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Data Analysis and Knowledge Discovery  2020, Vol. 4 Issue (9): 81-90    DOI: 10.11925/infotech.2096-3467.2020.0156
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Spatial Distribution and Socio-economic Driving Forces of Residential Changes: Case Study of Zhejiang Province
Zhou Heng1,Chen Zhangjian2,Li Aiqin2,Cheng Xiaoqiang3,4(),Wu Huayi1,5
1State Key Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing,Wuhan University, Wuhan 430079, China
2Zhejiang Academy of Surveying & Mapping, Hangzhou 311100, China
3Faculty of Resources and Environmental Science, Hubei University, Wuhan 430062, China
4Key Laboratory of Regional Development and Environmental Response, Hubei University, Wuhan 430062, China
5Collaborative Innovation Center of Geospatial Technology, Wuhan 430079, China
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Abstract  

[Objective] This paper aims to identify the changes of geographic elements in surveying and mapping, as well as their driving mechanism.[Methods] We collected the changes of residential areas from Zhejiang Province. With the help of GIS overlay and correlation analysis, we analyzed the socio-economic driving forces behind these changes.[Results] We found that the changes were concentrated in the north, central and southeast parts of Zhejiang Province.The development of industry was the main positive driving force (correlation coefficient: 0.336).The development of the service or retail sectors and government public investments were negative driving forces for the changes (correlation coefficients: -0.054 and -0.100).[Limitations] The accuracy of statistical data needs to be further improved to reduce the “false changes” from cartographic synthesis.[Conclusions] The changes in residential areas were different and their economic driving factors were also different.

Key wordsChanges in Residential Elements      Driving Force      Socio-economic Factors      Partial Least Squares Regression     
Received: 03 March 2020      Published: 14 October 2020
ZTFLH:  P283  
Corresponding Authors: Cheng Xiaoqiang     E-mail: carto@hubu.edu.cn

Cite this article:

Zhou Heng,Chen Zhangjian,Li Aiqin,Cheng Xiaoqiang,Wu Huayi. Spatial Distribution and Socio-economic Driving Forces of Residential Changes: Case Study of Zhejiang Province. Data Analysis and Knowledge Discovery, 2020, 4(9): 81-90.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2020.0156     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2020/V4/I9/81

Unfiltered Changes of Residential Elements
Frequency Distribution Histogram of Compactness Ratio
Filtered Changes of Residential Elements
居民地变化指标 总计 均值 标准差 最小值 最大值
变化数目 1 905 691 21 412 32 380 2 189 791
变化面积(km2 221.01 2.48 2.65 0.05 14.74
Statistical Characteristics of Residential Elements’ Changes
Spatial Distribution of Residential Elements’ Changes in Zhejiang Province
Spatial Agglomeration Characteristics of Residential Elements’ Changes in Zhejiang Province
探测领域 探测因子 指标
经济发展 X1经济规模 人均GDP(元)
产业结构 X2第一产业发展 第一产业占比(%)
X3第二产业发展 第二产业占比(%)
X4第三产业发展 第三产业占比(%)
政府公共投入 X5政府公共投入程度 人均一般公共预算支出(元)
地方规模 X6人口规模 区县常驻人口数(人)
X7建筑规模 建筑物总面积(km2)
X8建筑物密度 建筑物面积占行政区划面积的比(%)
社会群体收支 X9消费水平 人均社会消费品零售额(元)
X10可支配收入水平 人均住户存款年末余额(元)
Index of Socio-economic Driving Factors Detecting
Prediction of Partial Least Squares Regression Model for Residential Elements’ Changes and Socioeconomic Factors
X1 X2 X3 X4 X5 X6 X7 X8 X9 X10
Y1 -0.047 0.050 0.336 -0.054 -0.100 0.146 0.042 0.088 0.081 0.294
Y2 0.017 0.079 0.241 -0.065 -0.051 0.096 0.015 0.100 0.098 0.217
Regression Coefficients of Partial Least Squares Regression Model
Histogram of Regression Coefficients in Partial Least Squares Regression Model
[1] 李德仁, 苗前军, 邵振峰. 信息化测绘体系的定位与框架[J]. 武汉大学学报(信息科学版), 2007,32(3):189-192, 196.
[1] ( Li Deren, Miao Qianjun, Shao Zhenfeng. Orientation and Framework of Geo-informatization System[J]. Geomatics and Information Science of Wuhan University, 2007,32(3):189-192, 196.)
