Choosing the Best Method of Interpolation for the Average Zoning of Annual Temperature in Iran

Document Type : Research Paper

Authors

Abstract

The present study was done through Iran to investigate the best method of spatial interpolation to estimate the annual average temperature. Therefore, the data of 180 synoptic stations in Iran were used. Using different interpolation methods (IDW, GPI, LPI and RBF) with different powers of 1, 2, 3, 4 and 5 and models (Completely Regularized Spline, Inverse Multi-quadric, Multi-quadric, Spline with Tension, and Thin Plate Spline), spatial distribution of the average annual precipitation was investigated to recognize the best method of interpolation. The geo-statistical interpolation methods were kriging and co-kriging. Using some evaluation methods and some indices (RMSE, MBE, MAPE and R), the best method for interpolation was selected. Finally, annual temperature map in GIS was provided by the best method. The results showed that the RBF method has the least RMSE and the most correlation relationship than the others for the interpolating the annual average temperature in Iran (Multi-quadric)

Keywords

References

ثقفیان، بهرام؛ رحیمی بندرآبادی، سیما (1384) مقایسة روش‌های درون‌یابی و برون‌یابی برای برآورد توزیع مکانی مقدار بارندگی سالانه، تحقیقات منابع آب ایران، 2 (1)، صص. 84-74.
حسنی پاک، علی‌اصغر (1377) زمین­آمار (ژئواستاتیستیک)، تهران، دانشگاه تهران.
رحیمی بندرآبادی، سیما؛ ثقفیان، بهرام (1386) برآورد توزیع مکانی بارندگی با کمک تئوری مجموعه‌های فازی، تحقیقات منابع آب ایران، 2 (3)، صص. 38-26.
رضایی پژند، حجت (1380) کاربرد آمار و احتمالات در منابع آب، انتشارات سخن‌گستر، دانشگاه آزاد اسلامی واحد مشهد.
عساکره، حسین (1387) کاربرد روش کریجینگ در درون‌یابی دمای، مطالعه موردی، درون‌یابی دمای 26/14/1376 در ایران‌زمین،  جغرافیا و توسعه،  12، صص. 42-25.
عیوضی، معصومه؛ مساعدی، ابوالفضل (1391) بررسی الگوی گسترش مکانی دمای در سطح استان گلستان با استفاده از مدل‌های قطعی و زمین­آماری، نشریة آب و خاک (علوم و صنایع کشاورزی)، 26 (1)، صص. 64-53.
قهرودی تالی، منیژه (1381) ارزیابی درون‌یابی به روش کریجینگ، پژوهش‌های جغرافیایی، 43، صص. 108-95.
میثاقی، فرهاد؛ محمدی، کوروش (1385) پهنه‌بندی اطّلاعات بارندگی با استفاده از روش­های آمار کلاسیک و
زمین­آمار و مقایسه با شبکه­های عصبی مصنوعی، مجلّۀ علمی کشاورزی، 29، صص. 14-1.
Abdul-Rahman, A., Pilouk, M. (2008) Spatial data modelling for 3D GIS, Springer. USA.
Abramowitz, M., Stegun, I. A. (1965) Handbook of mathematical functions, Dover, New York.
Aguilar, F. J., Agüera, F., Aguilar, M. A., Carvajal, F. (2005) Effects of terrain morphology, sampling density, and interpolation methods on grid DEM accuracy, Photogrammetric Engineering and Remote Sensing, 71, pp. 805–816.
Apaydin, H., Sonmez, K., Yildirim, E. (2004) Spatial interpolation techniques for climate data in the GAP region in Turkey, Climate Research, 28, pp. 31-40.
Campling, P., Gobin, A., Feyen, J. (2001) Temporal and spatial rainfall analysis across a humid tropical catchment, Hydrol Process, 15, pp. 359–375.
Chaplot, V., Darboux, F., Bourennane, H., Leguédois, S., Silvera, N., Phachomphon, K. (2006) Accuracy of interpolation techniques for the derivation of Digital Elevation Models in relation to landform types and data density, Geomorphology, 77, pp. 126-141.
Cheng, K., Lin, sh., Liou, J. J. (2008) Rain-gauge network evaluation and augmentation using geostatistics, Hydrol, Proc, 22, pp. 2554-2564.
Coulibaly, M., Becker S., (2007) Spatial interpolation of annual precipitation in south Africa-comparison and evaluation of methods, International Water Resources Association, 3 (32), pp. 494-502.
Deutsch, C. V., Journel, A. G. (1998) GSLIB: Geostatistical software library and user’s guide (2nd ed.), New York, Oxford University Press.
Diodato, N., Ceccarelli, M. (2005) Interpolation processes using multivariate geostatistics for mapping of climatological precipitation mean in the Sannio Mountains (southern Italy), Earth Surface Proc. Landforms, 30, pp. 259-268.
Dirks, K. N., Hay J. E., Stow C. D., Harris D. (1998) High-resolution studies of rainfall on Norfolk Island. Part II: Interpolation of rainfall data, J Hydrol, 208, pp. 187–193.
Igúzquiza, E. P. (1998) Comparison of geostatistical methods for estimating the areal average climatological rainfall mean using data on precipitation and topography, Inter. J. Climat, 9 (8), pp. 1031– 1047.
Irmak, A., Ranade, P. K. (2008) GIS based estimation of spatial distribution of temperature and evaportanspiration in Nebeaska. Published by the American Society of Agricultural and Biological Engoneers, St. Joseph, Michigan.
Krige, D. G. (1951) A statistical approach to some mine valuations and allied problems at the Witwatersrand, Master's thesis of the University of Witwatersrand.
Li, Z., Zhu, Q., Gold, C. (2004) Digital terrain modeling principles and methology, CRC Press.
Price, D. T., Mckenny, D. W., Nedler, I. A., Hutchinson, M. F., Kesteven, J. K. (2000), A comparison of two statistical methods for interpolation, Canadian monthly mean climate data, Agic. For. Metrol, 101, pp. 81-94.
Prudhomme, C., Redd, D. (1999) Mapping extreme rainfall in a mountainous region using geostatistical techniques: A Case study in Scotland, Inter. J. Climat, 19, pp. 1337-1356.
Rajagopalan B., Lall U. (1998) Locally weighted polynomial estimation of spatial precipitation, J Geogr Inf Decision Anal, 2 (12), pp. 44–51.
Shepard, D. (1968) A two-dimensional interpolation function for irregularly spaced data, In Proc, 23nd National Conference ACM, 517–524.
Tabios G. Q., Salas J. D. (1985) A comparative analysis of techniques for spatial interpolation of precipitation, Water Resour Bull, 3 (21), pp. 365–380.
Wilson, J. P., Gallant, J. C. (2000) Terrain analysis principles and applications, Wiley, New York, 479.
Yan Hong, H., Nix, A., Mike Hutchinson, F., Trevor Booth, H. (2005) Spatial interpolation of monthly mean climate data for china. Int.J.Climatol, 25, pp. 1369-1379.
Yue, T. X., Du, Z. P., Song, D. J., Gong, Y. (2007) A new method of surface modeling and its application to DEM construction, Geomorphology, 91, pp. 161–172.
Zimmerman, D., Pavlik, C., Ruggles, A., Armstrong, M. (1999) An experimental comparison of ordinary and universal Kriging and Inverse Distance Weighting, Mathematical Geology, 31, pp. 375–390.

Files

Share

How to cite

Statistics