基于土地利用和人口密度的中国粮食产量空间化

Spatial distribution of China grain output based on land use and population density

将统计信息运用到地理-生态过程相关研究中,是人类活动与地理-生态过程相结合的重要体现。农业生产统计数据空间化的过程,即是恢复或重构其空间分布特征的一种手段,可以为地理-生态过程研究提供数据支持。该文以人口密度为因变量,以土地利用数据为辅助因子,将省区级粮食产量分布到空间网格上,得到了中国2000年粮食产量1km×1km网格图。通过在省级、地市州级和县级尺度上的检验,表明利用该方法进行粮食产量空间化能够正确地表达粮食产量的空间分布规律,尤其对于主要粮食产区,具有很高的数据重现精度,可以作为农业区相关研究的数据源。但其数据重现的准确性随着尺度的下降而下降。表明在粒度更细的情况下应该考虑更多的影响粮食产量的因子。在今后的研究中,有必要结合更多的因子进行粮食产量的空间化,以提高其数据重构精度。

Applying statistics in geo-ecological process researches is an important manifestation of the combination of human activities and the geo-ecological process. Spatialization of agricultural statistics is a means to restore and reconstruct the spatial features of agricultural statistics. The resulting raster maps can provide data support for a wide range of geo-ecological studies. In support of land use, a regression model was constructed by taking population density as the dependent variable and grain yield per unit of arable land as independent one. The model was then applied to spatially distribute provincial-level grain output statistics, resulting in a 1 km×1 km grid for China＇s grain output in 2000 The validation of the resulting maps by using grain output statistics at provincial, municipal and county administrative units showed that the method can correctly map the spatial distribution of grain output, especially for the major grain producing areas, with a high accuracy of the data reproduction. The results can be used as a data source for geo-ecological studies in agricultural areas. The accuracy of gridded grain output was observed to decline with the downscaling of the administrative region. The paper concluded that a higher accuracy grid would be generated if more ancillary factors associated with grain outputs were incorporated.