东北地区交通优势度演变格局及影响机制

doi:10.11821/dlxb202102014

Abstract

Abstract:

Traffic facilities are important resources for the future sustainable development of old industrial areas. It is of great practical significance to evaluate and study the spatiotemporal differentiation laws and mechanisms of traffic dominance. A comprehensive evaluation method based on traffic network density, traffic trunk line influence degree, and location dominance was constructed to measure traffic dominance. Taking Northeast China as the case study, the influencing factors and mechanisms of the overall pattern of traffic dominance were analyzed through network analysis, multivariable linear regression and geographic weighted regression. The results show that: (1) The overall traffic dominance of Northeast China is on the rise, and its spatial distribution pattern takes Harbin-Dalian line as the axis and presents a "core-periphery" structure. (2) The spatial differentiation of the overall traffic dominance of the study area is obvious. Most of the high value areas are concentrated along the high-speed railways, while the low value areas are mainly distributed in the east of Inner Mongolia and the north of Heilongjiang. The spatial difference is increasing gradually. (3) The fast traffic mode contributes a lot to the traffic dominance of Northeast China, and the influence of population carrying capacity on the spatiotemporal differentiation of traffic dominance is gradually strengthened. Expanding the traffic trunk lines and increasing the number of traffic hubs will help to improve the traffic dominance of Northeast China.

Key words: traffic dominance, location dominance, traffic trunk line influence degree, traffic network density, Northeast China

SUN Hongri, LIU Yanjun, ZHOU Guolei. The spatiotemporal differentiation and mechanisms of traffic dominance in Northeast China[J].Acta Geographica Sinica, 2021, 76(2): 444-458.

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数据类型	数据来源	说明
国道/省道/高速公路/普通铁路/县道	国家地理信息局	-
2010—2016年高速铁路	国家地理信息局	高速铁路线路
地形起伏度	地理空间数据云(http://www.gscloud.cn)	根据GDEMDEM 30 m分辨率数字高程数据提取东北地区DEM,并重采样为100 m分辨率,分区统计像元后取平均值作为该地区的高程。
建设用地面积	中国科学院资源环境科学数据中心(http://www.resdc.cn)	根据土地利用数据提取东北地区建设用地类型,将其重分类后分区统计各县域单元的建设用地面积。
社会经济指标	《辽宁统计年鉴》 (2011年、2017年) 《黑龙江统计年鉴》 (2011年、2017年) 《吉林统计年鉴》 (2011年、2017年) 《内蒙古统计年鉴》 (2011年、2017年) 《中国城市统计年鉴》 (2011年、2017年) 《中国县域统计年鉴》 (2011年、2017年)	各县域单元年末总人口、地区生产总值、行政区面积、固定资产投资、财政支出、二三产总产值。

类型	子类型	标准	赋值	类型	子类型	标准	赋值
公路	高速公路	拥有高速公路	2	机场		距枢纽机场50 km以内	1.5
		距高速公路30 km以内	1.5		干线机场	拥有干线机场	1.5
		距高速公路60 km以内	1			距干线机场30 km以内	1
		其他	0			其他	0
	国道公路	拥有国道	0.5		支线机场	拥有支线机场	0.5
	国道公路	其他	0	其他	支线机场		0
铁路	高速铁路	拥有高铁站点	2	港口	主要港口	拥有主要港口	2
		距高铁站点30 km以内	1.5			距主要港口30 km以内	1.5
		距高铁站点60 km以内	1			距主要港口60 km以内	1
		其他	0			其他	0
	普通铁路	拥有普通铁路	0.5		一般港口	拥有一般港口	0.5
	普通铁路	其他	0	其他	一般港口		0
机场	枢纽机场	拥有枢纽机场	2

指标名称	指标性质	指标解释
距最近铁路站点距离(X₁)	负向	对外铁路通达能力
距最近机场距离(X₂)	负向	对外航空通达能力
最短时间交通出行成本(X₃)	负向	交通出行选择效用
行政中心1 h等时圈面积(X₄)	正向	综合陆路交通能力
地均县道拥有量(X₅)	正向	近程联系能力
地均国道、省道、高速公路拥有量(X₆)	正向	中程联系能力
地均铁路拥有量(X₇)	正向	远程联系能力

指标名称	指标性质	指标解释
人口密度(x₁)	正向	人口承载能力
人均GDP(x₂)	正向	经济发展水平
地均固定资产投资(x₃)	正向	地块开发力度
地均财政支出(x₄)	正向	财政支持力度
二三产占比(x₅)	正向	产业结构水平
人均建设用地面积(x₆)	负向	建设开发程度
地形起伏度(x₇)	负向	自然地势地貌

TSC	2010年		2016年
TSC	县域单元数目	人口覆盖度(%)	县域单元数目	人口覆盖度(%)
0~0.50	12	0.74	7	0.56
0.50~1.00	15	1.44	12	0.83
1.00~1.50	82	24.72	44	10.76
1.50~2.00	91	43.62	88	30.95
≥ 2.00	28	29.53	77	56.89

The spatiotemporal differentiation and mechanisms of traffic dominance in Northeast China

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年份	指标名称	回归系数	OLS调整后R²
2010年	最短时间交通出行成本	1.223^***	0.773
	距最近铁路站点距离	0.454^***
	地均县道拥有量	0.650^***
	地均国道、省道、高速公路拥有量	0.569^***
2016年	行政中心1 h等时圈面积	0.869^***	0.691
	地均县道拥有量	1.322^***
	距最近铁路站点距离	0.653^***
	距最近机场距离	0.359^***

年份	指标名称	回归系数	OLS调整后R²
2010	高程	1.095^***	0.521
	人口密度	0.147^***
	二三产占比	0.652^***
	人均建设用地	0.338^***
2016	高程	1.300^***	0.563
	人口密度	0.783^***
	二三产占比	0.608^***
	人均建设用地	0.844^***

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