Assessment of spatial models for interpolation of elevation in Pakistan

作者：Hussain Ijaz^*; Faisal Muhammad; Shad Muhammad Yousaf; Hussain Tajammal; Ahmed Saeed

来源：International Journal of Global Warming, 2015, 7(3): 409-422.

DOI：10.1504/IJGW.2015.069371

• Bayesian kriging
• elevation
• ordinary kriging
• spatial artificial neural network
• SANN
• Pakistan

Elevation has major impact on the climate change. Interpolation of elevation at any location in Pakistan may be useful for predicting environmental parameters such as precipitation, temperature, humidity and wind speed. The locations with low elevations are more effecting global warming as compared with locations at high elevation. Present study interpolates the amount of elevation at unobserved locations using: 1) model-based ordinary kriging; 2) model-based Bayesian kriging with constant trend; 3) model-based Bayesian kriging with varying trend; 4) spatial artificial neural network. Prediction maps of elevation for complete domain are estimated along with prediction standard deviation. The results of suggested methods are compared with means of leave one take others cross validation method. It is observed from cross validation method that model-based Bayesian kriging with constant trend performs better than the other methods of predicting the amount of elevation in Pakistan.

• 出版日期2015