National Geographical Conditions Statistical Analysis in the Era of Big Data

LIU Jiping; DONG Chun; KANG Xiaochen; QIU Shike; ZHAO Rong; LI Bin; SUN Lijian

doi:10.13203/j.whugis20180420

Volume 44 Issue 1

Jan. 2019

Turn off MathJax

Article Contents

Abstract

References

Geomatics and Information Science of Wuhan University > 2019 > 44(1): 68-76, 83. > DOI: 10.13203/j.whugis20180420

LIU Jiping, DONG Chun, KANG Xiaochen, QIU Shike, ZHAO Rong, LI Bin, SUN Lijian. National Geographical Conditions Statistical Analysis in the Era of Big Data[J]. Geomatics and Information Science of Wuhan University, 2019, 44(1): 68-76, 83. DOI: 10.13203/j.whugis20180420

Citation:

PDF (10841 KB)

National Geographical Conditions Statistical Analysis in the Era of Big Data

1.
Chinese Academy of Surveying and Mapping, Beijing 100830, China
2.
Institute of Geographical Sciences, Henan Academy of Sciences, Zhengzhou 450052, China

Funds:

The National Key Research and Development Program of China 2016YFC0803101

the National Natural Science Foundation of China 41701461

the National Natural Science Foundation of China 71773117

the National Social Science Fund of China 18ZDA066

the National Social Science Fund of China 17BJL004

the Key Projects of Consultation and Research of the Chinese Academy of Engineering 2017-XZ-13

More Information

Author Bio:
LIU Jiping, PhD, professor, specializes in geospatial big data for e-government, government geographic information services, emergency geographic information services. E-mail: liujp@casm.ac.cn
Corresponding author:
KANG Xiaochen, PhD, assistant researcher. E-mail: kangxc@casm.ac.cn
Received Date: October 24, 2018
Published Date: January 04, 2019

Graphical Abstract

Abstract

Abstract

Statistical analysis is an important way of extracting information from the national geographical conditions data. It can reflect the internal spatial characteristics of resources, environment, ecology and economy, and their interactions from different dimensions. In view of the high-efficiency management, high-intensity computation and deep-level service for statistical analysis based on the big data, this paper puts forward a technical framework of national geographical conditions statistical analysis, and discusses the core process of statistical analysis from three dimensions:big data storage and integration, key technologies for statistical computation, service modeling and application. This paper will help to improve the application level of national geographical conditions monitoring and statistical analysis service in natural resources supervision, ecological protection and restoration, etc., and can promote the transformation and upgrading of geographical information industry in China.
- national geographical conditions,
- big data,
- technical framework,
- statistical computation,
- service modeling

FullText(HTML)

References (26)

