基于GIS的定位观测数据空间化

属性数据空间化是当前GIS领域的前沿问题之一。在对中国624个气象站多年平均气温数据空间化过程中,通过使用30秒分辨率的数字高程数据,把气温分解为受经纬度、海拔高度影响的规律性成分和受其它因素影响的非规律性成分两部分,并分别用多元回归和反距离权重内插方法对二者实施空间化,最后将空间化结果进行合成得到基于栅格的中国多年平均气温分布数据。该数据既能反映气温在空间上的宏观变化,又能反映气温在局部地区的微观变化。该方法可供其它类型观测数据空间化、特别是在观测站点稀疏的情况下参考和借鉴。

A Methodology of Spatialization of Observed Data Based on GIS

Spatialization of attribute data is one of forward issues in the field of GIS While 30 year mean temperature data from 624 meteorological stations in China was spatialized, the temperature was divided into regular component, which is affected by longitude, latitude and altitude, and irregular component affected by other local factorsThey were spatialized with multiple variable regression and inverse distance weighted interpolation respectivelyThere was a correlation ratio of R= 098 between temperature and geographical factors including longitude, latitude and altitudeSumming the two spatialized components generated grid based temperature dataIt can reflect temperature change both at large scale and at small scale.