Spatial Interpolation Methods for Small-Sampled Bangladesh
•Télécharger en tant que PPTX, PDF•
1 j'aime•1,278 vues
Statistical Evaluation of Spatial Interpolation Methods for Small-Sampled Region. A Case Study of Temperature Change Phenomenon in Bangladesh Avit Bhowmik, Pedro Cabral - Institute of Statistics and Information Management, New University of Lisbon
Recommandé
Recommandé
Contenu connexe
Tendances
Tendances (19)
En vedette
En vedette (13)
Similaire à Spatial Interpolation Methods for Small-Sampled Bangladesh
Similaire à Spatial Interpolation Methods for Small-Sampled Bangladesh (20)
Plus de Beniamino Murgante
Plus de Beniamino Murgante (20)
Dernier
Dernier (20)
Spatial Interpolation Methods for Small-Sampled Bangladesh
- 1. Statistical Evaluation of Spatial Interpolation Methods for Small-Sampled Region.A Case Study of Temperature Change Phenomenon in Bangladesh Presented by: Avit Kumar Bhowmik
- 2. Outline
- 4. Aim Identify most appropriate interpolation method.
- 5. Study Area - Bangladesh Total Area : 1,47,570 sq.km. Mean annual temperature has increased during the period of 1895-1980 at 0.310c and the annual mean maximum temperature will increase to 0.40c and 0.730c by the year of 2050 and 2100 respectively. Small Sample Size – 34 Meteorological Stations.
- 6. Objectives Describe overall and station specific Average, Maximum and Minimum temperature trend. Interpolate trend values obtained from trend analysis using Spline, IDW and Ordinary Kriging. Evaluate interpolation results using Univariate and Willmott Statistical method.thus identifying the most appropriate interpolation method.
- 8. Trend Analysis y= a + bx Trend Value, Goodness to fit or Co-efficient of Significance,
- 9. Trend Analysis - Results Maximum Temperature Average Temperature Minimum Temperature
- 10. Trend Analysis - Results
- 12. Variograms Lag Number = 10 Lag size = 3 Average Temperature Range = 8 Maximum Temperature Range = 7 Minimum Temperature Range = 3
- 17. Univariate Statistical Analysis Mean Bias Error (MBE) Standard Deviation of Observed (SDo) Standard Deviation of Estimated (SDe)
- 18. Univariate Statistical Analysis - Results
- 19. Univariate Statistical Analysis - Results
- 20. Univariate Statistical Analysis - Results
- 21. Evaluation of Univariate Statistical Analysis Estimated Temperature Change Observed Temperature Change Average Temperature
- 22. Evaluation of Univariate Statistical Analysis Estimated Temperature Change Observed Temperature Change Maximum Temperature
- 23. Evaluation of Univariate Statistical Analysis Estimated Temperature Change Observed Temperature Change Minimum Temperature
- 24. Willmott (1984) Statistical Analysis
- 25. Willmott (1984) Statistical Analysis - Results Average Temperature Change
- 26. Willmott (1984) Statistical Analysis - Results Maximum Temperature Change
- 27. Willmott (1984) Statistical Analysis - Results Minimum Temperature Change
- 29. Results
- 30. Major Findings Not only Mean Bias Error, but Root Mean Square Error has significant Influence in determining the best Spatial Interpolation Method. The best approach is to look for Error in the Errors.
- 31. Discussion Standard Errors Measured Values
- 32. Thanks for your Attention Questions or Comments