[2] 刘文谷. 测绘行业改革模式研究[D]. 重庆: 重庆大学, 2003.
[2] ( Liu Wengu. Research on Reforming Model of S/M Industry[D]. Chongqing: Chongqing University, 2003.)
[3] 张继贤, 顾海燕. 关于新型测绘的探索[J]. 测绘科学, 2016,41(2):3-10.
[3] ( Zhang Jixian, Gu Haiyan. The Exploration of New Surveying and Mapping[J]. Science of Surveying and Mapping, 2016,41(2):3-10.)
[4] 吴张峰, 刘一宁. 城市空间信息变化检测方法研究[J]. 上海国土资源, 2016,37(4):89-91, 95.
[4] ( Wu Zhangfeng, Liu Yining. Research on Methods for Detecting Change in Urban Spatial Information[J]. Shanghai Land & Resources, 2016,37(4):89-91, 95.)
[5] 陈甲全, 陈雪洋, 殷明. 浅议自然资源背景下的地理信息科技发展方向[J]. 地理空间信息, 2019,17(9):18-21.
[5] ( Chen Jiaquan, Chen Xueyang, Yin Ming. Talking about Development Direction of Geographical Information Science and Technology under the Background of Natural Resource[J]. Geospatial Information, 2019,17(9):18-21.)
[6] 肖建华, 彭清山, 李海亭. “测绘4.0”: 互联网时代下的测绘地理信息[J]. 测绘通报, 2015(7):1-4.
doi: 10.13474/j.cnki.11-2246.2015.0198
[6] ( Xiao Jianhua, Peng Qingshan, Li Haiting. “Geomatics 4.0”: Surveying, Mapping and Geoinformation in the Internet Era[J]. Bulletin of Surveying and Mapping, 2015(7):1-4.)
doi: 10.13474/j.cnki.11-2246.2015.0198
[7] 宁津生, 王正涛. 面向信息化时代的测绘科学技术新进展[J]. 测绘科学, 2010,35(5):5-10.
[7] ( Ning Jinsheng, Wang Zhengtao. The Newest Progress of Surveying & Mapping Oriented Informatization Stage[J]. Science of Surveying and Mapping, 2010,35(5):5-10.)
[8] 张效康. 地理国情监测数据可靠性分析与控制方法研究[D]. 武汉: 武汉大学, 2017.
[8] ( Zhang Xiaokang. Reliability Analysis and Controlling Methods for National Geographic State Monitoring Data[D]. Wuhan: Wuhan University, 2017.)
[9] 李新滨, 江娜, 孔杰. 一种基于几何特征的面状地理要素变化检测方法[J]. 测绘与空间地理信息, 2011,34(3):177-180.
[9] ( Li Xinbin, Jiang Na, Kong Jie. A Change Detection Method of Polygon Features Based on Geometrical Characteristic[J]. Geomatics & Spatial Information Technology, 2011,34(3):177-180.)
[10] 戴海伦, 王德冬, 刘中秋, 等. 基于地理国情数据的基础地理信息增量更新方法研究[J]. 地理信息世界, 2017,24(3):92-96.
[10] ( Dai Hailun, Wang Dedong, Liu Zhongqiu, et al. An Incremental Updating Method Research for Updating Basic Geographic Information Data Based on the Geographic National Condition Census Data[J]. Geomatics World, 2017,24(3):92-96.)
[11] 刘杰. 面向地理国情监测的地理要素变化检测方法[J]. 地理空间信息, 2017,15(5):32-34.
[11] ( Liu Jie. Geographical Element Change Detection Method Oriented to Geographical Conditions Monitoring[J]. Geospatial Information, 2017,15(5):32-34.)
[12] 王曙, 吉雷静, 张雪英, 等. 面向网页文本的地理要素变化检测[J]. 地球信息科学学报, 2013,15(5):625-634.
doi: 10.3724/SP.J.1047.2013.00625
[12] ( Wang Shu, Ji Leijing, Zhang Xueying, et al. Change Detection of Geographic Features Based on Web Pages[J]. Journal of Geo-information Science, 2013,15(5):625-634.)
doi: 10.3724/SP.J.1047.2013.00625
[13] 吉雷静. 面向网页文本的地理信息变化语义检测方法研究[D]. 南京: 南京师范大学, 2013.
