跨比例尺新旧居民地目标变化分析与决策树识别

doi:10.11947/j.AGCS.2018.20170373

测绘学报 ›› 2018, Vol. 47 ›› Issue (3): 403-412.doi: 10.11947/j.AGCS.2018.20170373

跨比例尺新旧居民地目标变化分析与决策树识别

陈利燕^1,3, 张新长^2,1, 林鸿³, 杨敏⁴

1. 中山大学地理科学与规划学院, 广东广州 510275;
2. 广州大学地理科学学院, 广东广州 510006;
3. 广州市城市规划勘测设计研究院, 广东广州 510060;
4. 武汉大学资源与环境科学学院, 湖北武汉 430072

收稿日期:2017-06-30 修回日期:2017-11-16 出版日期:2018-03-20 发布日期:2018-03-29
通讯作者: 张新长 E-mail:eeszxc@mail.sysu.edu.cn
作者简介:陈利燕(1981-),女,博士后,高级工程师,研究方向空间数据更新与融合.E-mail:jimigao@163.com
基金资助:
广州市博士后启动基金（201517040001）；国土资源部城市土地资源监测与仿真重点实验室开放基金（KF-2016-02-020）；国家自然科学基金重点项目（41431178）；广东省自然科学基金重点项目（2016A030311016）；广州市工信委信息化项目（GZIT2016-A5-147）

Change Analysis and Decision Tree Based Detection Model for Residential Objects across Multiple Scales

CHEN Liyan^1,3, ZHANG Xinchang^2,1, LIN Hong³, YANG Min⁴

1. School of Geography and Planning, Sun Yat-Sen University, Guangzhou 510275, China;
2. School of Geographical Sciences of Guangzhou University, Guangzhou 510006, China;
3. Guangzhou Urban Planning and Design Survey Research Institute, Guangzhou 510060, China;
4. School of Resources and Environment Science, Wuhan University, Wuhan 430072, China

Received:2017-06-30 Revised:2017-11-16 Online:2018-03-20 Published:2018-03-29
Supported by:
Guangzhou Postdoctoral Science Foundation (No. 201517040001);The Open Fund of Key Laboratory of Urban Land Resources Monitoring and Simulation,Ministry of Land and Resources (No. KF-2016-02-020);The National Natural Science Foundation of China (No. 41431178);The Natural Science Foundation of Guangdong Province of China (No. 2016A030311016);GZIT (No. 2016-A5-147)

摘要/Abstract

摘要： 变化分析与探测是跨比例尺地图数据更新的核心问题之一。以往研究主要关注时间维上地理实体时空演化引起的地图目标变化，甚至将地图目标变化等同于地理实体真实变化，忽略了尺度维上由地图综合导致的表达变化。本文以居民地数据为例，从表层形式和深层缘由对跨比例尺新旧地图数据间的目标变化进行深入分析。在此基础上，引入机器学习领域的决策树方法构建变化信息识别模型。该模型的目标是判别时态变化和表达变化两种类型，从而提取用于更新小比例尺地图数据的真正变化信息。结合广州市多比例尺地图数据库更新任务及实际数据进行验证，结果显示设计的变化探测模型可以达到90%以上的整体精度。

关键词: 数据更新, 多比例尺, 变化识别, 决策树

Abstract: Change analysis and detection plays important role in the updating of multi-scale databases.When overlap an updated larger-scale dataset and a to-be-updated smaller-scale dataset,people usually focus on temporal changes caused by the evolution of spatial entities.Little attention is paid to the representation changes influenced by map generalization.Using polygonal building data as an example,this study examines the changes from different perspectives,such as the reasons for their occurrence,their performance format.Based on this knowledge,we employ decision tree in field of machine learning to establish a change detection model.The aim of the proposed model is to distinguish temporal changes that need to be applied as updates to the smaller-scale dataset from representation changes.The proposed method is validated through tests using real-world building data from Guangzhou city.The experimental results show the overall precision of change detection is more than 90%,which indicates our method is effective to identify changed objects.

Key words: spatial data updating, multiple scales, change detection, decision tree

中图分类号:

P208

陈利燕, 张新长, 林鸿, 杨敏. 跨比例尺新旧居民地目标变化分析与决策树识别[J]. 测绘学报, 2018, 47(3): 403-412.

CHEN Liyan, ZHANG Xinchang, LIN Hong, YANG Min. Change Analysis and Decision Tree Based Detection Model for Residential Objects across Multiple Scales[J]. Acta Geodaetica et Cartographica Sinica, 2018, 47(3): 403-412.

