D. (1992). A comparison of geostatistical procedures for spatial analysis of precipitation in mountainous terrain. Agricultural and Forest Meteorology, 58(1-2), 119-141.

Phillips, S.J., Anderson, R.P., & Schapire, R.E. (2006). Maximum entropy modeling of species geographic distributions. Ecological Modelling, 190, 231-662.

Pratim, P., Chandrasekharan, A.H., Chakraborty, D., & Kamble, K. (2010). Assessment of groundwater pollution in West Delhi, India using geostatistical approach. Environmental Monitoring Assessment, 167, 599-615.

Roa, R., & Tapia, F. (2000). Cohorts in space: geostatistical mapping of the age structure of the squat lobster Pleuroncodes monodon population off central Chile. Marine Ecology Progress Series, 196, 239-251.

Rohde, R., Muller, R.A., Jacobsen, R., Muller, E., Perlmutter, S., Rosenteld, A., Wurtele, J., Groom, D., & Wickham, C. (2013). A new estimate of the average earth surface land temperature spanning. Geoinformatics&Geostatistics: An Overview, 1(1), 1-7.

Rueda, M. (2001). Spatial distribution of fish species in a tropical estuarine lagoon: A geostatistical appraisal. Marine Ecology Progress Series, 222, 217-226.

Silva, W.M., & Simões, S.J. (2014). Spatial intra-annual variability of precipitation based on geostatistics: A case study for the Paraiba Do Sul Basin, Southeastern Brazil. International Journal of Geosciences, 5, 408-417.

Subyani, A., & Şen, Z. (1989). Geostatistical modelling of the Wasia aquifer in Central Saudi Arabia. Journal of Hydrology, 110(3-4), 295-314.

Şen, Z. (1989). Cumulative semivariogram models of regionalized variables. Mathematical Geology, 21(8), 891-903.

Tobin, C., Nicotina, L, Parlange, M.B., Berne, A., & Rinaldo, A. (2011). Improved interpolation of meteorological forcings for hydrologic applications in a Swiss Alpine region. Journal of Hydrology, 401(1-2), 77-89.

Tobler, W.R. (1970). A computer movie simulating urban growth in the Detroit region. Economic Geography, 46, 234-240.

Tümertekin, E., & Özgüç, N. (2004). Beşeri Coğrafya İnsan Kültür Mekân. Çantay Kitabevi, İstanbul.

Türkoğlu, N.; Çiçek, İ.; Aydın, O.; Duman, N. (2015). Türkiye’de Yıllık Ortalama Toplam Yağış Dağılışının Kriging ve Co-Kriging Yöntemleriyle Analizi. Ankara Üniversitesi Bilimsel Araştırma Projeleri Koordinatörlüğü (BAP), Proje No:15B0759001.

Tveito, O.E, & Forland, E.J. (2010). Mapping temperatures in Norway applying terrain information geostatistics and GIS. Norwegian Journal of Geography, 53, 202-212.

Webster, R. (1985). Quantitative spatial analysis of soil in the field. Advances in Soil Science, 3, 1-70.

Zhang, K., Oswald, E.M., Brown, D.G., Brines, S.J., Gronlund, C.J.; White-Newsome, J.L., Rood, R.B., & Neill, M.S. (2011). Geostatistical exploration of spatial variation of summertime temperatures in the Detroit metropolitan region. Environmental Research, 11, 1046-1053.

Zhou, F., Guo, H.C., Ho, Y.S., & Wu, C.Z. (2007). Scientometric analysis of geostatistics using multivariate methods. Scientometrics, 73(3), 265–279.

Downloads

Published

2015-11-28

How to Cite

Aydın, O., Türkoğlu, N., & Çiçek, İhsan. (2015). The importance of geostatistics in pyschical geography&lt;p&gt;Fiziki coğrafyada jeoistatistiğin önemi. Journal of Human Sciences, 12(2), 1397–1415. Retrieved from https://www.j-humansciences.com/ojs/index.php/IJHS/article/view/3318

Issue

Section

Geography