[13] ( Ji Leijing. Semantic Change Detection of Geographic Information Based on Web Pages[D]. Nanjing: Nanjing Normal University, 2013.)
[14] 王子豪, 段佳, 张怡. 一种利用拓扑关系检测地理要素变化的方法[J]. 测绘, 2015,38(1):14-16.
[14] ( Wang Zihao, Duan Jia, Zhang Yi. A Method to Detect Changes of Geographic Elements by Using Topological Relation[J]. Surveying and Mapping, 2015,38(1):14-16.)
[15] 杨存建, 周成虎. TM影像的居民地信息提取方法研究[J]. 遥感学报, 2000,4(2):146-150, 166.
doi: 10.11834/jrs.20000212
[15] ( Yang Cunjian, Zhou Chenghu. Extracting Residential Areas on the TM Imagery[J]. Journal of Remote Sensing, 2000,4(2):146-150, 166.)
doi: 10.11834/jrs.20000212
[16] 牟凤云, 张增祥, 迟耀斌, 等. 基于多源遥感数据的北京市1973-2005年间城市建成区的动态监测与驱动力分析[J]. 遥感学报, 2007,11(2):257-268.
doi: 10.11834/jrs.20070236
[16] ( Mu Fengyun, Zhang Zengxiang, Chi Yaobin, et al. Dynamic Monitoring of Built-up Area in Beijing During 1973-2005 Based on Multi-original Remote Sensed Images[J]. Journal of Remote Sensing, 2007,11(2):257-268.)
doi: 10.11834/jrs.20070236
[17] 龚丽芳, 李爱勤, 陈张建. 政务应用驱动下的地理空间大数据建设实践[J]. 测绘通报, 2019(8):125-129.
[17] ( Gong Lifang, Li Aiqin, Chen Zhangjian. Case Study of Geospatial Big Data Driven by Government Application[J]. Bulletin of Surveying and Mapping, 2019(8):125-129.)
[18] 彭瑞, 许大璐, 朱雪坚. 浙江省基础地理空间要素数据库增量更新技术研究与生产应用[J]. 测绘与空间地理信息, 2018,41(10):104-107.
[18] ( Peng Rui, Xu Dalu, Zhu Xuejian. Research and Production Application on the Incremental Update Technology of Zhejiang Provincial Fundamental Geospacial Database[J]. Geomatics & Spatial Information Technology, 2018,41(10):104-107.)
[19] Cliff A D, Ord J K. Spatial Processes: Models and Applications[J]. Population, 1982,37:963.
[20] Anselin L, Kelejian H H. Testing for Spatial Error Autocorrelation in the Presence of Endogenous Regressors[J]. International Regional Science Review, 1997,20(1/2):153-182.
doi: 10.1177/016001769702000109
[21] Wang S J, Fang C L, Wang Y. Spatiotemporal Variations of Energy-related CO2 Emissions in China and Its Influencing Factors: An Empirical Analysis Based on Provincial Panel Data[J]. Renewable and Sustainable Energy Reviews, 2016,55:505-515.
doi: 10.1016/j.rser.2015.10.140
[22] 孟洁, 王惠文. 多元成分数据的对数衬度偏最小二乘通径分析模型[J]. 数理统计与管理, 2009,28(3):436-442.
[22] ( Meng Jie, Wang Huiwen. Logcontrast PLS Path Modeling of Multiple Compositional Data[J]. Application of Statistics and Management, 2009,28(3):436-442.)
[23] Zhang Y, Li C H, Wang T W, et al. County-level Patterns of Cropland and Their Relationships with Socio-economic Factors in Northwestern China[J]. Agriculture, Ecosystems and Environment, 2014,203(1):11-18.
doi: 10.1016/j.agee.2014.11.016
[24] 吴琼, 原忠虎, 王晓宁. 基于偏最小二乘回归分析综述[J]. 沈阳大学学报, 2007,19(2):33-35.
[24] ( Wu Qiong, Yuan Zhonghu, Wang Xiaoning. Summary of Partial Least Squares Regression[J]. Journal of Shenyang University, 2007,19(2):33-35.)
[25] 刘虎林, 闫浩文, 刘涛. 空间数据变化检测研究进展[J]. 测绘与空间地理信息, 2014,37(9):25-28.
[25] ( Liu Hulin, Yan Haowen, Liu Tao. Research on Spatial Data Change Detection[J]. Geomatics & Spatial Information Technology, 2014,37(9):25-28.)