参考文献

[1] FRITSCH D. GIS Data Revision-visions and Reality[R]. Keynote Speech in Joint ISPRS Commission Workshop on Dynamic and Multi-Dimensional GIS. Beijing:NGCC, 1999.
[2] 陈军, 王东华, 商瑶玲, 等. 国家1:50000数据库更新工程总体设计研究与技术创新[J]. 测绘学报, 2010, 39(1):7-10. CHEN Jun, WANG Donghua, SHANG Yaoling, et al. Master Design and Technical Development for National 1:50 000 Topographic Database Updating Engineering in China[J]. Acta Geodaetica et Cartographica Sinica, 2010, 39(1):7-10.
[3] ZHOU Qi, LI Zhilin. Use of Artificial Neural Networks for Selective Omission in Updating Road Networks[J]. The Cartographic Journal, 2014, 51(1):38-51.
[4] KILPELÄINEN T, SARJAKOSKI T. Incremental Generalization for Multiple Representations of Geographic Objects[M]//MULLER J C, LAGRANGE J P, WEIBEL R. GIS and Generalization. London:Taylor & Francis, 1995:209-218.
[5] HARRIE L, HELLSTRÖM A K. A Prototype System for Propagating Updates between Cartographic Data Sets[J]. The Cartographic Journal, 1999, 36(2):133-140.
[6] HAUNERT J H, SESTER M. Propagating Updates between Linked Datasets of Different Scales[C]//Proceedings of the XXⅡ International Cartographic Conference. A Coruña, Spain:ICC, 2005.
[7] DEVOGELE T, TREVISAN J, RAYNAL L. Building a Multi-scale database with Scale-transition Relationships[C]//Proceedings of the 7th International Symposium on Spatial Data Handling. London:Taylor & Francis, 1996:337-351.
[8] 胡云岗, 陈军, 李志林, 等. 地图数据缩编更新的模式分类与选择[J]. 地理与地理信息科学, 2007, 23(4):22-24. HU Yungang, CHEN Jun, LI Zhilin, et al. Study on Modes of Map Data Updating Based on Generalization[J]. Geography and Geo-information Science, 2007, 23(4):22-24.
[9] 陈军, 林艳, 刘万增, 等. 面向更新的空间目标快照差分类与形式化描述[J]. 测绘学报, 2012, 41(1):108-114. CHEN Jun, LIN Yan, LIU Wanzeng, et al. Formal Classification of Spatial Incremental Changes for Updating[J]. Acta Geodaetica et Cartographica Sinica, 2012, 41(1):108-114.
[10] 张新长, 郭泰圣, 唐铁. 一种自适应的矢量数据增量更新方法研究[J]. 测绘学报, 2012, 41(4):613-619. ZHANG Xinchang, GUO Taisheng, TANG Tie. An Adaptive Method for Incremental Updating of Vector Data[J]. Acta Geodaetica et Cartographica Sinica, 2012, 41(4):613-619.
[11] 唐炉亮, 杨必胜, 徐开明. 基于线状图形相似性的道路数据变化检测[J]. 武汉大学学报(信息科学版), 2008, 33(4):367-370. TANG Luliang, YANG Bisheng, XU Kaiming. The Road Data Change Detection Based on Linear Shape Similarity[J]. Geomatics and Information Science of Wuhan University, 2008, 33(4):367-370.
[12] 林艳, 陈军, 刘万增, 等. 面状水系伪增量剔除的拓扑量化法[J]. 武汉大学学报(信息科学版), 2012, 37(12):1504-1507. LIN Yan, CHEN Jun, LIU Wanzeng, et al. Topological Quantitatively Method for Spurious Increments Removed of Area Water[J]. Geomatics and Information Science of Wuhan University, 2012, 37(12):1504-1507.
[13] 林艳, 陈军, 赵仁亮, 等. 顾及时空目标边界不一致性的增量识别计算[J]. 测绘学报, 2014, 43(4):411-418. DOI:10.13485/j.cnki.11-2089.2014.0061. LIN Yan, CHEN Jun, ZHAO Renliang, et al. Increments Recognition and Calculation Considering the Inconsistency of Spatio-temporal Boundaries[J]. Acta Geodaetica et Cartographica Sinica, 2014, 43(4):411-418. DOI:10.13485/j.cnki.11-2089.2014.0061.
[14] QI H B, LI Z L, CHEN J. Automated Change Detection for Updating Settlements at Smaller-scale Maps from Updated Larger-Scale Maps[J]. Journal of Spatial Science, 2010, 55(1):133-146.
