摘要
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。
Spatialization of attribute data is one of forward issues in the field of GIS While 30year 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 factorsThey were spatialized with multiple variable regression and inverse distance weighted interpolation respectivelyThere was a correlation ratio of R= 098 between temperature and geographical factors including longitude, latitude and altitudeSumming the two spatialized components generated gridbased temperature dataIt can reflect temperature change both at large scale and at small scaleThe method used in this paper can be applied in spatialization of other observed data and it is especially suitable when distribution of observation stations disperses
出处
《地理科学进展》
CSCD
北大核心
2003年第1期87-93,T002,共8页
Progress in Geography
基金
国家科技基础性工作专项资金课题(2001DEA30027-9)
中国科学院知识创新工程项目资助(INF105-SDB-1-18)