[26] 简灿良. 多比例尺地图数据不一致性探测与处理方法研究[D]. 武汉:武汉大学, 2013.
[26] ( Jian Canliang. A Study on Multi-scale Vector Map Data Inconsistency Detection and Handling Methods[D]. Wuhan: Wuhan University, 2013.)
[27] 黄宝群. DLG数据库中面要素的变化检测与更新方法研究[D]. 南京: 南京师范大学, 2017.
[27] ( Huang Baoqun. Research on Change Detection and Update of Surface Elements in DLG Database[D]. Nanjing: Nanjing Normal University, 2017.)
[28] 王新生, 刘纪远, 庄大方, 等. 中国特大城市空间形态变化的时空特征[J]. 地理学报, 2005,60(3):392-400.
doi: 10.11821/xb200503005
[28] ( Wang Xinsheng, Liu Jiyuan, Zhuang Dafang, et al. Spatial-temporal Changes of Urban Spatial Morphology in China[J]. Acta Geographica Sinica, 2005,60(3):392-400.)
doi: 10.11821/xb200503005
[29] 刘纪远, 王新生, 庄大方, 等. 凸壳原理用于城市用地空间扩展类型识别[J]. 地理学报, 2003,58(6):885-892.
doi: 10.11821/xb200306012
[29] ( Liu Jiyuan, Wang Xinsheng, Zhuang Dafang, et al. Application of Convex Hull in Identifying the Types of Urban Land Expansion[J]. Acta Geographica Sinica, 2003,58(6):885-892.)
doi: 10.11821/xb200306012
[30] 王雪青, 陈媛, 刘炳胜. 中国区域房地产经济发展水平空间统计分析——全局Moran’s I、Moran散点图与LISA集聚图的组合研究[J]. 数理统计与管理, 2014,33(1):59-71.
[30] ( Wang Xueqing, Chen Yuan, Liu Bingsheng. Exploratory Spatial Data Analysis about the Development Level of the Regional Real Estate Economy China—The Research Based on Global Moran’s I, Moran Scatter Plots and LISA Cluster Map[J]. Journal of Applied Statistics and Management, 2014,33(1):59-71.)
[31] 杨晴青, 陈佳, 李伯华, 等. 长江中游城市群城市人居环境演变及驱动力研究[J]. 地理科学, 2018,38(2):195-205.
doi: 10.13249/j.cnki.sgs.2018.02.005
[31] ( Yang Qingqing, Chen Jia, Li Bohua, et al. Evolution and Driving Force Detection of Urban Human Settlement Environment at Urban Agglomeration in the Middle Reaches of the Yangtze River[J]. Scientia Geographica Sinica, 2018,38(2):195-205.)
doi: 10.13249/j.cnki.sgs.2018.02.005
[32] 顾刘阳, 张永福, 朱小强, 等. 基于遥感与CA-Markov模型的土地利用景观格局模拟及其驱动力研究[J]. 黑龙江大学工程学报, 2017,8(2):14-20, 30.
[32] ( Gu Liuyang, Zhang Yongfu, Zhu Xiaoqiang, et al. Simulation of Land Use Landscape Pattern Prediction and Analysis of Driving Forces Based on Remote Sensing and CA-Markov Model[J]. Journal of Engineering of Heilongjiang University, 2017,8(2):14-20, 30.)
[33] 宋金平, 赵西君, 王倩. 北京市丰台区土地利用变化及社会经济驱动力分析[J]. 中国人口·资源与环境, 2008,18(2):171-175.
[33] ( Song Jinping, Zhao Xijun, Wang Qian. Analysis of Land Use Change and Socioeconomic Driving Forces of Fengtai District in Beijing[J]. China Population Resources and Environment, 2008,18(2):171-175.)
[34] 叶莺, 陈崇帼, 林熙. 偏最小二乘回归的原理及应用[J]. 海峡预防医学杂志, 2005,11(3):3-6.
[34] ( Ye Ying, Chen Chongguo, Lin Xi. Theory and Application of Partial Least Squares Regression[J]. Strait Journal of Preventive Medicine, 2005,11(3):3-6.)
[1] Zhou Heng, Chen Zhangjian, Li Aiqin, Cheng Xiaoqiang, Wu Huayi. Analysis on the Spatial Distribution and Socio-economic Driving Forces of Changes in Residential Elements: A Case Study of Zhejiang Province [J]. 数据分析与知识发现, 0, (): 1-.
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