References

[1]	李清泉, 李德仁.大数据GIS[J].武汉大学学报·信息科学版, 2014, 39(6):641-644 http://ch.whu.edu.cn/CN/abstract/abstract3000.shtml Li Qingquan, Li Deren. Big Data GIS[J]. Geomatics and Information Science of Wuhan University, 2014, 39(6):641-644 http://ch.whu.edu.cn/CN/abstract/abstract3000.shtml
[2]	吴炳方, 张淼, 曾红伟, 等.大数据时代的农情监测与预警[J].遥感学报, 2016, 20(5):1027-1037 http://d.old.wanfangdata.com.cn/Periodical/xxydn201714047 Wu Bingfang, Zhang Miao, Zeng Hongwei, et al. Agricultural Monitoring and Early Warning in the Era of Big Data[J]. Journal of Remote Sensing, 2016, 20(5):1027-1037 http://d.old.wanfangdata.com.cn/Periodical/xxydn201714047
[3]	李德仁, 姚远, 邵振峰.智慧城市中的大数据[J].武汉大学学报·信息科学版, 2014, 39(6):631-640 http://ch.whu.edu.cn/CN/abstract/abstract2999.shtml Li Deren, Yao Yuan, Shao Zhenfeng. Big Data in Smart City[J]. Geomatics and Information Science of Wuhan University, 2014, 39(6):631-640 http://ch.whu.edu.cn/CN/abstract/abstract2999.shtml
[4]	刘经南, 方媛, 郭迟, 等.位置大数据的分析处理研究进展[J].武汉大学学报·信息科学版, 2014, 39(4):379-385 http://ch.whu.edu.cn/CN/abstract/abstract2947.shtml Liu Jingnan, Fang Yuan, Guo Chi, et al. Research Progress in Location Big Data Analysis and Processing[J]. Geomatics and Information Science of Wuhan University, 2014, 39(4):379-385 http://ch.whu.edu.cn/CN/abstract/abstract2947.shtml
[5]	陈俊勇.地理国情监测的学习札记[J].测绘学报, 2012, 41(5):633-635 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=QK201205236439 Chen Junyong. Study Notes on Geographic National Condition Monitoring[J]. Acta Geodaetica et Cartographica Sinica, 2012, 41(5):633-635 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=QK201205236439
[6]	史文中, 秦昆, 陈江平, 等.可靠性地理国情动态监测的理论与关键技术探讨[J].科学通报, 2012, 57(24):2239-2248 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=QK201203731437 Shi Wenzhong, Qin Kun, Chen Jiangping, et al. Key Theories and Technologies on Reliable Dynamic Monitoring for National Geographical State[J]. Chinese Science Bulletin, 2012, 57(24):2239-2248 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=QK201203731437
[7]	李德仁, 马军, 邵振峰.论地理国情普查和监测的创新[J].武汉大学学报·信息科学版, 2018, 43(1):1-9 http://ch.whu.edu.cn/CN/abstract/abstract5939.shtml Li Deren, Ma Jun, Shao Zhenfeng. Innovation in the Census and Monitoring of Geographical National Conditions[J]. Geomatics and Information Science of Wuhan University, 2018, 43(1):1-9 http://ch.whu.edu.cn/CN/abstract/abstract5939.shtml
[8]	李德仁, 眭海刚, 单杰.论地理国情监测的技术支撑[J].武汉大学学报·信息科学版, 2012, 37(5):505-512 http://ch.whu.edu.cn/CN/abstract/abstract190.shtml Li Deren, Sui Haigang, Shan Jie. Discussion on Key Technologies of Geographic National Conditions Monitoring[J].Geomatics and Information Science of Wuhan University, 2012, 37(5):505-512 http://ch.whu.edu.cn/CN/abstract/abstract190.shtml
[9]	牛铮, 李加洪, 高志海, 等. 《全球生态环境遥感监测年度报告》进展与展望[J].遥感学报, 2018, 22(4):672-685 http://d.old.wanfangdata.com.cn/Periodical/ygxb201804013 Niu Zheng, Li Jiahong, Gao Zhihai, et al. Progress and Future of China's Annual Report on Remote Sensing Monitoring of Global Ecosystem and Environment[J]. Journal of Remote Sensing, 2018, 22(4):672-685 http://d.old.wanfangdata.com.cn/Periodical/ygxb201804013
[10]	Andersonteixeira K J, Davies S J, Bennett A C, et al. CTFS-ForestGEO:A Worldwide Network Monitoring Forests in an Era of Global Change[J]. Global Change Biology, 2015, 21(2):528-549 doi: 10.1111/gcb.12712
[11]	Sarah C E, Greory H R H, Robert D H, et al. Experiment, Monitoring, and Gradient Methods Used to Infer Climate Change Effects on Plant Communities Yield Consistent Patterns[J]. Proceedings of the National Academy of Sciences, Cross Mark, 2015, 112(2):448-452 doi: 10.1073/pnas.1410088112
[12]	Gordeev E I, Girina O A, Lupyan E A, et al. The VolSatView Information System for Monitoring the Volcanic Activity in Kamchatka and on the Kuril Islands[J]. Journal of Volcanology & Seismology, 2016, 10(6):382-394 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=16afbcaf9bc4f66a6a0d62a4aff4508f
