Comparison of Four Precipatation Spatial Interpolation Methods in Gansu
LI Yuan-pin
Abstract
LI Yuan-pin
Abstract
Spatial interpolation of climate data is very important to those areas where the meteorological stations are rare and its distribution is unreasonable. Four methods Kriging、IDW、Spline and Trend were used to interpolate precipatation in Gansu province .The results presented that Kriging method was the best one for spatial interpolation .From the spatial distribution of precipation map obtained by Kriging in Gansu province ,we can see that the rainfull increased from southeast to northwest and that in the summer and autumn is much more than that in other seasons.
A significance statement is not available in the OpenAlex record.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
Spatial interpolation of climate data is very important to those areas where the meteorological stations are rare and its distribution is unreasonable. Four methods Kriging、IDW、Spline and Trend were used to interpolate precipatation in Gansu province .The results presented that Kriging method was the best one for spatial interpolation .From the spatial distribution of precipation map obtained by Kriging in Gansu province ,we can see that the rainfull increased from southeast to northwest and that in the summer and autumn is much more than that in other seasons.
Key concepts: Kriging, Spatial distribution, Multivariate interpolation, Interpolation (computer graphics), Spline (mechanical), Distribution (mathematics), Physical geography, Environmental science