1985-2010年中国省际人口迁移时空格局特征
作者简介:李扬(1982- ),女,山西晋中人,博士,助理研究员,主要研究方向为城镇化与人口流动。E-mail: liy2014@mail.las.ac.cn
收稿日期: 2014-12-04
要求修回日期: 2015-04-06
网络出版日期: 2015-07-12
基金资助
国家自然科学基金项目(41301121)
国家科技攻关计划项目(2012BAJ15B02)
中国科学院重点部署项目(KZZD-EW-06-04)
Spatial-temporal patterns of China's interprovincial migration during 1985-2010
Received date: 2014-12-04
Request revised date: 2015-04-06
Online published: 2015-07-12
Copyright
改革开放以来,伴随着快速城镇化进程的推进以及20世纪80年代户籍制度出现松动,大规模跨区域的人口迁移流动已呈现不可阻挡之势,人口迁移时空格局亦发生着剧烈的变化。目前大多数相关研究只关注某一特定时期的人口迁移,故而人口迁移的时空格局分析显得尤其重要。使用双组分趋势制图法和1985-1990年、1990-1995年、1995-2000年、2000-2005年以及2005-2010年五个时期的人口迁移数据,分析人口迁入、迁出和净迁移的强度及其变化特征。在研究时期内,中国省际人口迁移表现出强烈的空间差异,迁移强度也有大幅的增加。八个主要人口迁入地全部位于东部三个经济快速增长的发展区域(珠江三角洲、长江三角洲和京津冀都市圈)内,而主要的人口来源地都是相对欠发达的中西部省份,这和全国经济发展空间格局完全吻合。双组分趋势地图结果显示南方省份的人口迁移强度及变化趋势都强于北方省份,因此从某种意义上说,在1985-2010年间,南方省份的人口迁移较北方省份更活跃,这可能主要受到南北方自然地理环境以及文化差异的影响。人口迁移时空格局分析结果表明,中国的人口迁移规律正在逐渐形成新特色,东部和西部地区之间的人口流动主要是受到经济因素和区域发展差异的影响,而南方和北方地区的人口迁移活跃程度则主要是由自然地理环境以及文化差异所致。
李扬 , 刘慧 , 汤青 . 1985-2010年中国省际人口迁移时空格局特征[J]. 地理研究, 2015 , 34(6) : 1135 -1148 . DOI: 10.11821/dlyj201506012
Migration plays an increasing role in economy since mobility rose and economic restructuring has proceeded during the last three decades in China. Given the background of most studies focusing on migration in a particular period, it is critical to analyze the spatial-temporal patterns of migration. Using bicomponent trend mapping technique and interprovincial migration data during the periods 1985-1990, 1990-1995, 1995-2000, 2000-2005, and 2005-2010, we analyze net-, in-, out-migration intensity, and their changes over time in this study. Strong spatial variations in migration intensity were found in China's interprovincial migration, and substantial increase in migration intensity was also detected in Eastern China during 1985-2010. Eight key destinations are mostly located within the three rapidly growing economic regions of Eastern China (Pearl River Delta, Yangtze River Delta and Jing-Jin-Ji Metropolitan Area), while most key origins are relatively undeveloped central and western provinces, which are exactly in accordance with economic development patterns in China. The results of bicomponent trend mapping show that most provinces with an increasing trend in in-migration are located in South China, and those with a decreasing trend are in North China. Therefore, in a sense, the migration in the south was more active than that in the north over the last three decades, which might largely be the results of cultural differences between the south and north. These results on spatial-temporal patterns reveal that migration has a strong relationship with regional development, and economic-cultural factors may be of increased relevance to interprovincial migration.
