基于GIS的农业气候资源区域化问题研究——以甘肃省为例

在农业气候资源研究中,站点数据的区域化问题是进行资源优化配置和高效利用的一个重要环节。通过采用逐步回归分析与空间插值相结合的方法,以甘肃省及其相邻省区的112个站点1970~2001年31年的月平均温度和降水数据以及计算得到的月平均太阳辐射和潜在蒸散量为数据源,对甘肃省气候资源进行了区域化。对每种气象要素都采用了两种空间插值方法,并对插值结果运用了绝对验证和相对验证两种方法进行了验证和对比。结果表明:温度残差的平均绝对误差(MAE)是Spline< IDW, 其值分别为:0.744℃和0.754℃,平均相对误差(RME)分别为:9.56%和9.66%。降水的平均绝对误差是Kriging温度>潜在蒸散量>降水,但都达到了较高的精度。

Study on the Zonal Digitization of Agricultural Climate Resources Based on GIS--Case Study of Gansu Province

In research of agricultural climate resources, the zonal digitization of climate data is very important for optimization, collocation and high efficient utilization of agricultural resources. Using 11-year of monthly mean air temperature, precipitation, solar radiation and evapotranspiration potential at 112 station in Gansu province and adjacent regions, we combined the methods of stepwise regression analysis and spatial interpolation to regionalize climate variables in Gansu province. Based on stepwise regression analysis,we chosen the methods of zonal digitization. The two methods of spatial interpolation were applied for every climate variables, and farther the results were validated and contrasted by absolute errors from cross-validation test and relative errors from proportion of mean absolute errors (MAE) and corresponding monthly mean climate variables. The results of mean absolute errors were ranked as Spline air temperature > evapotranspiration potential > precipitation, but the zonal digitization of the four climate variables all achieved good precision.