探索式空间数据分析(ESDA)方法可以很好地揭示区域经济增长特征及其与空间环境的关系,是深入了解和把握区域经济的空间分布和演化规律的有效手段之一。本文基于ESDA方法,利用黄土高原地区284 个县市级行政单元1990、2000 和2007 年3 期的人均GDP数据,分析了黄土高原地区经济增长的空间分布格局和动态演变特征,验证了ESDA方法在揭示社会经济发展空间分异和演变规律方面的作用。分析结果表明：黄土高原地区的人均GDP分布表现出了显著的高值和低值集聚(空间正相关)特征,且其空间分异状况具有一定的稳定性；目前黄土高原地区的经济增长仍以不平衡增长为主,短期内高水平地区高速增长趋势仍将继续,而低水平地区很难实现经济增长的快速提高；黄土高原地区存在着常态化的城市产业集聚推动型和机遇性的资源开发拉动型两种增长类型,后者对人均GDP水平的拉动效应更强,然而却容易造成产业畸形单一,经济增长缺乏可持续性、稳定性和抗干扰性。
Exploratory spatial data analysis (ESDA) can finely reveal the characteristics of economic growth of a region in relation to its geographical environment, and therefore is a powerful tool to help us better understanding the spatial-temporal dynamics of the distributions of economic factors in each region. The study of the spatial distribution of per capita GDP of 284 counties in the Loess Plateau region since 1990 using ESDA proved its role in investigating the rules of distribution and evolution of social or economic development. And several points can be highlighted.
First, ESDA reveals significant positive global and local spatial autocorrelation of per capita GDP in the Loess Plateau region throughout the period 1990-2007.
Second, the analysis of scatter plots and local indicators of spatial association (LISA) over the period indicates that there are four significant regional clusters persisting over time. The first is a significant High-High (HH) type of clustering, located mainly in Inner Mongolia—north Ningxia—north Shaanxi in the Loess Plateau region. The other HH forms of clustering are located in Northwest Henan and Southeast Shanxi. The largest areas of low-low (LL) type of clustering are primarily located in the south of Gansu, the south of Ningxia and east of Gansu.
Third, the comparative analysis of per capita GDP and average growth rates of per capita GDP suggests that the development of per capita GDP in the Loess Plateau region is mainly in a way of polarized growth in the past 20 years. And it is predictable that this trend will persist, and even get stronger in the near future. Until now there are no characteristics of β-convergence detected in the Loess Plateau region.
Finally, the stable spatial patterns in Loess Plateau region indicate two kinds of economic growth modes. One is the normal economic growth pushed by industrial agglomeration, and the other is the opportunistic economic growth pulled by energy/resources exploring. The latter is far more powerful in promoting the level of per capita GDP, but always with problems of singleness of industrial type and lack of stability, sustainability and interference immunity during its working process in pulling economic growth.
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