[13]	Chang Yue, Hou Kang, Li Xuxiang, et al. Review of Land Use and Land Cover Change Research Progress[J]. IOP Conference Series:Earth and Environmental Science, 2018, 113(1), doi: 10.1088/1755-1315/113/1/012087
[14]	张继贤, 顾海燕, 鲁学军, 等.地理国情大数据研究框架[J].遥感学报, 2016, 20(5):1017-1026 http://d.old.wanfangdata.com.cn/Periodical/ygxb201605027 Zhang Jixian, Gu Haiyan, Lu Xuejun, et al. Research Framework of Geographical Conditions and Big Data[J].Journal of Remote Sensing, 2016, 20(5):1017-1026 http://d.old.wanfangdata.com.cn/Periodical/ygxb201605027
[15]	张晓祥.大数据时代的空间分析[J].武汉大学学报·信息科学版, 2014, 39(6):655-659 http://ch.whu.edu.cn/CN/abstract/abstract3010.shtml Zhang Xiaoxiang. Spatial Analysis in the Era of Big Data[J]. Geomatics and Information Science of Wuhan University, 2014, 39(6):655-659 http://ch.whu.edu.cn/CN/abstract/abstract3010.shtml
[16]	王家耀, 谢明霞.地理国情与复杂系统[J].测绘学报, 2016, 45(1):1-8 http://d.old.wanfangdata.com.cn/Periodical/chxb201601001 Wang Jiayao, Xie Mingxia. Geographical National Condition and Complex System[J]. Acta Geodaetica et Cartographica Sinica, 2016, 45(1):1-8 http://d.old.wanfangdata.com.cn/Periodical/chxb201601001
[17]	李绍俊, 杨海军, 黄耀欢, 等.基于NoSQL数据库的空间大数据分布式存储策略[J].武汉大学学报·信息科学版, 2017, 42(2):163-169 http://ch.whu.edu.cn/CN/abstract/abstract5656.shtml Li Shaojun, Yang Haijun, Huang Yaohuan, et al. Geo-spatial Big Data Storage Based on NoSQL Database[J]. Geomatics and Information Science of Wuhan University, 2017, 42(2):163-169 http://ch.whu.edu.cn/CN/abstract/abstract5656.shtml
[18]	Delgado F, Finat J. An Evaluation of Ontology Matching Techniques on Geospatial Ontologies[J]. International Journal of Geographical Information Science, 2013, 27(12):2279-2301 doi: 10.1080/13658816.2013.812215
[19]	Christopher C W, Renee E S. Toward an Inclusive Semantic Interoperability:The Case of Cree Hydrographic Features[J]. International Journal of Geographical Information Science, 2013, 27(1):168-191 doi: 10.1080/13658816.2012.688975
[20]	Anjum N, Harding J, Young R, et al. Verification of Knowledge Shared Across Design and Manufacture Using a Foundation Ontology[J]. Internatio-nal Journal of Production Research, 2013, 51(22):6534-6552 doi: 10.1080/00207543.2013.798051
[21]	董南, 杨小唤, 蔡红艳, 等.人口密度格网尺度适宜性评价方法研究——以宣州区乡村区域为例[J].地理学报, 2017, 72(12):2310-2324 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=dlxb201712014 Dong Nan, Yang Xiaohuan, Cai Hongyan, et al. Suitability Evaluation of Gridded Population Distribution:A Case Study in Rural Area of Xuanzhou District, China[J]. Acta Geographica Sinica, 2017, 72(12):2310-2324 http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=dlxb201712014
[22]	刘纪平, 吴立新, 董春, 等.一种大规模空间数据流式并行处理方法研究[J].测绘科学, 2016, 41(1):89-93 http://d.old.wanfangdata.com.cn/Periodical/chkx201601017 Liu Jiping, Wu Lixin, Dong Chun, et al. Study on a Streaming Parallel Method for Massive Spatial Data Processing[J].Science of Surveying and Mapping, 2016, 41(1):89-93 http://d.old.wanfangdata.com.cn/Periodical/chkx201601017
[23]	亢晓琛, 刘纪平, 林祥国.多核处理器的机载激光雷达点云并行三角网渐进加密滤波方法[J].测绘学报, 2013, 42(3):331-336 http://d.old.wanfangdata.com.cn/Periodical/chxb201303003 Kang Xiaochen, Liu Jiping, Lin Xiangguo. Parallel Filter of Progressive TIN Densification for Airborne LiDAR Point Cloud Using Multi-core CPU[J]. Acta Geodaetica et Cartographica Sinica, 2013, 42(3):331-336 http://d.old.wanfangdata.com.cn/Periodical/chxb201303003
[24]	刘瑞, 朱道林.基于转移矩阵的土地利用变化信息挖掘方法探讨[J].资源科学, 2010, 32(8):1544-1550 http://d.old.wanfangdata.com.cn/Periodical/zykx201008016 Liu Rui, Zhu Daolin. Method for Detecting Land Use Changes Based on the Land Use Transition Matrix[J].Resources Science, 2010, 32(8):1544-1550 http://d.old.wanfangdata.com.cn/Periodical/zykx201008016
[25]	Taniguchi M, Rebellato L M, Cai J, et al. Higher Risk of Kidney Graft Failure in the Presence of Anti-Angiotensin Ⅱ Type-1 Receptor Antibodies[J]. American Journal of Transplantation, 2013, 13(10):2577-2589 doi: 10.1111/ajt.12395
[26]	Mikolov T, Karafiát M, Burget L, et al. Recurrent Neural Network Based Language Model[C].The 11th Annual Conference of the International Speech Communication Association, Makuhari, Japan, 2010

