Title :
Spatial pattern evolution of per capita share of grain in the counties of Henan province
Author :
Yating Li ; Shaoqi Pan ; Changhong Miao
Author_Institution :
Reserach Center of Yellow River Civilization & Sustainable Dev., Kaifeng, China
Abstract :
Based on the statistical data of 126 counties in Henan province, we described the spatial pattern and driving mechanism of per capita grain possession of Henan since the 1990s through the related analysis of spatial autocorrelation analysis, gravity center model and spatial econometric model. The results show that: first, there is certain spatial relevance on per capita grain possession in Henan. The similar areas cluster in space. And this trend is strengthening as time goes by. LISA cluster map demonstrates that counties with higher per capita grain possession are gathered in the center of north Henan and the intersection of Zhumadian and Xinyang, while the lower per capita grain possession are gathered in the west and southwest of Henan. Second, the per capita grain possession in Henan is imbalanced and the per capita grain possession gravity center moves to the southeast of Henan. Finally, the spatial distribution changing of per capita grain possession is affected positively by the per capita cultivated land, planting structure, history development foundation, and affected negatively by the level of economic development.
Keywords :
agricultural products; econometrics; statistical analysis; Henan province; LISA cluster map; Xinyang; Zhumadian; driving mechanism; economic development level; grain per capita share; gravity center model; history development foundation; north Henan; per capita cultivated land; per capita grain possession gravity center; planting structure; southwest Henan; spatial autocorrelation analysis; spatial distribution; spatial econometric model; spatial pattern evolution; statistical data; west Henan; Analytical models; Cities and towns; Correlation; Data models; Economics; Gravity; Mathematical model; Henan province; evolvement track of gravity center; per capita grain; spatial autocorrelation; spatial patter;
Conference_Titel :
Geoinformatics (GEOINFORMATICS), 2013 21st International Conference on
Conference_Location :
Kaifeng
DOI :
10.1109/Geoinformatics.2013.6626113