Fig. 1 Two regional zoning systems in China图1 中国的两种区域划分系统 |
Tab. 1 Interprovincial migration in China during 1985-2010表1 1985-2010年中国省际人口迁移量 |
省份 | 1985-1990年 | 1990-1995年 | 1995-2000年 | 2000-2005年 | 2005-2010年 | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
迁入 | 迁出 | 迁入 | 迁出 | 迁入 | 迁出 | 迁入 | 迁出 | 迁入 | 迁出 | |||||
北京 | 672662 | 132148 | 676368 | 114059 | 1989158 | 183537 | 2245358 | 329811 | 3827760 | 405950 | ||||
天津 | 244607 | 72194 | 217404 | 60293 | 517874 | 109768 | 908453 | 106717 | 1497120 | 213360 | ||||
河北 | 520387 | 645704 | 490036 | 405684 | 810432 | 918116 | 611849 | 989509 | 924090 | 2017390 | ||||
山西 | 307026 | 218472 | 154287 | 136559 | 402874 | 351126 | 210189 | 345208 | 498210 | 793680 | ||||
内蒙古 | 254306 | 303129 | 268054 | 242047 | 342621 | 464274 | 394038 | 417057 | 827680 | 647590 | ||||
辽宁 | 541375 | 294996 | 423704 | 191397 | 794547 | 399863 | 673811 | 416453 | 1171870 | 685420 | ||||
吉林 | 237293 | 355532 | 145910 | 287145 | 267326 | 557168 | 217811 | 532453 | 338420 | 853890 | ||||
黑龙江 | 367428 | 607485 | 218475 | 597666 | 317053 | 989284 | 195245 | 1019849 | 321850 | 1463210 | ||||
上海 | 665526 | 132562 | 707147 | 118929 | 2281926 | 171516 | 3025057 | 375094 | 4900490 | 401010 | ||||
江苏 | 791110 | 620478 | 943642 | 437828 | 2008789 | 1306295 | 3290717 | 1327774 | 4887290 | 1893540 | ||||
浙江 | 335886 | 632323 | 453509 | 500847 | 2857611 | 1020842 | 5062189 | 1041132 | 8372910 | 1339400 | ||||
安徽 | 337763 | 533388 | 151267 | 724972 | 329958 | 3045221 | 670642 | 3835774 | 822140 | 5525590 | ||||
福建 | 251044 | 238387 | 335359 | 213897 | 1417095 | 657400 | 1933962 | 802038 | 2449910 | 1113660 | ||||
江西 | 224865 | 293772 | 121851 | 499289 | 248347 | 2821684 | 499170 | 2475849 | 698350 | 3483280 | ||||
山东 | 609432 | 534842 | 513218 | 371691 | 951663 | 924421 | 923472 | 1123019 | 1335580 | 2014990 | ||||
河南 | 477833 | 589626 | 262794 | 720881 | 494632 | 2430484 | 279547 | 3433358 | 429660 | 5430370 | ||||
湖北 | 431121 | 346274 | 263476 | 371691 | 638137 | 2326526 | 501132 | 2714868 | 843470 | 3804200 | ||||
湖南 | 271802 | 528614 | 209417 | 685621 | 381726 | 3432863 | 501057 | 3327849 | 688420 | 4591910 | ||||
广东 | 1257508 | 250494 | 1896636 | 215164 | 12106389 | 461053 | 11996377 | 1715170 | 13874400 | 1612900 | ||||
广西 | 142505 | 588889 | 116494 | 539419 | 302589 | 1934884 | 397208 | 2123094 | 597790 | 2820530 | ||||
海南 | 150101 | 105977 | 101105 | 99351 | 229126 | 136411 | 190792 | 157962 | 337710 | 235900 | ||||
重庆 | - | - | - | - | 471326 | 1161189 | 427170 | 1437434 | 735590 | 1844060 | ||||
四川 | 469876a | 1316049a | 384938a | 1419262a | 620632 | 4626874 | 763245 | 3940755 | 1052830 | 4988090 | ||||
