【摘要】 土壤温度栅格数据是很多区域性宏观研究的重要基础,对离散的土壤温度数据进行空间预测分析获取空间上连续的土壤温度数据具有重要意义。本文用我国698个气象站点的年均土壤温度和年均气温数据以及数字高程模型数据,分析不同气象和地形因素对年均土壤温度的影响;根据全国各地可获取数据源的不同,分别用3组不同的影响因素为辅助变量:(1)年均气温;(2)经度、纬度和海拔;(3)年均气温、经度、纬度和海拔,采用回归克里格法预测我国年均土壤温度空间分布。结果表明年均气温、经度、纬度和海拔对年均土壤温度空间变异均有显著影响。土壤温度空间预测结果的准确性检验显示用经度、纬度和海拔预测土壤温度的精度最高,基于年均气温、经度、纬度和海拔预测的稍差,只用年均气温预测的最差。辅助变量数据的精度及其与年均土壤温度的相关性对预测效果的影响较大。更多还原

【Abstract】 Spatial data of soil temperature is one of the basic datasets of many large scale researches,such as the International Geosphere-Biosphere Program and DIVERSITAS.Thus,it is really meaningful to derive spatial continuous data of soil temperature from discrete data using the spatial estimation method.Based on the data of mean annual soil and air temperatures in the period from 1971 to 2000 collected from 698 meteorological stations in China and the data of the digital elevation model of China,analysis was conducted of effects of meteorological and topographic factors on mean annual soil temperature.In light of different sources of data,three groups of affecting factors,that is,1)mean annual air temperature;2)longitude,latitude and elevation;and 3)mean annual air temperature,longitude,latitude and elevation;were designed as auxiliary variable,and the regression kriging method was adopted to predict the spatial patterns of mean annual soil temperatures across the country.Results showed that mean annual air temperature,longitude,latitude and elevation all displayed significant impacts on spatial variation of mean annual soil temperatures.Validation of the results revealed that prediction with auxiliary variable of group 2 was in the lead in accuracy,and followed by that with Group 3 and then with Group 1.Data accuracy of the auxiliary variables and their relativity with mean annual soil temperature would significantly affect precision of the prediction.更多还原