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Acta Agronomica Sinica ›› 2019, Vol. 45 ›› Issue (12): 1859-1867.doi: 10.3724/SP.J.1006.2019.94041

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Characteristics and influencing factors of geographical agglomeration of cotton plantation in Xinjiang

Chun-Yue MA1,2,Sawut Mamat1,2,3,*(),Ablet Ershat1,2,Jie YAO4   

  1. 1 College of Resources and Environmental Science, Xinjiang University, Urumqi 830046, Xinjiang, China
    2 Key Laboratory of Oasis Ecology of Ministry of Education, Urumqi 830046, Xinjiang, China
    3 Key Laboratory for Wisdom City and Environmental Modeling, Xinjiang University, Urumqi 830046, Xinjiang, China
    4 Chongqing Yingxi Hengzong Information Technology Co. Ltd, Chongqing 400014, China
  • Received:2019-03-15 Accepted:2019-06-20 Online:2019-12-12 Published:2019-07-16
  • Contact: Sawut Mamat E-mail:korxat@xju.edu.cn
  • Supported by:
    This study was supported by the National Natural Science Foundation of China(41361016);This study was supported by the National Natural Science Foundation of China(41461051)

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Abstract:

Xinjiang is the largest cotton production base in China. The study on the geographical agglomeration characteristics of cotton planting in Xinjiang is of great significance in adjusting and optimizing the agricultural structure distribution of cotton production, increasing farmers’ income, and promoting the sustainable development of cotton. Based on the cotton production data of Xinjiang from 1988 to 2016, we explored the spatial-temporal change characteristics of cotton plantation by Location quotient, Gini coefficient, and spatial autocorrelation analysis, qualitatively and quantitatively analyzed various influence factors on the geographical agglomeration of cotton plantation by spatial panel data model, and revealed the main driving force of cotton planting industry in Xinjiang. The cotton planting area in Xinjiang experienced three stages, including continuous growth (1988-1999), slow decrease (2000-2004) and fluctuating growth (2005-2016). In 2016, the cotton planting area accounted for nearly 3/5 of the total area in China, and its professional agglomeration level was higher than that of other regions in China, with the increasingly strengthened leading position since 1992. The regional characteristics of cotton planting industry in Xinjiang were obvious. The change of cotton area in southern Xinjiang dominated the change of cotton plantation in Xinjiang. The agglomeration level of cotton plantation in Xinjiang showed a trend of slow recovery after a decline in fluctuation since 1988. The high aggregation (H-H) area transferred from Kashgar area to Kuqa and Xinhe in Aksu area, at the same time, the changes of high-low cluster, low-high cluster and low-low cluster were not significant. The main factors promoting the geographical agglomeration of cotton planting in Xinjiang included the proportion of productive land area, cotton comparative income, mechanization level and policy factors.

Key words: cotton plantation, geographical agglomeration, spatio-temporal characteristics, spatial panel data model

Fig. 1

Proportion of cotton areas in the country from 1988 to 2016"

Table 1

Location quotient (Qi) of top five provinces or autonomous region and cities from 1988 to 2016"

年份
Year		 第1 Top 1 第2 Top 2 第3 Top 3 第4 Top 4 第5 Top 5
省、区
Region		 区位商Qi 省、区
Region		 区位商Qi 省、区
Region		 区位商Qi 省、区
Region		 区位商Qi 省、区
Region		 区位商Qi
1988 山东Shandong 3.4 新疆Xinjiang 3.4 河北Hebei 2.8 河南Henan 2.0 江苏Jiangsu 1.9
1992 新疆Xinjiang 4.6 山东Shandong 3.1 河南Henan 2.3 河北Hebei 2.3 江苏Jiangsu 1.8
1996 新疆Xinjiang 8.1 河南Henan 2.6 江苏Jiangsu 2.0 湖北Hubei 2.0 河北Hebei 1.6
2000 新疆Xinjiang 12.1 河南Henan 2.3 山东Shandong 1.9 湖北Hubei 1.6 河北Hebei 1.4
2004 新疆Xinjiang 8.5 天津Tianjin 4.7 山东Shandong 2.7 河北Hebei 2.1 河南Henan 1.9
2008 新疆Xinjiang 10.2 天津Tianjin 4.3 山东Shandong 2.3 河北Hebei 2.2 湖北Hubei 2.0
2012 新疆Xinjiang 11.7 天津Tianjin 4.0 河北Hebei 2.3 湖北Hubei 2.0 安徽Anhui 1.2
2016 新疆Xinjiang 16.6 山东Shandong 1.9 河北Hebei 1.5 天津Tianjin 1.3 湖北Hubei 1.2

Table 2

Cotton plantation areas of top five provinces and cities from 1988 to 2016 (×104 hm2)"