贵州 | 190408 | 312786 | 148053 | 391074 | 275211 | 1296758 | 531094 | 1765660 | 591930 | 2680750 | ||||
云南 | 250264 | 277432 | 201332 | 235326 | 771305 | 419095 | 469132 | 600906 | 620880 | 1089070 | ||||
西藏 | - | 54582 | 34968 | 27273 | 74411 | 37211 | 25434 | 31396 | 91970 | 62490 | ||||
陕西 | 314588 | 362349 | 158865 | 257632 | 445253 | 757179 | 254868 | 826943 | 734020 | 1347490 | ||||
甘肃 | 199196 | 280715 | 135878 | 244580 | 214358 | 590337 | 117736 | 494340 | 260200 | 1046860 | ||||
青海 | 115819 | 102141 | 50065 | 74513 | 80958 | 129632 | 73585 | 85358 | 182540 | 149980 | ||||
宁夏 | 91912 | 56609 | 47533 | 52987 | 135600 | 92021 | 74566 | 67774 | 239030 | 150660 | ||||
新疆 | 341718 | 277412 | 551205 | 145910 | 1202295 | 228189 | 577434 | 181736 | 839800 | 286690 | ||||
总省际人口迁移量 | 11065361 | 10382989 | 33981221 | 38042340 | 54993910 |
Fig. 2 Schematic diagram of bicomponent trend mapping图2 双组分趋势地图使用方法示意图 |
Tab. 2 Five-year internal migration intensities between four countries表2 国内5年人口迁移强度的国际比较 |
国家 | 分区系统 | 区域个数 | 普查年份 | 强度(%) |
---|---|---|---|---|
中国 | 省 | 31 | 2005 | 3.00 |
墨西哥 | 州(state) | 32 | 2005 | 2.70 |
美国 | 州(state) | 51 | 2005 | 8.94 |
澳大利亚 | 区域(SD) | 61 | 2006 | 10.39 |
注:资料来源于Martin等[26]。 3.1 净迁移 |
Fig. 3 Crude net-migration probabilities by province in China during 2005-2010图3 2005-2010年中国省域人口净迁移率 |
Fig. 4 Net-migration probabilities by province during 1985-2010图4 1985-2010年分省区人口净迁移率 |
Fig. 5 Bicomponent trend of net-migration probabilities during 1985-2010图5 1985-2010年人口净迁移率双组分趋势地图 |
Fig. 6 In-migration probabilities by province during 1995-2010图6 1985-2010年分省区人口迁入率 |
Tab. 3 Province types of main destinations during 1985-2010表3 1985-2010年主要人口迁入地省份类型划分 |
省份 | 人口迁入率 (%) | 成熟 | 波动 | 新兴 | ||||
---|---|---|---|---|---|---|---|---|
1985-1990 | 1990-1995 | 1995-2000 | 2000-2005 | 2005-2010 | ||||
上海 | 5.469 | 5.289 | 15.662 | 18.071 | 27.562 | √ | ||
北京 | 7.007 | 6.228 | 16.042 | 16.247 | 24.888 | √ | ||
浙江 | 0.833 | 1.088 | 6.443 | 10.824 | 17.095 | √ | ||
广东 | 2.011 | 2.989 | 17.170 | 13.881 | 15.091 | √ | ||
天津 | 3.027 | 2.459 | 5.434 | 9.075 | 14.354 | √ | ||
江苏 | 0.925 | 1.104 | 4.318 | 5.572 | 6.930 | √ | ||
福建 | 1.273 | 1.394 | 2.810 | 4.424 | 6.538 | √ | ||
新疆 | 2.511 | 3.605 | 6.998 | 3.000 | 4.178 | √ |
Fig. 7 Bicomponent trend of in-migration probabilities during 1985-2010图7 1985-2010年人口迁入率双组分趋势地图 |
Fig. 8 Out-migration probabilities by provinces during 1985-2010图8 1985-2010年分省区人口迁出率 |
Fig. 9 Bicomponent trend of out-migration probabilities, 1985-1990 to 2005-2010图9 1985-2010年人口迁出率双组分趋势地图 |
The authors have declared that no competing interests exist.
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