警用空间大数据区位标识方法及其应用

doi:10.11947/j.AGCS.2016.F015

测绘学报 ›› 2016, Vol. 45 ›› Issue (S1): 121-126.doi: 10.11947/j.AGCS.2016.F015

警用空间大数据区位标识方法及其应用

胡晓光¹, 高树辉¹, 童晓冲², 程承旗³, 蔡能斌⁴

1. 中国人民公安大学刑事科学技术学院, 北京 100038;
2. 信息工程大学地理空间信息学院, 河南郑州 450001;
3. 北京大学工学院, 北京 100871;
4. 上海市现场物证重点实验室, 200083

收稿日期:2016-08-20 修回日期:2016-10-20 出版日期:2016-12-31 发布日期:2017-03-29
通讯作者: 蔡能斌 E-mail:13162056906@163.com
作者简介:胡晓光(1980-),男,博士,讲师,主要从事地理信息系统与计算机视觉方面的研究。E-mail:Michael.hu.07@Foxmail.com
基金资助:
2016年中国人民公安大学刑事科学技术学院学科建设项目；2016上海市刑事科学技术研究院横向项目（2016XCWZK10）；中国人民公安大学中央高校基本科研业务费项目（2016JKF01315）

Police Spatial Big Data Location Code and Its Application Prospect

HU Xiaoguang¹, GAO Shuhui¹, TONG Xiaochong², CHENG Chengqi³, CAI Nengbin⁴

1. Institute of Forensic Science, People's Public Security University of China, Beijing 100038, China;
2. Institute of Surveying and Mapping, Information Engineering University, Zhengzhou 450001, China;
3. College of Engineering, Peking University, Beijing 100871, China;
4. Shanghai Key Laboratory of Criminal Scene Evidence, Shanghai 200083, China

Received:2016-08-20 Revised:2016-10-20 Online:2016-12-31 Published:2017-03-29
Supported by:
2016 Discipline Construction Project of Institute of Forensic Science, PPSUC;2016 Shanghai Institute of Criminal Science and Technology Project (2016XCWZK10);The Fundamental Research Funds for the Central Universities, PPSUC(2016JKF01315)

摘要/Abstract

摘要： 警用空间大数据为警务工作的开展提供了丰富的决策依据，但也带来了一些挑战，如大数据整合复杂、多尺度信息关联困难、区位标识不唯一等，不利于警务改革的深入发展。本文提出了基于区域的位置标识方法来解决存在的问题，方法基于剖分网格设计了警用空间大数据的区位编码方法，并以户籍的区位标识为例进行说明，最后对其应用进行了展望，从而为警用空间大数据的有效组织和高效应用等提供了一种新的解决思路。

关键词: 警用空间大数据, 区位标识, 区位编码, 剖分网格

Abstract: The rich decision-making basis are provided for police work by police spatial big data. But some challenges are also brought by it, such as:large data integration complex, multi scale information related difficulties, the location identification is not unique. Thus, how to make the data better service to the police work reform and development is a problem need to be study. In this paper, we propose location identification method to solve the existing problems. Based on subdivision grid, we design the location encoding method of police spatial big data, and choose domicile location identification as a case. Finally, the prospect of its application is presented. So, a new idea is proposed to solve the problem existing in the police spatial data organization and application.

Key words: police spatial big data, location identification, location coding, subdivision grid

中图分类号:

P227

胡晓光, 高树辉, 童晓冲, 程承旗, 蔡能斌. 警用空间大数据区位标识方法及其应用[J]. 测绘学报, 2016, 45(S1): 121-126.

HU Xiaoguang, GAO Shuhui, TONG Xiaochong, CHENG Chengqi, CAI Nengbin. Police Spatial Big Data Location Code and Its Application Prospect[J]. Acta Geodaetica et Cartographica Sinica, 2016, 45(S1): 121-126.

