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Proceedings Paper

A DEM-based partition adjustment for the interpolation of annual cumulative temperature in China
Author(s): Jun Zhao; Fei Li; Haiyue Fu; Ying Tian; Zizhi Hu
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Paper Abstract

The spatial interpolation of meteorological elements has more important application value. The interpolation methods of air temperature data have been wildly applied in the large scale region. It has been paid more attentions that taking altitude as a variable was introduced into the interpolation models so as to improve the interpolation precision of air temperature data. In a large area, it is difficult to find the relationship between annual cumulative temperature and altitude according to the distribution of meteorological stations. Compared whit it dividing the study area, introducing interpolation models modified by DEM in the smaller region, we can availably improve the spatial interpolation precision of the annual cumulative temperature. The result shows that: Applied in the partition study area, inverse distance squared method modified by DEM can reduce complexity of spatial data analysis in the process of annual cumulative temperature interpolation. Partition interpolation methods take into account some factors that affect the interpolation results, such as the spatial distribution imbalance of the meteorological stations, altitude and region difference. The methods are fit for the interpolation analysis of the large-scale region. Compared with the tradition interpolation methods such as Kriging, Inverse distance interpolation method, etc., inverse distance squared method modified by DEM has higher interpolation precision of annual cumulative temperature in China.

Paper Details

Date Published: 25 July 2007
PDF: 11 pages
Proc. SPIE 6753, Geoinformatics 2007: Geospatial Information Science, 67532G (25 July 2007); doi: 10.1117/12.763506
Show Author Affiliations
Jun Zhao, Northwest Normal Univ. (China)
Gansu Agricultural Univ. (China)
Fei Li, Northwest Normal Univ. (China)
Haiyue Fu, Northwest Normal Univ. (China)
Nanjing Univ. (China)
Ying Tian, Northwest Normal Univ. (China)
Zizhi Hu, Gansu Agricultural Univ. (China)


Published in SPIE Proceedings Vol. 6753:
Geoinformatics 2007: Geospatial Information Science

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