[1]	LU Binbin, TIAN Xiaoxi, QIN Sixian, SHI Yilin, LI Jiansong. Urban Land Carrying Capacity Evaluation of Wuhan City with Geographically Weighted Techniques[J]. Geomatics and Information Science of Wuhan University, 2025, 50(3): 430-438. DOI: 10.13203/j.whugis20220778
[2]	LU Binbin, GE Yong, QIN Kun, ZHENG Jianghua. A Review on Geographically Weighted Regression[J]. Geomatics and Information Science of Wuhan University, 2020, 45(9): 1356-1366. DOI: 10.13203/j.whugis20190346
[3]	LUO Minghai, JIANG Zilong, CHENG Qi, QIN Sixian, YANG Nana, ZHANG Xinyue. Carrying Capacity Evaluation of Land Resources in Wuhan Based on the Geographical Condition Monitoring[J]. Geomatics and Information Science of Wuhan University, 2018, 43(12): 2317-2324. DOI: 10.13203/j.whugis20180389
[4]	NIE Lei, SHU Hong, LIU Yan. Interpolation of Monthly Average Temperature by Using (Mixed) Geographically Weighted Regression Kriging in the Complex Terrain Region[J]. Geomatics and Information Science of Wuhan University, 2018, 43(10): 1553-1559. DOI: 10.13203/j.whugis20160433
[5]	LIU Xiaojing, GUI Zhipeng, CAO Jun, LI Rui, WU Huayi. Spatiotemporal-Aware Hybrid Prediction Model for Response Time of Web Map Services by Integrating GWR and STARMA[J]. Geomatics and Information Science of Wuhan University, 2018, 43(6): 951-958. DOI: 10.13203/j.whugis20160370
[6]	LU Binbin, YANG Huan, SUN Huabo, YU Qingde. Algorithm of Approximating Road Network Distance Via the Minkowski Distance[J]. Geomatics and Information Science of Wuhan University, 2017, 42(10): 1373-1380. DOI: 10.13203/j.whugis20160225
[7]	WANG Xu, LIN Zheng, ZHANG Zhi, LI Dan. Modelling the Spatial Distribution of Lake Surface Water Temperature of the Thaw Lakes in Arctic Coastal Plain Using Geographically Weighted Regression Model[J]. Geomatics and Information Science of Wuhan University, 2016, 41(7): 918-924. DOI: 10.13203/j.whugis20140411
[8]	MA Ronghua, HE Zengyou, . Mining Complete and Correct Frequent Neighboring Class Sets from Spatial Databases[J]. Geomatics and Information Science of Wuhan University, 2007, 32(2): 115-119.
[9]	YU Leiyi. Study on the Architecture of GIS Grid[J]. Geomatics and Information Science of Wuhan University, 2004, 29(2): 153-156.
[10]	LIU Yanxiong, CHEN Yongqi, LIU Jingnan. Determination of Weighted Mean Tropospheric Temperature Using Ground Meteorological Measurement[J]. Geomatics and Information Science of Wuhan University, 2000, 25(5): 400-404.

Cited By

Get Citation

PDF

XML

Article views PDF downloads

National Geographical Conditions Statistical Analysis in the Era of Big Data

Abstract

References

Related Articles

Catalog

Related

National Geographical Conditions Statistical Analysis in the Era of Big Data

Abstract

References

Related Articles

Catalog

Related

Export File

Citation

Format

Content