[15] 简灿良, 赵彬彬, 王晓密, 等. 多尺度地图面目标变化分类、描述及判别[J]. 武汉大学学报(信息科学版), 2014, 39(8):968-973. JIAN Canliang, ZHAO Binbin, WANG Xiaomi, et al. A Methodology of Change Classification, Formal Description and Identification between Corresponding Areas in Multi-scale Maps[J]. Geomatics and Information Science of Wuhan University, 2014, 39(8):968-973.
[16] 杨敏, 艾廷华, 晏雄锋, 等. 叠置运算支持下的跨比例尺城区居民地数据变化发现与更新[J]. 测绘学报, 2016, 45(4):466-474. DOI:10.11947/j.AGCS.2016.20150302. YANG Min, AI Tinghua, YAN Xiongfeng, et al. Change Detection and Updating by Using Map Overlay for Buildings on Multi-scale Maps[J]. Acta Geodaetica et Cartographica Sinica, 2016, 45(4):466-474. DOI:10.11947/j.AGCS.2016.20150302.
[17] 艾廷华, 郭仁忠. 基于格式塔识别原则挖掘空间分布模式[J]. 测绘学报, 2007, 36(3):302-308. AI Tinghua, GUO Renzhong. Polygon Cluster Pattern Mining Based on Gestalt Principles[J]. Acta Geodaetica et Cartographica Sinica, 2007, 36(3):302-308.
[18] AI Tinghua, KE Shu, YANG Min, et al. Envelope Generation and Simplification of Polylines Using Delaunay Triangulation[J]. International Journal of Geographical Information Science, 2017, 31(2):297-319.
[19] 童小华, 邓愫愫, 史文中. 基于概率的地图实体匹配方法[J]. 测绘学报, 2007, 36(2):210-217. DOI:10.3321/j.issn:1001-1595.2007.02.017. TONG Xiaohua, DENG Susu, SHI Wenzhong. A Probabilistic Theory-based Matching Method[J]. Acta Geodaetica et Cartographica Sinica, 2007, 36(2):210-217. DOI:10.3321/j.issn:1001-1595.2007.02.017.
[20] 黄智深, 钱海忠, 郭敏, 等. 面状居民地匹配骨架线傅里叶变化方法[J]. 测绘学报, 2013, 42(6):913-921, 928. HUANG Zhishen, QIAN Haizhong, GUO Min, et al. Matching Algorithm of Polygon Habitations Based on Their Skeleton-lines Using Fourier Transform[J]. Acta Geodaetica et Cartographica Sinica, 2013, 42(6):913-921, 928.
[21] 赵东保, 盛业华. 全局寻优的矢量道路网自动匹配方法研究[J]. 测绘学报, 2010, 39(4):416-421. ZHAO Dongbao, SHENG Yehua. Research on Automatic Matching of Vector Road Networks Based on Global Optimization[J]. Acta Geodaetica et Cartographica Sinica, 2010, 39(4):416-421.
[22] 张云菲, 杨必胜, 栾学晨. 利用概率松弛法的城市路网自动匹配[J]. 测绘学报, 2012, 41(6):933-939. ZHANG Yunfei, YANG Bisheng, LUAN Xuechen. Automated Matching Urban Road Networks Using Probabilistic Relaxation[J]. Acta Geodaetica et Cartographica Sinica, 2012, 41(6):933-939.
[23] 田文文, 朱欣焰, 呙维. 一种VGI矢量数据增量变化发现的多层次蔓延匹配算法[J]. 武汉大学学报(信息科学版), 2014, 39(8):963-967, 973. TIAN Wenwen, ZHU Xinyan, GUO Wei. A VGI Vector Road Data Increment Distinguishing Research Based on Multilevel Spreading Algorithm[J]. Geomatics and Information Science of Wuhan University, 2014, 39(8):963-967, 973.
[24] 田晶, 艾廷华, 丁绍军. 基于C4.5算法的道路网网格模式识别[J]. 测绘学报, 2012, 41(1):121-126. TIAN Jing, AI Tinghua, DING Shaojun. Grid Pattern Recognition in Road Networks Based on C4.5 Algorithm[J]. Acta Geodaetica et Cartographica Sinica, 2012, 41(1):121-126.
[25] QUINLAN J R. Induction of Decision Trees[J]. Machine Learning, 1986, 1(1):81-106.
[26] QUINLAN J R. C4.5:Programs for Machine Learning[M]. San Francisco, CA, USA:Morgan Kaufmann Publishers Inc., 1993.
[27] BREIMAN L, FRIEDMAN J H, OLSHEN R A, et al. Classification and Regression Trees[M]. Belmont, CA, USA:Wadsworth, 1984.

跨比例尺新旧居民地目标变化分析与决策树识别

Change Analysis and Decision Tree Based Detection Model for Residential Objects across Multiple Scales

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