Volume 43 Issue 12
Dec.  2018
Turn off MathJax
Article Contents
Abstract
References
Related Articles
LI Chengming, YIN Yong, WU Pengda, WU Wei. A Partitioned Dissolution Method for Long and Narrow Patches[J]. Geomatics and Information Science of Wuhan University, 2018, 43(12): 2259-2268. DOI: 10.13203/j.whugis20180274
Citation: LI Chengming, YIN Yong, WU Pengda, WU Wei. A Partitioned Dissolution Method for Long and Narrow Patches[J]. Geomatics and Information Science of Wuhan University, 2018, 43(12): 2259-2268. DOI: 10.13203/j.whugis20180274
shu

A Partitioned Dissolution Method for Long and Narrow Patches

  • 1.

    Chinese Academy of Surveying and Mapping, Beijing 100830, China

  • 2.

    National Engineering Laboratory for Intergrated Aero-Space-Ground-Ocean Big Data Application Technology, Xi'an 710072, China

Funds: 

The National Basic Surveying and Mapping Project A1705

the National Natural Science Foundation of China 41871375

More Information
  • Author Bio:

    LI Chengming, PhD, professor, specialige in digital city, smart city and map generalization automatically. E-mail:cmli@casm.ac.cn

  • Corresponding author:

    YIN Yong, PhD. E-mail:yinyong@casm.ac.cn

  • Received Date: July 14, 2018
  • Published Date: December 04, 2018
    Graphical Abstract
    • Abstract
  • The dissolution operation is a common operation in patch generalization and it involves a large number of computations. Due to limitations in computational power, it is very difficult to process a large number of patches over a large area using traditional dissolution methods. To overcome this limitation, this paper proposes a partitioned dissolution method for long and narrow patches (LN patches) by introducing the block strategy and focusing on the topological changes that occur in the partition lines of LN patches at partition-cell boundaries. Firstly, the topological changes that appear around partition-cell boundaries during the dissolution of LN patches are summarized into four patterns. For each of these patterns, a corresponding method is formulated for reconciling the topological changes of the partition line. Our approach is then validated by using the national geographical conditions data of Chishui City, Guizhou Province. It is experimentally demonstrated that our method is capable of processing large-scale patch data and greatly improves the efficiency of patch dissolution opera-tions. The results of our partitioned dissolution method are also found to be strongly consistent with the unpartitioned method of dissolution. Our method is therefore viable for practical applications.
    • FullText(HTML)
    • References (16)
  • [1]
    艾廷华, 杨帆, 李精忠.第二次土地资源调查数据建库中的土地利用图综合缩编[J].武汉大学学报·信息科学版, 2010, 35 (8): 887-891 http://ch.whu.edu.cn/CN/abstract/abstract1024.shtml

    Ai Tinghua, Yang Fan, Li Jingzhong. Land-use Data Generalization for the Database Construction of the Second Land Resource Survey[J]. Geomatics and Information Science of Wuhan University, 2010, 35(8): 887-891 http://ch.whu.edu.cn/CN/abstract/abstract1024.shtml
    [2]
    Aichholzer O, Aurenhammer F, Alberts D, et al. A Novel Type of Skeleton for Polygons[M]. Berlin, Heidelberg: Springer, 1996
    [3]
    Haunert J H, Sester M. Area Collapse and Road Centerlines Based on Straight Skeletons[J]. GeoInformatica, 2008, 12(2): 169-191 doi: 10.1007/s10707-007-0028-x
    [4]
    Lee D T. Medial Axis Transformation of a Planar Shape[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1982, PAMI-4 (4): 363-369 doi: 10.1109/TPAMI.1982.4767267
    [5]
    Cloppet F, Oliva J M, Stamon G. Angular Bisector Network, a Simplified Generalized Voronoi Diagram: Application to Processing Complex Intersections in Biomedical Images[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000, 22(1): 120-128 doi: 10.1109/34.824824
    [6]
    Ruas A. Multiple Paradigms for Automating Map Generalization: Geometry, Topology, Hierarchical Partitioning and Local Triangulation[C]. ACSM/ASPRS Annual Convention and Exposition, Charlotte, USA, 1995
    [7]
    Ware J M, Jones C B, Bundy G L. A Triangulated Spatial Model for Cartographic Generalization of Areal Objects[C]// Kraak M J, Molenaar M. Advance in GIS Research Ⅱ (the 7th Int Symposium on Spatial Data Handling). London: Taylor & Francis, 1997a: 173-192
    [8]
    Delucia A A, Black R T. A Comprehensice Approach to Automatic Feature Generalization[C]. The 13th International Cartographic Conference, Morelia, Mexico, 1987
    [9]
    艾廷华, 郭仁忠.支持地图综合的面状目标约束Delaunay三角网剖分[J].武汉大学学报·信息科学版, 2000, 25(1): 35-41 http://ch.whu.edu.cn/CN/abstract/abstract5070.shtml

    Ai Tinghua, Guo Renzhong. A Constrained Delaunay Partitioning of Areal Objects to Support Map Generalization[J]. Geomatics and Information Science of Wuhan University, 2000, 25(1): 35-41 http://ch.whu.edu.cn/CN/abstract/abstract5070.shtml
    [10]
    艾廷华, 刘耀林.土地利用数据综合中的聚合与融合[J].武汉大学学报·信息科学版, 2002, 27(5): 486-492 http://ch.whu.edu.cn/CN/abstract/abstract4997.shtml