年份
Year		 第1 Top 1 第2 Top 2 第3 Top 3 第4 Top 4 第5 Top 5
省、区
Region		 面积
Area		 省、区
Region		 面积
Area		 省、区
Region		 面积
Area		 省、区
Region		 面积
Area		 省、区
Region		 面积
Area
1988 山东Shandong 141.2 河北Hebei 92.4 河南Henan 89.6 江苏Jiangsu 59.9 湖北Hubei 44.2
1992 山东Shandong 147.7 河南Henan 122.9 河北Hebei 87.7 江苏Jiangsu 66.0 新疆Xinjiang 63.2
1996 河南Henan 95.4 新疆Xinjiang 74.3 山东Shandong 50.9 江苏Jiangsu 47.3 湖北Hubei 44.1
2000 新疆Xinjiang 106.3 河南Henan 79.1 山东Shandong 54.1 河北Hebei 33.0 安徽Anhui 31.0
2004 新疆Xinjiang 112.8 山东Shandong 105.9 河南Henan 95.2 河北Hebei 66.9 江苏Jiangsu 41.0
2008 新疆Xinjiang 166.8 山东Shandong 88.8 河北Hebei 69.0 河南Henan 60.6 湖北Hubei 54.3
2012 新疆Xinjiang 172.1 山东Shandong 69.0 河北Hebei 57.8 湖北Hubei 47.3 安徽Anhui 30.5
2016 新疆Xinjiang 215.5 山东Shandong 46.5 河北Hebei 28.9 湖北Hubei 20.3 安徽Anhui 18.3

Fig. 2

Variation of cotton plantation areas in Xinjiang from 1988 to 2016"

Fig. 3

Changing trend of geographical agglomeration of cotton industry in Xinjiang from 1988 to 2016"

Fig. 4

Global correlation analysis of Xinjiang cotton industry from 1988 to 2016"

Fig. 5

Local spatial auto-correlation of geographical agglomeration in Xinjiang cotton industry (1988-2016) H-H indicates that a high value is surrounded by its adjacent high value, which belongs to high-high aggregation; H-L indicates that a high value is surrounded by its adjacent low value, which belongs to high-low aggregation; L-H indicates that a low value is surrounded by its adjacent high value, which belongs to low-high aggregation; L-L indicates that a low value is surrounded by its adjacent low value, which belongs to low-low aggregation."

Table 3

Assumption of influence factor and variable description"

影响因素
Influence factor		 变量
Variable		 变量说明
Variable description
资源条件
Resource conditions		 生产性土地面积比重
Proportion of productive land area (X1)		 棉花种植面积/土地面积
Cotton plantation areas/land area
人均粮食产量
Per capita grain yield (X2)		 粮食总产量/总人口数
Total grain production/total population
灌溉水平
Irrigation level (X3)		 区域灌溉用水量/耕地面积
Irrigation water consumption/cultivated area
经济和市场因素
Economic and market factors		 人均GDP情况
Per capita GDP (X4)		 区域GDP总量/总人口数
Total regional GDP/total population
棉花比较效益
Comparative benefit of cotton (X5)		 棉花与竞争性作物(粮食)价格比值
The price ratio of cotton to a competitive crop (grain)
技术因素
Technical factors		 机械化水平
Mechanization level (X6)		 农业机械总动力/耕地面积
Total power of agricultural machinery/cultivated area
化肥施用量
Consumption of chemical fertilizers (X7)		 化肥折纯量/耕地面积
Consumption of chemical fertilizers/cultivated area
塑料薄膜使用情况
Consumption of plastic film (X8)		 塑料薄膜使用量/耕地面积
Consumption of plastic film/cultivated area
交通条件和政策因素
Traffic condition and policies		 交通运输网密度
Traffic network density (X9)		 每百平方千米铁路和公路的总里程数
The total mileage of a railroad or highway per 100 square kilometers
政策虚拟变量
Policy dummy variable (X10)

Table 4

Regression results of spatial Durbin panel data model"

变量
Variable		 系数
Coefficient		 直接效应
Direct effect		 间接效应
Indirect effect		 总效应
Total effect
生产性土地面积比重
Proportion of productive land area (X1)		 0.8663*** 0.8852*** 0.3180** 1.2032***
人均粮食产量
Per capita grain yield (X2)		 0.4889** 0.4240** -0.2182* 0.2058*
灌溉水平
Irrigation level (X3)		 0.2631** 0.2136* 0.0116 0.2252*
人均GDP情况
Per capita GDP (X4)		 0.3591* 0.3619** 0.1007 0.4626
棉花比较效益
Comparative benefit of cotton (X5)		 1.0390* 1.0328* 0.3328*** 1.3656***
机械化水平
Mechanization level (X6)		 0.4320** 0.4186** -0.1245* 0.2911**
化肥施用量
Consumption of chemical fertilizers (X7)		 0.0772 0.0639 0.0281 0.0920
塑料薄膜使用情况
Consumption of plastic film (X8)		 0.1092 0.1164 0.0334 0.1498
交通运输网密度
Traffic network density (X9)		 -0.1840* 0.1526 -0.0214 0.1312*
政策虚拟变量
Policy dummy variable (X10)		 0.4798** 0.4173*** 0.1017** 0.5190***

Fig. 6

Influence of various variables on the geographical agglomeration of cotton planting in Xinjiang"

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