JOURNAL OF NATURAL RESOURCES ›› 2019, Vol. 34 ›› Issue (10): 2087-2102.doi: 10.31497/zrzyxb.20191006
• Theory and Concept • Previous Articles Next Articles
Received:
2019-04-28
Revised:
2019-07-25
Online:
2019-10-28
Published:
2019-10-28
ZHU Jie. The model of population urbanization in urban land spatial planning based on multi-source data fusion: A case study of Yangzhou city[J].JOURNAL OF NATURAL RESOURCES, 2019, 34(10): 2087-2102.
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Table 1
Comparison of advantages and disadvantages of traditional data and big data in population flow analysis"
属性 | 人口普查或抽样序列 | 手机信令 | |
---|---|---|---|
时间跨度 | 长期趋势:普查10年一次,1%抽样调查5年一次 | 短期特点:一周、一日分析居多 | |
空间尺度 | 国家 | 全国人口总体发展特征,省区人口流动特征 | 数据量巨大,不适宜分析 |
区域 | 人口流动数据无法分解到地级市和以下层级 | 城市群/都市圈尺度可细分到县市 | |
城市 | 城市内部可细分到乡镇、街道,乃至村庄 | ||
数据结构 | 迁移人口属性数据丰富,涵盖年龄结构、职业构成、受教育程度、迁移原因等;但只有外来人口,缺乏外出人口 | 因数据保密性等因素,不含属性数据;但能够辨识外来、外出人口 |
Table 4
The headquarters-branch linkage of prefecture-level cities in Jiangsu under the classification of whole industry and new economy"
城市名称 | 全产业门类 | 新经济门类 | 新经济分类下关联度提升情况/% | |||
---|---|---|---|---|---|---|
关联度 | 比例/% | 关联度 | 比例/% | |||
南京 | 39551 | 20.42 | 6468 | 17.91 | -2.51 | |
苏州 | 28313 | 14.62 | 4594 | 12.72 | -1.89 | |
无锡 | 18762 | 9.69 | 4051 | 11.22 | 1.53 | |
南通 | 16304 | 8.42 | 2570 | 7.12 | -1.30 | |
盐城 | 13927 | 7.19 | 2360 | 6.54 | -0.65 | |
徐州 | 13685 | 7.07 | 2661 | 7.37 | 0.30 | |
常州 | 12329 | 6.36 | 2018 | 5.59 | -0.78 | |
扬州 | 11999 | 6.19 | 2068 | 5.73 | -0.47 | |
淮安 | 9104 | 4.70 | 2038 | 5.64 | 0.94 | |
泰州 | 8759 | 4.52 | 2068 | 5.73 | 1.21 | |
宿迁 | 7566 | 3.91 | 1780 | 4.93 | 1.02 | |
镇江 | 7406 | 3.82 | 1947 | 5.39 | 1.57 | |
连云港 | 5996 | 3.10 | 1486 | 4.12 | 1.02 |
Table 5
The coupling degree between enterprises interlocking network and migration from prefecture-level cities to Yangzhou in Yangtze River Delta"
城市名称 | 标准化后企业 关联网络强度Y1 | 标准化后人口 通勤强度Y2 | 耦合度C |
---|---|---|---|
南京市 | 1.00 | 1.00 | 1.000 |
合肥市 | 0.10 | 0.10 | 1.000 |
连云港市 | 0.11 | 0.10 | 0.999 |
盐城市 | 0.21 | 0.23 | 0.999 |
杭州市 | 0.13 | 0.10 | 0.993 |
徐州市 | 0.11 | 0.15 | 0.988 |
上海市 | 0.58 | 0.39 | 0.982 |
常州市 | 0.17 | 0.26 | 0.975 |
宿迁市 | 0.11 | 0.18 | 0.967 |
南通市 | 0.15 | 0.26 | 0.966 |
无锡市 | 0.18 | 0.34 | 0.951 |
苏州市 | 0.24 | 0.46 | 0.949 |
滁州市 | 0.10 | 0.23 | 0.918 |
淮安市 | 0.13 | 0.38 | 0.876 |
镇江市 | 0.15 | 0.51 | 0.838 |
泰州市 | 0.23 | 0.90 | 0.807 |
平均值 | 0.950 |
Table 6
The coupling degree between enterprises interlocking network and migration among towns in Yangzhou"
总部所在地 | 分支所在地 | 标准化后企业关联网络强度Y1 | 标准化后人口通勤强度Y2 | 耦合度C |
---|---|---|---|---|
东关街道 | 丁沟镇 | 0.24 | 0.25 | 1.000 |
真州镇 | 新集镇 | 0.12 | 0.14 | 0.998 |
东关街道 | 公道镇 | 0.12 | 0.10 | 0.997 |
东关街道 | 真武镇 | 0.23 | 0.28 | 0.995 |
邵伯镇 | 东关街道 | 0.69 | 0.87 | 0.993 |
东关街道 | 邵伯镇 | 0.42 | 0.60 | 0.984 |
东关街道 | 樊川镇 | 0.29 | 0.19 | 0.980 |
东关街道 | 李典镇 | 0.14 | 0.22 | 0.977 |
马棚街道 | 高邮街道 | 0.16 | 0.25 | 0.970 |
杨寿镇 | 东关街道 | 0.13 | 0.23 | 0.964 |
安宜镇 | 泾河镇 | 0.20 | 0.38 | 0.953 |
东关街道 | 真州镇 | 1.00 | 0.53 | 0.952 |
安宜镇 | 氾水镇 | 0.20 | 0.39 | 0.949 |
安宜镇 | 射阳湖镇 | 0.38 | 0.19 | 0.947 |
东关街道 | 郭村镇 | 0.36 | 0.18 | 0.946 |
东关街道 | 安宜镇 | 0.60 | 0.30 | 0.942 |
东关街道 | 吴桥镇 | 0.12 | 0.24 | 0.940 |
东关街道 | 小纪镇 | 0.49 | 0.22 | 0.928 |
小纪镇 | 东关街道 | 0.10 | 0.24 | 0.911 |
安宜镇 | 山阳镇 | 0.24 | 0.58 | 0.911 |
安宜镇 | 望直港镇 | 0.26 | 0.62 | 0.910 |
东关街道 | 头桥镇 | 0.15 | 0.37 | 0.904 |
真州镇 | 马集镇 | 0.20 | 0.65 | 0.851 |
东关街道 | 丁伙镇 | 0.16 | 0.53 | 0.850 |
东关街道 | 甘泉街道 | 0.12 | 0.44 | 0.826 |
东关街道 | 宜陵镇 | 0.21 | 0.76 | 0.825 |
东关街道 | 高邮街道 | 0.98 | 0.26 | 0.818 |
高邮街道 | 卸甲镇 | 0.12 | 0.47 | 0.813 |
高邮街道 | 龙虬镇 | 0.11 | 0.47 | 0.778 |
真州镇 | 东关街道 | 0.17 | 0.87 | 0.742 |
杨庙镇 | 东关街道 | 0.19 | 1.00 | 0.739 |
平均值 | 0.913 |
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