    Ai Tinghua, Liu Yaolin. Aggregation and Amalgamation in Land-use Data Generalization[J]. Geoma-tics and Information Science of Wuhan University, 2002, 27(5): 486-492 http://ch.whu.edu.cn/CN/abstract/abstract4997.shtml
    [11]
    Penninga F, Verbree E, Quak W, et al. Construction of the Planar Partition Postal Code Map Based on Cadastral Registration[J]. GeoInformatica, 2005, 9(2): 181-204 doi: 10.1007/s10707-005-6430-3
    [12]
    Jones C B, Bundy G L, Ware M J. Map Generalization with a Triangulated Data Structure[J]. Cartography and Geographic Information Systems, 1995, 22(4): 317-331 doi: 10.1559/152304095782540221
    [13]
    Uitermark H, Vogels A, van Oosterom P. Semantic and Geometric Aspects of Integrating Road Networks[M]. Berlin, Heidelberg :Springer, 1999
    [14]
    Touya G. Relevant Space Partitioning for Collaborative Generalization[C]. The 13th Workshop of the ICA Commission on Generalisation and Multiple Representation, Zürich, Switzertand, 2010
    [15]
    Touya G, Berli J, Lokhat I, et al. Experiments to Distribute and Parallelize Map Generalization Processes[J]. The Cartographic Journal, 2017, 54(4): 322-332 doi: 10.1080/00087041.2017.1413787
    [16]
    Thiemann F, Werder S, Globig T, et al. Investigations into Partitioning of Generalization Processes in a Distributed Processing Framework[C]. The 26th International Cartographic Conference, Dresden, Germany, 2013
    • Related Articles

  • Related Articles

    [1]Gan Wenxia, Pan Junjie, Geng Jing, Wang Huini, Hu Xiaodi. A Fusion Method for Infrared and Visible Images in All-weather Road Scenes[J]. Geomatics and Information Science of Wuhan University. DOI: 10.13203/j.whugis20240173
    [2]SONG Zhina, SUI Haigang, LI Yongcheng. A Survey on Ship Detection Technology in High-Resolution Optical Remote Sensing Images[J]. Geomatics and Information Science of Wuhan University, 2021, 46(11): 1703-1715. DOI: 10.13203/j.whugis20200481
    [3]XIANG Tianzhu, GAO Rongrong, YAN Li, XU Zhenliang. Region Feature Based Multi-scale Fusion Method for Thermal Infrared and Visible Images[J]. Geomatics and Information Science of Wuhan University, 2017, 42(7): 911-917. DOI: 10.13203/j.whugis20141007
    [4]ZHANG Lifu, YANG Hang, FANG Conghui, PAN Mao. Thermal Infrared Target Recognition Using Multi-scale Fractal Model[J]. Geomatics and Information Science of Wuhan University, 2012, 37(3): 339-342.
    [5]YING Shen, LI Lin, GAO Yurong. Pedestrian Simulation in Urban Space Based on Visibility Analysis and Agent Techniques[J]. Geomatics and Information Science of Wuhan University, 2011, 36(11): 1367-1370.
    [6]XU Hanqiu, ZHANG Tiejun, LI Chunhua. Cross Comparison of Thermal Infrared Data Between ASTER and Landsat ETM~+ Sensors[J]. Geomatics and Information Science of Wuhan University, 2011, 36(8): 936-940.
    [7]ZHU Zhongmin, GONG Wei, YU Juan, TIAN Liqiao. Applicability Analysis of Transformation Models for Aerosol Optical Depth and Horizontal Visibility[J]. Geomatics and Information Science of Wuhan University, 2010, 35(9): 1086-1090.
    [8]MAO Yue, SONG Xiaoyong, FENG Laiping. Visibility Analysis of X-ray Pulsar Navigation[J]. Geomatics and Information Science of Wuhan University, 2009, 34(2): 222-225.
    [9]YANG Guijun, LIU Qinhuo, LIU Qiang, GU Xingfa. Fusion of Visible and Thermal Infrared Remote Sensing Data Based on GA-SOFM Neural Network[J]. Geomatics and Information Science of Wuhan University, 2007, 32(9): 786-790.
    [10]GONG Shengrong, YANG Shanchao. A Visible Watermarking Algorithm Holding Image Content[J]. Geomatics and Information Science of Wuhan University, 2006, 31(9): 757-760.

  • Cited by

    Periodical cited type(2)

    1. 徐辛超，高阳. 融合跳跃连接网络与双重注意力机制的可见光与红外遥感影像匹配方法. 地球信息科学学报. 2025(03): 766-783 .
    2. 姚国标，张成成，龚健雅，张现军，李兵. 非线性尺度空间改进的光学与SAR影像自动配准. 武汉大学学报(信息科学版). 2024(12): 2249-2260 .

    Other cited types(0)

Catalog

    Get Citation
    PDF
    XML
    Article views PDF downloads Cited by(2)
    Related

    Copyright © 2013 《武汉大学学报·信息科学版》编辑部

    Address：武汉大学文理学部本科生院楼北5楼Post Code：430072

    Tel：027-68778465,68788631E-mail:whuxxb@vip.163.com

    Submit Article

    Submission Guidelines

    e

    Contact Us

    Qrcode

    Supported by: Beijing Renhe Information Technology Co., Ltd.  Baidu Analytics

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return