参考文献

[1] 李德仁, 王树良, 李德毅, 等. 论空间数据挖掘和知识发现的理论与方法[J]. 武汉大学学报(信息科学版), 2002, 27(3):221-233. LI Deren, WANG Shuliang, LI Deyi, et al. Theories and Technologies of Spatial Data Mining and Knowledge Discovery[J]. Geomatics and Information Science of Wuhan University, 2002, 27(3):221-233.
[2] 李德仁, 王树良, 史文中, 等. 论空间数据挖掘和知识发现[J]. 武汉大学学报(信息科学版), 2001, 26(6):491-499. LI Deren, WANG Shuliang, SHI Wenzhong, et al. On Spatial Data Mining and Knowledge Discovery (SDMKD)[J]. Geomatics and Information Science of Wuhan University, 2001, 26(6):491-499.
[3] 陆大道. 区位论及区域研究方法[M]. 北京:科学出版社, 1988. LU Dadao. Location Theory and Regional Research Methods[M]. Beijing:Science Press, 1988.
[4] GOODCHILD M F, YANG Shiren. A Hierarchical Spatial Data Structure for Global Geographic Information Systems[J]. CVGIP:Graphical Models and Image Processing, 1992, 54(1):31-44.
[5] DUTTON G. Improving Locational Specificity of Map Data-A Multi-Resolution, Metadata-Driven Approach and Notation[J]. International Journal of Geographical Information Systems, 1996, 10(3):253-268.
[6] SAHR K, WHITE D, KIMERLING A J. Geodesic Discrete Global Grid Systems[J]. Cartography and Geographic Information Science, 2003, 30(2):121-134.
[7] TONG Xiaochong, BEN Jin, WANG Ying, et al. Efficient Encoding and Spatial Operation Scheme for Aperture 4 Hexagonal Discrete Global Grid System[J]. International Journal of Geographical Information Science, 2013, 27(5):898-921.
[8] CHENG Chengqi, TONG Xiaochong, CHEN Bo, et al. A Subdivision Method to Unify the Existing Latitude and Longitude Grids[J]. ISPRS International Journal of Geo-Information, 2016, 5(9):161.
[9] 程承旗, 郑承迅. 一种统一现有经纬度剖分网格的方法:中国, 102609525A[P]. 2012-07-25. CHENG Chengqi, ZHENG Chengxun. A Subdivision Method to Unify the Existing Latitude and Longitude Grids:China, 102609525A[P]. 2012-07-25.
[10] 李世忠, 宋树华, 程承旗, 等. 基于GeoSOT网格的"天绘一号"卫星影像数据组织[J]. 遥感学报, 2012, 16(S):102-107. LI Shizhong, SONG Shuhua, CHENG Chengqi, et al. Mapping Satellite-1 Remote Sensing Data Organization Based on GeoSOT[J]. Journal of Remote Sensing, 2012, 16(S):102-107.
[11] 宋树华, 程承旗, 濮国梁, 等. 全球遥感数据剖分组织的GeoSOT网格应用[J]. 测绘学报, 2014, 43(8):869-876. DOI:10.13485/j.cnki.11-2089.2014.0103. SONG Shuhua, CHENG Chengqi, PU Guoliang, et al. Global Remote Sensing Data Subdivision Organization Based on GeoSOT[J]. Acta Geodaetica et Cartographica Sinica, 2014, 43(8):869-876. DOI:10.13485/j.cnki.11-2089.2014.0103.
[12] 程承旗, 吕雪锋, 关丽. 空间数据剖分集群存储系统架构初探[J]. 北京大学学报(自然科学版), 2011, 47(1):103-108. CHENG Chengqi, LÜ Xuefeng, GUAN Li. Study on System Architecture of Subdivision Storage Cluster for Global Spatial Data[J]. Acta Scientiarum Naturalium Universitatis Pekinensis, 2011, 47(1):103-108.
[13] LÜ Xuefeng, CHENG Chengqi, GONG Jianya, et al. Review of Data Storage and Management Technologies for Massive Remote Sensing Data[J]. Science China Technological Sciences, 2011, 54(12):3220-3232.
[14] GONG J Y, XIANG L G, CHEN J, et al. Multi-source Geospatial Information Integration and Sharing in Virtual Globes[J]. Science China Technological Sciences, 2010, 53(S1):1-6.
[15] SAMPLE J T, LOUP E. Tile-based Geospatial Information Systems:Principles and Practices[M]. New York, NY:Springer, 2010:23-200.
[16] BOSCHETTI L, ROY D P, JUSTICE C O. Using NASA's World Wind Virtual Globe for Interactive Internet Visualization of the Global MODIS Burned Area Product[J]. International Journal of Remote Sensing, 2008, 29(11):3067-3072.
[17] SCHWARTZ J. Bing Maps Tile System[EB/OL]. http://msdn.microsoft.com/en-us/library/bb259689.aspx.
[18] BARCLAY T, GRAY J, EKBLAD S, et al. Designing and Building TerraService[J]. IEEE Internet Computing, 2006, 10(5):16-25.
[19] NAKAJIMA K. Preconditioned Iterative Linear Solvers for Unstructured Grids on the Earth Simulator[C]//Proceedings of the Seventh International Conference on High Performance Computing and Grid in Asia Pacific Region. Tokyo:IEEE, 2004:150-159.
[20] 钱建梅, 郑旭东. 国家卫星气象中心气象卫星资料存档系统[J]. 应用气象学报, 2003, 14(6):756-762. QIAN Jianmei, ZHENG Xudong. The Satellite Data Archive System of National Satellite Meteorological Center[J]. Journal of Applied Meteorological Science, 2003, 14(6):756-762.
[21] 李德仁, 朱欣焰, 龚健雅. 从数字地图到空间信息网格:空间信息多级网格理论思考[J]. 武汉大学学报:信息科学版, 2003, 28(6):642-650. LI Deren, ZHU Xinyan, GONG Jianya. From Digital Map to Spatial Information Multi-grid:A Thought of Spatial Information Multi-grid Theory[J]. Geomatics and Information Science of Wuhan University, 2003, 28(6):642-650.
[22] 国家测绘地理信息局测绘标准化研究所. GB/T 13989-2012国家基本比例尺地形图分幅和编号[S]. 北京:中国标准出版社, 2012. Institute on Standardiztion of National Adminstration of Suveying, Mapping and Geoinformation. GB/T 13989-2012 Subdivision and Numbering for the National Primary Scale Topographic Maps[S]. Beijing:China Standard Press, 2012.

警用空间大数据区位标识方法及其应用

Police Spatial Big Data Location Code and Its Application Prospect

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 2

编辑推荐

Metrics

本文评价

[1]	俞童, 邓术军, 钱海忠, 杨清丽. 剖分网格下顾及用户兴趣的矢量地图多尺度表达方法[J]. 测绘学报, 2016, 45(S1): 127-134.
[2]	孟丽, 程承旗, 陈东, 杨伟铭. 地球剖分网格的地形量化模型[J]. 测绘学报, 2016, 45(S1): 152-158.